diff --git a/.DS_Store b/.DS_Store
new file mode 100644
index 0000000..3f96954
Binary files /dev/null and b/.DS_Store differ
diff --git a/.github/.DS_Store b/.github/.DS_Store
new file mode 100644
index 0000000..36b372c
Binary files /dev/null and b/.github/.DS_Store differ
diff --git a/.github/workflows/build-and-push-jupyterlab-image.yml b/.github/workflows/build-and-push-jupyterlab-image.yml
new file mode 100644
index 0000000..d313734
--- /dev/null
+++ b/.github/workflows/build-and-push-jupyterlab-image.yml
@@ -0,0 +1,44 @@
+name: build-and-push-jupyterlab-image
+
+on:
+  workflow_dispatch:  # This allows you to manually trigger the action from GitHub UI.
+
+jobs:
+  
+  build:
+    runs-on: ubuntu-latest
+    
+    steps:
+    
+      - name: Checkout
+        uses: actions/checkout@v3.5.0
+      
+      - name: Set up Docker Buildx
+        id: buildx
+        uses: docker/setup-buildx-action@v2.5.0
+            
+      - name: Login to dockerhub 
+        uses: docker/login-action@v2.1.0
+        with:
+          username: ${{ secrets.DOCKERHUB_USERNAME }}
+          password: ${{ secrets.DOCKERHUB_PASSWORD }}
+
+      - name: Get lowercase repo name (for dynamic tags)
+        id: repo_name  
+        run: |
+          lowercase_name=$(echo ${{ github.event.repository.name }} | tr '[:upper:]' '[:lower:]')
+          echo "::set-output name=repo_name::${lowercase_name}"
+        
+      - name: Build and push latest
+        id: docker_build_jupyterlab
+        uses: docker/build-push-action@v4.0.0
+        with:
+          context: docker/jupyterlab
+          file: docker/jupyterlab/Dockerfile
+          builder: ${{ steps.buildx.outputs.name }}
+          push: true
+          tags: |
+            esiil/${{ steps.repo_name.outputs.repo_name }}_jupyterlab:latest
+     
+      - name: Image digest
+        run: echo ${{ steps.docker_build.outputs.digest }}
diff --git a/.github/workflows/fetch-template.yml b/.github/workflows/fetch-template.yml
new file mode 100644
index 0000000..a332591
--- /dev/null
+++ b/.github/workflows/fetch-template.yml
@@ -0,0 +1,34 @@
+name: Sync with Template Repository
+
+on:
+    workflow_dispatch:
+
+jobs:
+  sync_template:
+    runs-on: ubuntu-latest
+
+    steps:
+    - name: Checkout main repository
+      uses: actions/checkout@v2
+
+    - name: Configure Git for merge
+      run: |
+          git config --global user.name "github-actions" 
+          git config --global user.email "actions@users.noreply.github.com"
+    
+    - name: Fetch template repository
+      run: git fetch --no-tags --no-recurse-submodules https://github.com/CU-ESIIL/Postdoc_OASIS.git +refs/heads/*:refs/remotes/template/*
+
+    - name: Merge changes from template repository
+      run: |
+        git merge --no-commit --no-ff --allow-unrelated-histories template/main || true
+        git checkout --ours .
+        git add .
+        
+    - name: Commit changes
+      run: git commit -am "Merge changes from template repository"
+
+    - name: Push changes
+      uses: ad-m/github-push-action@master
+      with:
+        github_token: ${{ secrets.GITHUB_TOKEN }}
\ No newline at end of file
diff --git a/.github/workflows/gh-pages.yml b/.github/workflows/gh-pages.yml
new file mode 100644
index 0000000..71f39e6
--- /dev/null
+++ b/.github/workflows/gh-pages.yml
@@ -0,0 +1,21 @@
+ name: Publish docs via GitHub
+ on:
+   push:
+     branches:
+       - main
+
+ jobs:
+   build:
+     name: Deploy docs
+     runs-on: ubuntu-latest
+     steps:
+       - uses: actions/checkout@v3
+       - uses: actions/setup-python@v4
+         with:
+           python-version: 3.9
+       - name: run requirements file
+         run:  pip install -r requirements.txt 
+       - name: Deploy docs
+         run: mkdocs gh-deploy --force
+         env:
+           GITHUB_TOKEN: ${{ secrets.GH_TOKEN }}
diff --git a/.gitignore b/.gitignore
new file mode 100644
index 0000000..82b2bbb
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1,48 @@
+# History files
+.Rhistory
+.Rapp.history
+
+# Session Data files
+.RData
+.RDataTmp
+
+# User-specific files
+.Ruserdata
+
+# Example code in package build process
+*-Ex.R
+
+# Output files from R CMD build
+/*.tar.gz
+
+# Output files from R CMD check
+/*.Rcheck/
+
+# RStudio files
+.Rproj.user/
+
+# produced vignettes
+vignettes/*.html
+vignettes/*.pdf
+
+# OAuth2 token, see https://github.com/hadley/httr/releases/tag/v0.3
+.httr-oauth
+
+# knitr and R markdown default cache directories
+*_cache/
+/cache/
+
+# Temporary files created by R markdown
+*.utf8.md
+*.knit.md
+
+# R Environment Variables
+.Renviron
+
+
+
+# translation temp files
+po/*~
+
+# RStudio Connect folder
+rsconnect/
diff --git a/LICENSE b/LICENSE
new file mode 100644
index 0000000..8a9b45c
--- /dev/null
+++ b/LICENSE
@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2023 Environmental Data Science Innovation and Inclusion Lab (ESIIL)
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
diff --git a/README.md b/README.md
new file mode 100644
index 0000000..0935171
--- /dev/null
+++ b/README.md
@@ -0,0 +1,72 @@
+# Postdoc OASIS
+This is the central hub for information pertaining to ESIIL Postdocs
+
+# [Your Name]
+
+Welcome to the [Your Name] repository, part of the Environmental Data Science Innovation and Inclusion Lab (ESIIL). This repository serves as the central hub for our research at ESIIL, hosting your project description, proposals, bio, codebase, and more.
+
+## Your Project
+
+[Provide a brief overview of your project here. Explain what you aim to achieve, the importance of your project, and its expected impact.]
+
+## Project Proposal
+
+[Link to the detailed project proposal document or include the proposal directly in the repository. This should outline the goals, methodologies, anticipated challenges, and projected timelines.]
+
+## Collaborators and Co-Authors 
+
+[List the names and a brief description of people you work with, possibly linking to their personal or professional web pages.]
+
+- **Collaborator 1**: Brief description.
+- **Collaborator 2**: Brief description.
+- ...
+
+## Code Repository
+
+This section of the repository will include all the code developed for the project. You can structure it as follows:
+
+- **Analysis Code**: Scripts for data analysis, statistical modeling, etc.
+- **Data Processing**: Scripts for cleaning, merging, and managing datasets.
+- **Visualization**: Code for creating figures, charts, and interactive visualizations.
+
+## Meeting Notes and Agendas
+
+When you meet with your advisor, collaborators, or a team, you should take notes here. 
+
+## Contributing to This Repository
+
+To maintain the quality and integrity of the repository, please adhere to the following guidelines:
+
+- Make sure all commits have a clear and concise message.
+- Document any major changes or decisions in the meeting notes.
+- Review and merge changes through pull requests to ensure oversight.
+
+## Getting Help
+
+If you encounter any issues or have questions about how to contribute, please refer to the [ESIIL Support Page](https://esiil.org/support) or contact the repository maintainers directly.
+
+## Customize Your Repository
+
+As a new working group, you'll want to make this repository your own. Here's how to get started:
+
+1. **Edit This Readme**: Replace the placeholder content with information about your specific project. Ensure that the introduction, project overview, and objectives clearly reflect your group's research focus.
+
+2. **Update Bio**: Add details about your expertise, role in the project, and professional background. Include links to personal or professional web pages to foster community engagement and collaboration.
+
+3. **Organize Your Code**: Structure your codebase in a way that is logical and accessible. Use directories and clear naming conventions to make it easy for all members to find and contribute to different parts of the project.
+
+4. **Document Your Data**: Include a data directory with README files explaining the datasets, sources, and any preprocessing steps. This will help new members understand and work with the project's data effectively.
+
+5. **Outline Your Methods**: Create a detailed METHODS.md file where you describe the methodologies, software, and tools you will be using in your research. This transparency will support reproducibility and collaborative development.
+
+6. **Set Up Project Management**: Utilize the 'Issues' and 'Projects' features on GitHub to track tasks, discuss ideas, and manage your workflow. This can help in maintaining a clear view of progress and priorities.
+
+7. **Add a License**: Choose and include an appropriate open-source license for your project, ensuring that the broader community understands how they can use and contribute to your work.
+
+8. **Create Contribution Guidelines**: Establish a CONTRIBUTING.md file with instructions for members on how to propose changes, submit issues, and contribute code.
+
+9. **Review and Merge Workflow**: Decide on a workflow for reviewing and merging changes. Will you use branch protection? Who will have merge privileges? Document this process to avoid confusion.
+
+10. **Establish Communication Channels**: Beyond GitHub, set up additional communication channels like Slack, Discord, or email lists for quick and informal discussions.
+
+Remember, the goal is to make your repository clear, accessible, and useful for all current and future members of your working group. Happy researching!
diff --git a/docker/.DS_Store b/docker/.DS_Store
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diff --git a/docker/jupyterlab/Dockerfile b/docker/jupyterlab/Dockerfile
new file mode 100644
index 0000000..d9a7447
--- /dev/null
+++ b/docker/jupyterlab/Dockerfile
@@ -0,0 +1,136 @@
+FROM jupyter/r-notebook:hub-4.0.1 
+
+USER root
+
+# Set up package manager
+RUN apt-get install -y apt-transport-https && \
+    apt-get clean && apt-get update && apt-get install -y software-properties-common && \
+    add-apt-repository multiverse && \
+    apt-get clean && rm -rf /var/lib/apt/lists/*
+
+# Install some base software
+RUN apt-get update --yes && \
+    apt-get install --yes \
+    fonts-dejavu \
+    unixodbc \
+    unixodbc-dev \
+    r-base \
+    r-cran-rodbc && \
+    apt-get clean && rm -rf /var/lib/apt/lists/*
+
+# Add sudo to jovyan user
+RUN apt update && \
+    apt install -y sudo && \
+    apt clean && \
+    rm -rf /var/lib/apt/lists/*
+    
+# This is where we can control which root permissions the jovyan user will have
+ARG PRIV_CMDS='/bin/ch*,/bin/cat,/bin/gunzip,/bin/tar,/bin/mkdir,/bin/ps,/bin/mv,/bin/cp,/usr/bin/apt*,/usr/bin/pip*,/bin/yum,/opt,/opt/conda/bin/*,/usr/bin/*'
+
+RUN usermod -aG sudo jovyan && \
+    echo "$LOCAL_USER ALL=NOPASSWD: $PRIV_CMDS" >> /etc/sudoers
+RUN addgroup jovyan
+RUN usermod -aG jovyan jovyan
+
+# Install RStudio
+RUN apt-get update && apt-get install --yes gdebi-core && \
+    wget https://download2.rstudio.org/server/jammy/amd64/rstudio-server-2023.09.1-494-amd64.deb && \
+    gdebi -n rstudio-server-2023.09.1-494-amd64.deb && \
+    rm rstudio-server-2023.09.1-494-amd64.deb && \
+    apt-get clean && rm -rf /var/lib/apt/lists/*
+
+# Install Geospatial libraries
+RUN apt-get update && \
+    apt install -y \
+    gdal-bin \
+    lbzip2 \
+    libfftw3-dev \
+    libgdal-dev \
+    libgeos-dev \
+    libgsl0-dev \
+    libgl1-mesa-dev \
+    libglu1-mesa-dev \
+    libhdf4-alt-dev \
+    libhdf5-dev \
+    libjq-dev \
+    libpq-dev \
+    libproj-dev \
+    libprotobuf-dev \
+    libnetcdf-dev \
+    libsqlite3-dev \
+    libudunits2-dev \
+    lsb-release \
+    netcdf-bin \
+    postgis \
+    protobuf-compiler \
+    sqlite3 \
+    tk-dev \
+    libfmt-dev \
+    unixodbc-dev && \
+    apt-get clean && rm -rf /var/lib/apt/lists/*
+
+# Fix RStudio / Conda openssl version mismatch
+RUN wget https://www.openssl.org/source/openssl-3.2.0.tar.gz && \
+    tar xfz openssl-3.2.0.tar.gz && \
+    mkdir openssl-build && cd openssl-build && \
+    ../openssl-3.2.0/Configure --libdir=/lib/x86_64-linux-gnu/ && \
+    make && \
+    make install
+
+# Update permissions for /opt/conda
+RUN mkdir /usr/local/bin/start-notebook.d && \
+    chown -R jovyan:users /opt/conda/share /usr/local/share /usr/local/bin/start-notebook.d 
+
+USER jovyan
+
+# Install jupyterlab and rstudio dependencies
+RUN conda install -c conda-forge \ 
+    jupyter_client \ 
+    jupyter_core \ 
+    jupyterlab_server \ 
+    jupyter_server \
+    r-rgl \
+    r-htmlwidgets \
+    r-htmltools && \ 
+    jupyter lab clean
+
+# reinstall R packages. Here is where you add any new R packages you would like to install 
+RUN mamba install --quiet --yes \
+    r-base \
+    r-tidyverse \
+    r-terra \
+    r-future \
+    r-future.apply \
+    r-furrr \
+    && \ 
+    mamba clean --all -f -y
+
+# Install Jupyter Lab Proxy extensions (cards in Launcher)
+RUN pip install jupyter-rsession-proxy jupyter-server-proxy jupyter-shiny-proxy jupyterlab-git 
+
+# Install Mamba Gator package manager
+RUN rm -f ~/.jupyter/lab/workspaces/default* && \
+    mamba install -y -c conda-forge mamba_gator
+
+# Install and configure jupyter lab 
+COPY jupyter_notebook_config.json /opt/conda/etc/jupyter/jupyter_notebook_config.json
+
+# Rebuild the Jupyter Lab with new tools
+RUN jupyter lab build
+
+# Build Conda environment. Any packages you would like to install with conda need to be added to the environment.yml file in this Dockerfiles directory
+RUN conda update -y conda && \
+    conda config --remove channels conda-forge && \
+    conda config --add channels conda-forge
+WORKDIR /home/jovyan
+COPY environment.yml /home/jovyan/ 
+RUN mamba env create -f /home/jovyan/environment.yml
+RUN . /opt/conda/etc/profile.d/conda.sh && conda deactivate && conda activate custom && python -m ipykernel install --name custom && pip install jupyter_contrib_nbextensions
+
+# Install R packages from CRAN and GitHub
+RUN R -e "remotes::install_github('tomroh/ecoregions')"
+RUN R -e "install.packages('mblm', repos='http://cran.rstudio.com/')"
+
+# Set any required environment variables 
+ENV PROJ_LIB=/opt/conda/envs/custom/share/proj
+RUN echo "PROJ_LIB=/opt/conda/envs/custom/share/proj" > /home/jovyan/.Renviron
diff --git a/docker/jupyterlab/environment.yml b/docker/jupyterlab/environment.yml
new file mode 100644
index 0000000..d46cab5
--- /dev/null
+++ b/docker/jupyterlab/environment.yml
@@ -0,0 +1,40 @@
+name: custom
+channels:
+  - conda-forge
+  - defaults
+
+dependencies:
+  - python=3.10
+  
+  - pip:
+      - affine==2.4.0
+      - aiosignal==1.3.1
+      - appdirs==1.4.4
+      - attrs==23.1.0
+      - certifi==2023.7.22
+      - charset-normalizer==3.1.0
+      - click==8.1.3
+      - click-plugins==1.1.1
+      - cligj==0.7.2
+  
+  # Core scientific python
+  - numpy
+  - matplotlib
+  - rioxarray
+  - geopandas
+  - gdal
+
+  # Jupyter Lab Environment & Kernel
+  - papermill
+  - autopep8
+  - jupyterlab
+  - notebook
+  - ipython
+  - nbclean
+  - nbresuse
+  - jupyterlab-geojson
+  - nb_conda_kernels
+  - ipykernel
+  
+  # openssh because openssl bin path is in conda now for Rstudio issue
+  - openssh  
diff --git a/docker/jupyterlab/jupyter_notebook_config.json b/docker/jupyterlab/jupyter_notebook_config.json
new file mode 100644
index 0000000..b9f06f7
--- /dev/null
+++ b/docker/jupyterlab/jupyter_notebook_config.json
@@ -0,0 +1,11 @@
+{
+    "NotebookApp": {
+      "allow_origin" : "*",
+        "token":"",
+        "password":"",
+      "nbserver_extensions": {
+        "jupyterlab": true,
+        "mamba_gator": true
+      }
+    }
+  }  
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+# [Your Name]
+
+Welcome to the [Your Name] repository, part of the Environmental Data Science Innovation and Inclusion Lab (ESIIL). This repository serves as the central hub for our research at ESIIL, hosting your project description, proposals, bio, codebase, and more.
+
+## Your Project
+
+[Provide a brief overview of your project here. Explain what you aim to achieve, the importance of your project, and its expected impact.]
+
+## Project Proposal
+
+[Link to the detailed project proposal document or include the proposal directly in the repository. This should outline the goals, methodologies, anticipated challenges, and projected timelines.]
+
+## Collaborators
+- ...
+
+## Code Repository
+
+This section of the repository will include all the code developed for the project. You can structure it as follows:
+
+- **Analysis Code**: Scripts for data analysis, statistical modeling, etc.
+- **Data Processing**: Scripts for cleaning, merging, and managing datasets.
+- **Visualization**: Code for creating figures, charts, and interactive visualizations.
+
+## Meeting Notes and Agendas
+
+Meeting notes and agendas will be regularly updated here to keep all group members informed and engaged with the progress and direction of the project.
+
+## Contributing to This Repository
+
+We welcome contributions from all group members. To maintain the quality and integrity of the repository, please adhere to the following guidelines:
+
+- Make sure all commits have a clear and concise message.
+- Document any major changes or decisions in the meeting notes.
+- Review and merge changes through pull requests to ensure oversight.
+
+## Getting Help
+
+If you encounter any issues or have questions about how to contribute, please refer to the [ESIIL Support Page](https://esiil.org/support) or contact the repository maintainers directly.
+
+## Customize Your Repository
+
+As a new working group, you'll want to make this repository your own. Here's how to get started:
+
+1. **Edit This Readme**: Replace the placeholder content with information about your specific project. Ensure that the introduction, project overview, and objectives clearly reflect your group's research focus.
+
+2. **Update Group Member Bios**: Add details about each group member's expertise, role in the project, and professional background. Include links to personal or professional web pages to foster community engagement and collaboration.
+
+3. **Organize Your Code**: Structure your codebase in a way that is logical and accessible. Use directories and clear naming conventions to make it easy for all members to find and contribute to different parts of the project.
+
+4. **Document Your Data**: Include a data directory with README files explaining the datasets, sources, and any preprocessing steps. This will help new members understand and work with the project's data effectively.
+
+5. **Outline Your Methods**: Create a detailed METHODS.md file where you describe the methodologies, software, and tools you will be using in your research. This transparency will support reproducibility and collaborative development.
+
+6. **Set Up Project Management**: Utilize the 'Issues' and 'Projects' features on GitHub to track tasks, discuss ideas, and manage your workflow. This can help in maintaining a clear view of progress and priorities.
+
+7. **Add a License**: Choose and include an appropriate open-source license for your project, ensuring that the broader community understands how they can use and contribute to your work.
+
+8. **Create Contribution Guidelines**: Establish a CONTRIBUTING.md file with instructions for members on how to propose changes, submit issues, and contribute code.
+
+9. **Review and Merge Workflow**: Decide on a workflow for reviewing and merging changes. Will you use branch protection? Who will have merge privileges? Document this process to avoid confusion.
+
+10. **Establish Communication Channels**: Beyond GitHub, set up additional communication channels like Slack, Discord, or email lists for quick and informal discussions.
+
+Remember, the goal is to make your repository clear, accessible, and useful for all current and future members of your working group. Happy researching!
+
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+Pulling Sentinal 2 data
+================
+Ty Tuff, ESIIL Data Scientist
+2023-10-27
+
+# Set Java Options
+
+``` r
+# Run these Java options before anything else.
+options(java.parameters = "-Xmx64G")
+options(timeout = max(600, getOption("timeout")))
+```
+
+# R libraries and global setting.
+
+``` r
+#library(Rcpp)
+library(sf)
+library(gdalcubes)
+library(rstac)
+library(gdalUtils)
+library(terra)
+library(rgdal)
+library(reshape2)
+library(osmdata)
+library(terra)
+library(dplyr)
+#library(glue)
+library(stars)
+library(ggplot2)
+library(colorspace)
+library(geos)
+#library(glue)
+library(osmdata)
+library(ggthemes)
+library(tidyr)
+gdalcubes_options(parallel = 8)
+
+sf::sf_extSoftVersion()
+```
+
+              GEOS           GDAL         proj.4 GDAL_with_GEOS     USE_PROJ_H 
+          "3.11.0"        "3.5.3"        "9.1.0"         "true"         "true" 
+              PROJ 
+           "9.1.0" 
+
+``` r
+gdalcubes_gdal_has_geos()
+```
+
+    [1] TRUE
+
+# Start timer
+
+``` r
+start <- Sys.time()
+```
+
+# Set color palette
+
+``` r
+library(ggtern)
+our_yellow <- rgb2hex(r = 253, g = 201, b = 51)
+our_green <- rgb2hex(r = 10, g = 84, b = 62)
+our_grey <- rgb2hex(r = 92, g = 96, b = 95)
+our_white <- rgb2hex(r = 255, g = 255, b = 255)
+```
+
+# Load area of interest
+
+``` r
+# Read the shapefile into an sf object
+aoi_total <- st_read("/Users/ty/Documents/Github/Southern_California_Edison_Fire_Risk/SCE_Fire_Zone_V2/SCE_Fire_Zone_V2.shp") %>% 
+  st_as_sf()
+```
+
+    Reading layer `SCE_Fire_Zone_V2' from data source 
+      `/Users/ty/Documents/Github/Southern_California_Edison_Fire_Risk/SCE_Fire_Zone_V2/SCE_Fire_Zone_V2.shp' 
+      using driver `ESRI Shapefile'
+    Simple feature collection with 12 features and 5 fields
+    Geometry type: POLYGON
+    Dimension:     XY
+    Bounding box:  xmin: 176062.4 ymin: 3674043 xmax: 764123.1 ymax: 4254012
+    Projected CRS: NAD83 / UTM zone 11N
+
+``` r
+# Plot the entire spatial dataset
+plot(aoi_total)
+```
+
+![](Pull_Sentinal2_l2_data_files/figure-gfm/load_aoi_polygon-1.png)
+
+``` r
+# Filter the dataset to obtain the geometry with OBJECTID 5
+aoi <- aoi_total %>%
+  filter(OBJECTID == 5)
+
+# Obtain and plot the bounding box of the filtered geometry
+shape_bbox <- st_bbox(aoi)
+plot(aoi)
+```
+
+![](Pull_Sentinal2_l2_data_files/figure-gfm/load_aoi_polygon-2.png)
+
+``` r
+# Transform the filtered geometry to EPSG:4326 and store its bounding box
+aoi %>% st_transform("EPSG:4326") %>%
+  st_bbox() -> bbox_4326
+
+# Transform the filtered geometry to EPSG:32618 and store its bounding box
+aoi %>% st_transform("EPSG:32618") %>%
+  st_bbox() -> bbox_32618
+```
+
+# Arrange STAC collection
+
+In this code chunk, the primary goal is to search for and obtain
+satellite imagery data. The data source being tapped into is a
+SpatioTemporal Asset Catalog (STAC) provided by an online service
+(earth-search by Element84). Here’s a breakdown:
+
+A connection is established with the STAC service, searching
+specifically within the “sentinel-s2-l2a-cogs” collection. -The search
+is spatially constrained to a bounding box (bbox_4326) and temporally
+limited to a range of one day, between May 15 and May 16, 2021. -Once
+the search is conducted, the desired assets or spectral bands from the
+returned satellite images are defined, ranging from Band 1 (B01) to Band
+12 (B12) and including the Scene Classification Layer (SCL). -These
+bands are then organized into an image collection for further processing
+or analysis.
+
+``` r
+# Initialize STAC connection
+s = stac("https://earth-search.aws.element84.com/v0")
+
+# Search for Sentinel-2 images within specified bounding box and date range
+items = s %>%
+    stac_search(collections = "sentinel-s2-l2a-cogs",
+                bbox = c(bbox_4326["xmin"], 
+                         bbox_4326["ymin"],
+                         bbox_4326["xmax"], 
+                         bbox_4326["ymax"]), 
+                datetime = "2021-05-15/2021-05-16") %>%
+    post_request() %>%
+    items_fetch(progress = FALSE)
+
+# Print number of found items
+length(items$features)
+```
+
+    [1] 12
+
+``` r
+# Prepare the assets for analysis
+library(gdalcubes)
+assets = c("B01", "B02", "B03", "B04", "B05", "B06", 
+           "B07", 
+           "B08", "B8A", "B09", "B11", "B12", "SCL")
+s2_collection = stac_image_collection(items$features, asset_names = assets)
+
+# Display the image collection
+s2_collection
+```
+
+    Image collection object, referencing 12 images with 13 bands
+    Images:
+                          name      left      top   bottom     right
+    1 S2B_11SNS_20210515_1_L2A -117.0002 33.43957 32.44372 -115.8191
+    2 S2B_11SPS_20210515_1_L2A -115.9361 33.43490 32.42937 -114.7436
+    3 S2B_11SQS_20210515_0_L2A -114.8732 33.42092 32.41918 -113.9566
+    4 S2B_12STB_20210515_0_L2A -114.2244 33.40433 32.61015 -113.9559
+    5 S2B_11SNT_20210515_0_L2A -117.0002 34.34164 33.34577 -115.8066
+    6 S2B_11SPT_20210515_0_L2A -115.9253 34.33683 33.33091 -114.7198
+                 datetime        srs
+    1 2021-05-15T18:35:13 EPSG:32611
+    2 2021-05-15T18:35:10 EPSG:32611
+    3 2021-05-15T18:35:06 EPSG:32611
+    4 2021-05-15T18:35:01 EPSG:32612
+    5 2021-05-15T18:34:59 EPSG:32611
+    6 2021-05-15T18:34:55 EPSG:32611
+    [ omitted 6 images ] 
+
+    Bands:
+       name offset scale unit nodata image_count
+    1   B01      0     1                      12
+    2   B02      0     1                      12
+    3   B03      0     1                      12
+    4   B04      0     1                      12
+    5   B05      0     1                      12
+    6   B06      0     1                      12
+    7   B07      0     1                      12
+    8   B08      0     1                      12
+    9   B09      0     1                      12
+    10  B11      0     1                      12
+    11  B12      0     1                      12
+    12  B8A      0     1                      12
+    13  SCL      0     1                      12
+
+# Define view window
+
+In this code chunk, a ‘view’ on the previously obtained satellite image
+collection is being defined. Think of this as setting up a specific lens
+or perspective to look at the satellite data:
+
+-The view is set to the coordinate reference system EPSG:32618. -Spatial
+resolution is defined as 100x100 meters. -Temporal resolution is defined
+monthly (P1M), even though the actual range is only one day. -When there
+are multiple values in a grid cell or timeframe, they are aggregated
+using the median value. -If any resampling is needed, the nearest
+neighbor method is used (near). -The spatial and temporal extents are
+constrained to specific values. -By defining this view, it allows for
+consistent analysis and visualization of the image collection within the
+specified spatial and temporal resolutions and extents.
+
+``` r
+# Define a specific view on the satellite image collection
+v = cube_view(
+    srs = "EPSG:32618", 
+    dx = 100, 
+    dy = 100, 
+    dt = "P1M", 
+    aggregation = "median", 
+    resampling = "near",
+    extent = list(
+        t0 = "2021-05-15", 
+        t1 = "2021-05-16",
+        left = bbox_32618["xmin"], 
+        right = bbox_32618["xmax"],
+        top = bbox_32618["ymax"], 
+        bottom = bbox_32618["ymin"]
+    )
+)
+
+# Display the defined view
+v
+```
+
+    A data cube view object
+
+    Dimensions:
+                    low              high count pixel_size
+    t        2021-05-01        2021-05-31     1        P1M
+    y  4471226.41402451  4741326.41402451  2701        100
+    x -3463720.00044994 -3191420.00044994  2723        100
+
+    SRS: "EPSG:32618"
+    Temporal aggregation method: "median"
+    Spatial resampling method: "near"
+
+# Pull data
+
+In this chunk, the primary aim is to transform and prepare satellite
+imagery data for analysis:
+
+-The current time is stored in variable a for tracking the time taken by
+the process. -The previously defined ‘view’ on the satellite imagery, v,
+is used to create a raster cube, a multi-dimensional array containing
+the satellite data. This raster cube contains spatial, spectral, and
+temporal data. -The desired spectral bands are selected. -The data is
+limited to a specific area of interest, aoi. -The band names are renamed
+to their respective wavelengths in nanometers for clarity. -A subset of
+the data, comprising 50,000 random samples, is selected. -Unwanted
+columns are removed, and the dataset is transformed into a long format,
+where each row represents a particular date and wavelength combination.
+-The entire process duration is computed by taking the difference
+between the end time (b) and the start time (a). -The transformed
+dataset y is then displayed.
+
+``` r
+# Record start time
+a <- Sys.time()
+
+# Transform the satellite image collection into a raster cube
+x <- s2_collection %>%
+    raster_cube(v) %>%
+    select_bands(c("B01", "B02", "B03", "B04", 
+                   "B05", "B06", "B07", "B08", 
+                   "B8A", "B09", "B11", "B12")) %>%
+    extract_geom(aoi) %>%
+    rename(
+        "time" = "time",
+        "443" = "B01",
+        "490" = "B02",
+        "560" = "B03",
+        "665" = "B04",
+        "705" = "B05",
+        "740" = "B06",
+        "783" = "B07",
+        "842" = "B08",
+        "865" = "B8A",
+        "940" = "B09",
+        "1610" = "B11",
+        "2190" = "B12"
+    )
+
+# Sample, transform and prepare data for analysis
+y <- x %>%
+    slice_sample(n = 50000) %>%
+    select(-FID) %>%
+    pivot_longer(!time, names_to = "wavelength_nm", values_to = "reflectance") %>%
+    mutate(wavelength_nm = as.numeric(wavelength_nm))
+
+# Record end time and compute duration
+b <- Sys.time()
+processing_time <- difftime(b, a)
+
+# Display the processing time and transformed dataset
+processing_time
+```
+
+    Time difference of 1.23593 mins
+
+``` r
+y
+```
+
+    # A tibble: 600,000 × 3
+       time       wavelength_nm reflectance
+       <chr>              <dbl>       <dbl>
+     1 2021-05-01           443        1855
+     2 2021-05-01           490        2255
+     3 2021-05-01           560        2884
+     4 2021-05-01           665        3711
+     5 2021-05-01           705        3990
+     6 2021-05-01           740        4009
+     7 2021-05-01           783        4078
+     8 2021-05-01           842        4219
+     9 2021-05-01           865        4060
+    10 2021-05-01           940        4120
+    # ℹ 599,990 more rows
+
+# Base plot
+
+``` r
+# Set custom colors for the plot
+our_green <- "#4CAF50"
+our_white <- "#FFFFFF"
+our_yellow <- "#FFEB3B"
+
+# Create a 2D density plot
+day_density <- ggplot(data = y, aes(x = wavelength_nm, y = reflectance, group = time)) + 
+  stat_smooth(color = our_green, fill = "lightgrey") +
+  geom_density2d(colour = "black", bins = 10, alpha = 0.1) +
+  stat_density2d(aes(alpha = ..level.., fill = ..level..), 
+                 linewidth = 2, bins = 10, geom = "polygon") + 
+  scale_fill_gradient(low = our_white, high = our_yellow) +
+  scale_alpha(range = c(0.00, 0.8), guide = FALSE) +
+  theme_tufte() +
+  xlab("wavelength") +
+  ylab("reflectance") +
+  ylim(0, 16000) +
+  theme(
+    aspect.ratio = 5/14, 
+    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1, 
+                               colour = c("darkblue", "blue", "green", "red", 
+                                          "darkred", "darkred", "darkred", "darkred", 
+                                          "darkred", "black", "black", "black", "black")),
+    axis.title.x = element_blank(),
+    axis.title.y = element_blank(),
+    plot.margin = margin(t = 30, r = 10, b = 40, l = 18)
+  ) +
+  scale_x_continuous(breaks = c(443, 490, 560, 665, 705, 740, 783, 842, 865, 940, 1610, 2190))
+
+# Display the plot
+day_density
+```
+
+![](Pull_Sentinal2_l2_data_files/figure-gfm/base_plot-1.png)
+
+# Inlay 1 - geographic zone
+
+``` r
+guide_map <- ggplot(data= aoi_total) +
+  geom_sf(fill=our_yellow, color=our_white) +
+  geom_sf(data= aoi, fill=our_green, color=our_white) +
+  theme_tufte()+
+  ggtitle("Zone 5")+
+  theme(axis.text.x=element_blank(), #remove x axis labels
+        axis.ticks.x=element_blank(), #remove x axis ticks
+        axis.text.y=element_blank(),  #remove y axis labels
+        axis.ticks.y=element_blank()  #remove y axis ticks, bg=none
+        )+ theme(plot.title = element_text(hjust=0.8, vjust = -2))
+guide_map
+```
+
+![](Pull_Sentinal2_l2_data_files/figure-gfm/aoi_inlay-1.png)
+
+# Inlay 2 - date text
+
+``` r
+library(geosphere)
+aoi_total |> st_centroid()  |> st_transform(crs="+proj=longlat") |> st_coordinates() |> colMeans() -> lat_long
+
+daylength_line <- daylength(lat = lat_long[2], 1:365)
+
+daylengths <- data.frame(time= 1:365, daylength = daylength_line)
+
+library(lubridate)
+
+# Create a template date object
+date <- as.POSIXlt("2021-05-15")
+
+doy <- format(date, format = "%j") |> as.numeric()
+
+display_date <- format(date, format="%e %B %Y   ")
+```
+
+# Inlay 3 - daylength
+
+``` r
+date_inlay <- ggplot(data=daylengths) + 
+ 
+  ggtitle("Daylength")+
+  geom_ribbon(aes(x=time, ymin=daylength, ymax=15), fill=our_grey, alpha=0.5) +
+  geom_ribbon(aes(x=time, ymax=daylength, ymin=9), fill=our_yellow, alpha=1) +
+  geom_hline(yintercept=12, color=our_white) +
+ geom_vline(xintercept=doy, color=our_green, size=1) +
+  theme_tufte() +
+  ylim(9,15) +
+  theme(axis.text.y=element_blank(),
+        axis.ticks.y=element_blank(),
+        axis.title.y=element_blank(),
+        axis.title.x=element_blank(),
+        axis.text.x=element_blank(),
+        axis.ticks.x=element_blank()) + theme(plot.title = element_text(hjust=0.5, vjust = 0))
+date_inlay
+```
+
+![](Pull_Sentinal2_l2_data_files/figure-gfm/date_inlay-1.png)
+
+# Ensemble map assembly
+
+``` r
+library(cowplot)
+library(magick)
+map_overlay <- ggdraw(day_density) + 
+  draw_plot(guide_map, x = 1.08, y = 1, hjust = 1, vjust = 1, width = 0.3, height = 0.3)+
+  draw_plot(date_inlay, x = 1, y = 0.35, hjust = 1, vjust = 1, width = 0.1, height = 0.25)+
+  geom_text(aes(x=1, y=0.08, label=display_date, hjust = 1), color=our_grey, cex=3, fontface='bold') +
+ # draw_image("Ty_powerline_plots/Southern_California_Edison_Logo.png", x = -0.24, y = 0.38, scale=.3)+
+ # draw_image("Ty_powerline_plots/earthlab_logo.png", x = -0.38, y = 0.38, scale=.25)+
+  geom_text(aes(x=0.4, y=.9, label="Spectral library - Monthly average"), color=our_green, hjust = 0, cex=8, fontface='bold') +
+  geom_text(aes(x=0.01, y=.04, 
+    label="Created by ESIIL (T. Tuff) for Fall Hackathon -- October 2023. Sentinel 2 Data from 'https://earth-search.aws.element84.com/v0'"), color=our_grey, hjust  = 0, cex=3) +
+geom_text(aes(x=0.4, y=.1, label="wavelength (nm)"), color=our_grey, hjust = 0, cex=4, fontface='bold') +
+geom_text(aes(x=0.01, y=.5,angle = 90, label="reflectance"), color=our_grey, hjust = 0, cex=4, fontface='bold')
+map_overlay
+```
+
+![](Pull_Sentinal2_l2_data_files/figure-gfm/map_assembly-1.png)
+
+# Save map
+
+``` r
+ggsave(map_overlay, file="day_density_15_May_2021_zone_5.png", bg="white", dpi = 600, width = 12,
+  height = 5)
+```
+
+# End timer
+
+``` r
+end <- Sys.time()
+difftime(end,start)
+```
+
+    Time difference of 3.2202 mins
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diff --git a/docs/resources/Pull_Sentinal2_l2_data_files/libs/bootstrap/bootstrap-icons.woff b/docs/resources/Pull_Sentinal2_l2_data_files/libs/bootstrap/bootstrap-icons.woff
new file mode 100644
index 0000000..b26ccd1
Binary files /dev/null and b/docs/resources/Pull_Sentinal2_l2_data_files/libs/bootstrap/bootstrap-icons.woff differ
diff --git a/docs/resources/Pull_Sentinal2_l2_data_files/libs/bootstrap/bootstrap.min.css b/docs/resources/Pull_Sentinal2_l2_data_files/libs/bootstrap/bootstrap.min.css
new file mode 100644
index 0000000..2b6003a
--- /dev/null
+++ b/docs/resources/Pull_Sentinal2_l2_data_files/libs/bootstrap/bootstrap.min.css
@@ -0,0 +1,10 @@
+/*!
+ * Bootstrap v5.1.3 (https://getbootstrap.com/)
+ * Copyright 2011-2021 The Bootstrap Authors
+ * Copyright 2011-2021 Twitter, Inc.
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[page-bottom]}.page-full{grid-column:screen-start/screen-end !important}.page-columns>*{grid-column:body-content-start/body-content-end}.page-columns.column-page>*{grid-column:page-start/page-end}.page-columns.column-page-left>*{grid-column:page-start/body-content-end}.page-columns.column-page-right>*{grid-column:body-content-start/page-end}.page-rows{grid-auto-rows:auto}.header{grid-column:screen-start/screen-end;grid-row:page-top/contents-top}#quarto-content{padding:0;grid-column:screen-start/screen-end;grid-row:contents-top/contents-bottom}body.floating .sidebar.sidebar-navigation{grid-column:page-start/body-start;grid-row:content-top/page-bottom}body.docked .sidebar.sidebar-navigation{grid-column:screen-start/body-start;grid-row:content-top/page-bottom}.sidebar.toc-left{grid-column:page-start/body-start;grid-row:content-top/page-bottom}.sidebar.margin-sidebar{grid-column:body-end/page-end;grid-row:content-top/page-bottom}.page-columns 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diff --git a/docs/resources/Pull_Sentinal2_l2_data_files/libs/bootstrap/bootstrap.min.js b/docs/resources/Pull_Sentinal2_l2_data_files/libs/bootstrap/bootstrap.min.js
new file mode 100644
index 0000000..cc0a255
--- /dev/null
+++ b/docs/resources/Pull_Sentinal2_l2_data_files/libs/bootstrap/bootstrap.min.js
@@ -0,0 +1,7 @@
+/*!
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+  * Copyright 2011-2021 The Bootstrap Authors (https://github.com/twbs/bootstrap/graphs/contributors)
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+  */
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e=t.state,i=t.options,n=t.name,s=i.offset,o=void 0===s?[0,0]:s,r=Lt.reduce((function(t,i){return t[i]=function(t,e,i){var n=Ut(t),s=[bt,mt].indexOf(n)>=0?-1:1,o="function"==typeof i?i(Object.assign({},e,{placement:t})):i,r=o[0],a=o[1];return r=r||0,a=(a||0)*s,[bt,_t].indexOf(n)>=0?{x:a,y:r}:{x:r,y:a}}(i,e.rects,o),t}),{}),a=r[e.placement],l=a.x,c=a.y;null!=e.modifiersData.popperOffsets&&(e.modifiersData.popperOffsets.x+=l,e.modifiersData.popperOffsets.y+=c),e.modifiersData[n]=r}},Pe={name:"popperOffsets",enabled:!0,phase:"read",fn:function(t){var e=t.state,i=t.name;e.modifiersData[i]=Ce({reference:e.rects.reference,element:e.rects.popper,strategy:"absolute",placement:e.placement})},data:{}},je={name:"preventOverflow",enabled:!0,phase:"main",fn:function(t){var e=t.state,i=t.options,n=t.name,s=i.mainAxis,o=void 0===s||s,r=i.altAxis,a=void 0!==r&&r,l=i.boundary,c=i.rootBoundary,h=i.altBoundary,d=i.padding,u=i.tether,f=void 0===u||u,p=i.tetherOffset,m=void 0===p?0:p,g=ke(e,{boundary:l,rootBoundary:c,padding:d,altBoundary:h}),_=Ut(e.placement),b=ce(e.placement),v=!b,y=ee(_),w="x"===y?"y":"x",E=e.modifiersData.popperOffsets,A=e.rects.reference,T=e.rects.popper,O="function"==typeof m?m(Object.assign({},e.rects,{placement:e.placement})):m,C={x:0,y:0};if(E){if(o||a){var k="y"===y?mt:bt,L="y"===y?gt:_t,x="y"===y?"height":"width",D=E[y],S=E[y]+g[k],N=E[y]-g[L],I=f?-T[x]/2:0,P=b===wt?A[x]:T[x],j=b===wt?-T[x]:-A[x],M=e.elements.arrow,H=f&&M?Kt(M):{width:0,height:0},B=e.modifiersData["arrow#persistent"]?e.modifiersData["arrow#persistent"].padding:{top:0,right:0,bottom:0,left:0},R=B[k],W=B[L],$=oe(0,A[x],H[x]),z=v?A[x]/2-I-$-R-O:P-$-R-O,q=v?-A[x]/2+I+$+W+O:j+$+W+O,F=e.elements.arrow&&te(e.elements.arrow),U=F?"y"===y?F.clientTop||0:F.clientLeft||0:0,V=e.modifiersData.offset?e.modifiersData.offset[e.placement][y]:0,K=E[y]+z-V-U,X=E[y]+q-V;if(o){var Y=oe(f?ne(S,K):S,D,f?ie(N,X):N);E[y]=Y,C[y]=Y-D}if(a){var Q="x"===y?mt:bt,G="x"===y?gt:_t,Z=E[w],J=Z+g[Q],tt=Z-g[G],et=oe(f?ne(J,K):J,Z,f?ie(tt,X):tt);E[w]=et,C[w]=et-Z}}e.modifiersData[n]=C}},requiresIfExists:["offset"]};function Me(t,e,i){void 0===i&&(i=!1);var n=zt(e);zt(e)&&function(t){var e=t.getBoundingClientRect();e.width,t.offsetWidth,e.height,t.offsetHeight}(e);var s,o,r=Gt(e),a=Vt(t),l={scrollLeft:0,scrollTop:0},c={x:0,y:0};return(n||!n&&!i)&&(("body"!==Rt(e)||we(r))&&(l=(s=e)!==Wt(s)&&zt(s)?{scrollLeft:(o=s).scrollLeft,scrollTop:o.scrollTop}:ve(s)),zt(e)?((c=Vt(e)).x+=e.clientLeft,c.y+=e.clientTop):r&&(c.x=ye(r))),{x:a.left+l.scrollLeft-c.x,y:a.top+l.scrollTop-c.y,width:a.width,height:a.height}}function He(t){var e=new Map,i=new Set,n=[];function s(t){i.add(t.name),[].concat(t.requires||[],t.requiresIfExists||[]).forEach((function(t){if(!i.has(t)){var n=e.get(t);n&&s(n)}})),n.push(t)}return t.forEach((function(t){e.set(t.name,t)})),t.forEach((function(t){i.has(t.name)||s(t)})),n}var Be={placement:"bottom",modifiers:[],strategy:"absolute"};function Re(){for(var t=arguments.length,e=new Array(t),i=0;i<t;i++)e[i]=arguments[i];return!e.some((function(t){return!(t&&"function"==typeof t.getBoundingClientRect)}))}function We(t){void 0===t&&(t={});var e=t,i=e.defaultModifiers,n=void 0===i?[]:i,s=e.defaultOptions,o=void 0===s?Be:s;return function(t,e,i){void 0===i&&(i=o);var s,r,a={placement:"bottom",orderedModifiers:[],options:Object.assign({},Be,o),modifiersData:{},elements:{reference:t,popper:e},attributes:{},styles:{}},l=[],c=!1,h={state:a,setOptions:function(i){var s="function"==typeof i?i(a.options):i;d(),a.options=Object.assign({},o,a.options,s),a.scrollParents={reference:$t(t)?Ae(t):t.contextElement?Ae(t.contextElement):[],popper:Ae(e)};var r,c,u=function(t){var e=He(t);return Bt.reduce((function(t,i){return t.concat(e.filter((function(t){return t.phase===i})))}),[])}((r=[].concat(n,a.options.modifiers),c=r.reduce((function(t,e){var i=t[e.name];return t[e.name]=i?Object.assign({},i,e,{options:Object.assign({},i.options,e.options),data:Object.assign({},i.data,e.data)}):e,t}),{}),Object.keys(c).map((function(t){return c[t]}))));return a.orderedModifiers=u.filter((function(t){return t.enabled})),a.orderedModifiers.forEach((function(t){var e=t.name,i=t.options,n=void 0===i?{}:i,s=t.effect;if("function"==typeof s){var o=s({state:a,name:e,instance:h,options:n});l.push(o||function(){})}})),h.update()},forceUpdate:function(){if(!c){var t=a.elements,e=t.reference,i=t.popper;if(Re(e,i)){a.rects={reference:Me(e,te(i),"fixed"===a.options.strategy),popper:Kt(i)},a.reset=!1,a.placement=a.options.placement,a.orderedModifiers.forEach((function(t){return a.modifiersData[t.name]=Object.assign({},t.data)}));for(var n=0;n<a.orderedModifiers.length;n++)if(!0!==a.reset){var s=a.orderedModifiers[n],o=s.fn,r=s.options,l=void 0===r?{}:r,d=s.name;"function"==typeof o&&(a=o({state:a,options:l,name:d,instance:h})||a)}else a.reset=!1,n=-1}}},update:(s=function(){return new Promise((function(t){h.forceUpdate(),t(a)}))},function(){return r||(r=new Promise((function(t){Promise.resolve().then((function(){r=void 0,t(s())}))}))),r}),destroy:function(){d(),c=!0}};if(!Re(t,e))return h;function d(){l.forEach((function(t){return t()})),l=[]}return h.setOptions(i).then((function(t){!c&&i.onFirstUpdate&&i.onFirstUpdate(t)})),h}}var $e=We(),ze=We({defaultModifiers:[pe,Pe,ue,Ft]}),qe=We({defaultModifiers:[pe,Pe,ue,Ft,Ie,xe,je,le,Ne]});const Fe=Object.freeze({__proto__:null,popperGenerator:We,detectOverflow:ke,createPopperBase:$e,createPopper:qe,createPopperLite:ze,top:mt,bottom:gt,right:_t,left:bt,auto:vt,basePlacements:yt,start:wt,end:Et,clippingParents:At,viewport:Tt,popper:Ot,reference:Ct,variationPlacements:kt,placements:Lt,beforeRead:xt,read:Dt,afterRead:St,beforeMain:Nt,main:It,afterMain:Pt,beforeWrite:jt,write:Mt,afterWrite:Ht,modifierPhases:Bt,applyStyles:Ft,arrow:le,computeStyles:ue,eventListeners:pe,flip:xe,hide:Ne,offset:Ie,popperOffsets:Pe,preventOverflow:je}),Ue="dropdown",Ve="Escape",Ke="Space",Xe="ArrowUp",Ye="ArrowDown",Qe=new RegExp("ArrowUp|ArrowDown|Escape"),Ge="click.bs.dropdown.data-api",Ze="keydown.bs.dropdown.data-api",Je="show",ti='[data-bs-toggle="dropdown"]',ei=".dropdown-menu",ii=m()?"top-end":"top-start",ni=m()?"top-start":"top-end",si=m()?"bottom-end":"bottom-start",oi=m()?"bottom-start":"bottom-end",ri=m()?"left-start":"right-start",ai=m()?"right-start":"left-start",li={offset:[0,2],boundary:"clippingParents",reference:"toggle",display:"dynamic",popperConfig:null,autoClose:!0},ci={offset:"(array|string|function)",boundary:"(string|element)",reference:"(string|element|object)",display:"string",popperConfig:"(null|object|function)",autoClose:"(boolean|string)"};class hi extends B{constructor(t,e){super(t),this._popper=null,this._config=this._getConfig(e),this._menu=this._getMenuElement(),this._inNavbar=this._detectNavbar()}static get Default(){return li}static get DefaultType(){return ci}static get NAME(){return Ue}toggle(){return this._isShown()?this.hide():this.show()}show(){if(c(this._element)||this._isShown(this._menu))return;const t={relatedTarget:this._element};if(j.trigger(this._element,"show.bs.dropdown",t).defaultPrevented)return;const e=hi.getParentFromElement(this._element);this._inNavbar?U.setDataAttribute(this._menu,"popper","none"):this._createPopper(e),"ontouchstart"in document.documentElement&&!e.closest(".navbar-nav")&&[].concat(...document.body.children).forEach((t=>j.on(t,"mouseover",d))),this._element.focus(),this._element.setAttribute("aria-expanded",!0),this._menu.classList.add(Je),this._element.classList.add(Je),j.trigger(this._element,"shown.bs.dropdown",t)}hide(){if(c(this._element)||!this._isShown(this._menu))return;const t={relatedTarget:this._element};this._completeHide(t)}dispose(){this._popper&&this._popper.destroy(),super.dispose()}update(){this._inNavbar=this._detectNavbar(),this._popper&&this._popper.update()}_completeHide(t){j.trigger(this._element,"hide.bs.dropdown",t).defaultPrevented||("ontouchstart"in document.documentElement&&[].concat(...document.body.children).forEach((t=>j.off(t,"mouseover",d))),this._popper&&this._popper.destroy(),this._menu.classList.remove(Je),this._element.classList.remove(Je),this._element.setAttribute("aria-expanded","false"),U.removeDataAttribute(this._menu,"popper"),j.trigger(this._element,"hidden.bs.dropdown",t))}_getConfig(t){if(t={...this.constructor.Default,...U.getDataAttributes(this._element),...t},a(Ue,t,this.constructor.DefaultType),"object"==typeof t.reference&&!o(t.reference)&&"function"!=typeof t.reference.getBoundingClientRect)throw new TypeError(`${Ue.toUpperCase()}: Option "reference" provided type "object" without a required "getBoundingClientRect" method.`);return t}_createPopper(t){if(void 0===Fe)throw new TypeError("Bootstrap's dropdowns require Popper (https://popper.js.org)");let e=this._element;"parent"===this._config.reference?e=t:o(this._config.reference)?e=r(this._config.reference):"object"==typeof this._config.reference&&(e=this._config.reference);const i=this._getPopperConfig(),n=i.modifiers.find((t=>"applyStyles"===t.name&&!1===t.enabled));this._popper=qe(e,this._menu,i),n&&U.setDataAttribute(this._menu,"popper","static")}_isShown(t=this._element){return t.classList.contains(Je)}_getMenuElement(){return V.next(this._element,ei)[0]}_getPlacement(){const t=this._element.parentNode;if(t.classList.contains("dropend"))return ri;if(t.classList.contains("dropstart"))return ai;const e="end"===getComputedStyle(this._menu).getPropertyValue("--bs-position").trim();return t.classList.contains("dropup")?e?ni:ii:e?oi:si}_detectNavbar(){return null!==this._element.closest(".navbar")}_getOffset(){const{offset:t}=this._config;return"string"==typeof t?t.split(",").map((t=>Number.parseInt(t,10))):"function"==typeof t?e=>t(e,this._element):t}_getPopperConfig(){const t={placement:this._getPlacement(),modifiers:[{name:"preventOverflow",options:{boundary:this._config.boundary}},{name:"offset",options:{offset:this._getOffset()}}]};return"static"===this._config.display&&(t.modifiers=[{name:"applyStyles",enabled:!1}]),{...t,..."function"==typeof this._config.popperConfig?this._config.popperConfig(t):this._config.popperConfig}}_selectMenuItem({key:t,target:e}){const i=V.find(".dropdown-menu .dropdown-item:not(.disabled):not(:disabled)",this._menu).filter(l);i.length&&v(i,e,t===Ye,!i.includes(e)).focus()}static jQueryInterface(t){return this.each((function(){const e=hi.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t])throw new TypeError(`No method named "${t}"`);e[t]()}}))}static clearMenus(t){if(t&&(2===t.button||"keyup"===t.type&&"Tab"!==t.key))return;const e=V.find(ti);for(let i=0,n=e.length;i<n;i++){const n=hi.getInstance(e[i]);if(!n||!1===n._config.autoClose)continue;if(!n._isShown())continue;const s={relatedTarget:n._element};if(t){const e=t.composedPath(),i=e.includes(n._menu);if(e.includes(n._element)||"inside"===n._config.autoClose&&!i||"outside"===n._config.autoClose&&i)continue;if(n._menu.contains(t.target)&&("keyup"===t.type&&"Tab"===t.key||/input|select|option|textarea|form/i.test(t.target.tagName)))continue;"click"===t.type&&(s.clickEvent=t)}n._completeHide(s)}}static getParentFromElement(t){return n(t)||t.parentNode}static dataApiKeydownHandler(t){if(/input|textarea/i.test(t.target.tagName)?t.key===Ke||t.key!==Ve&&(t.key!==Ye&&t.key!==Xe||t.target.closest(ei)):!Qe.test(t.key))return;const e=this.classList.contains(Je);if(!e&&t.key===Ve)return;if(t.preventDefault(),t.stopPropagation(),c(this))return;const i=this.matches(ti)?this:V.prev(this,ti)[0],n=hi.getOrCreateInstance(i);if(t.key!==Ve)return t.key===Xe||t.key===Ye?(e||n.show(),void n._selectMenuItem(t)):void(e&&t.key!==Ke||hi.clearMenus());n.hide()}}j.on(document,Ze,ti,hi.dataApiKeydownHandler),j.on(document,Ze,ei,hi.dataApiKeydownHandler),j.on(document,Ge,hi.clearMenus),j.on(document,"keyup.bs.dropdown.data-api",hi.clearMenus),j.on(document,Ge,ti,(function(t){t.preventDefault(),hi.getOrCreateInstance(this).toggle()})),g(hi);const di=".fixed-top, .fixed-bottom, .is-fixed, .sticky-top",ui=".sticky-top";class fi{constructor(){this._element=document.body}getWidth(){const t=document.documentElement.clientWidth;return Math.abs(window.innerWidth-t)}hide(){const t=this.getWidth();this._disableOverFlow(),this._setElementAttributes(this._element,"paddingRight",(e=>e+t)),this._setElementAttributes(di,"paddingRight",(e=>e+t)),this._setElementAttributes(ui,"marginRight",(e=>e-t))}_disableOverFlow(){this._saveInitialAttribute(this._element,"overflow"),this._element.style.overflow="hidden"}_setElementAttributes(t,e,i){const n=this.getWidth();this._applyManipulationCallback(t,(t=>{if(t!==this._element&&window.innerWidth>t.clientWidth+n)return;this._saveInitialAttribute(t,e);const s=window.getComputedStyle(t)[e];t.style[e]=`${i(Number.parseFloat(s))}px`}))}reset(){this._resetElementAttributes(this._element,"overflow"),this._resetElementAttributes(this._element,"paddingRight"),this._resetElementAttributes(di,"paddingRight"),this._resetElementAttributes(ui,"marginRight")}_saveInitialAttribute(t,e){const i=t.style[e];i&&U.setDataAttribute(t,e,i)}_resetElementAttributes(t,e){this._applyManipulationCallback(t,(t=>{const i=U.getDataAttribute(t,e);void 0===i?t.style.removeProperty(e):(U.removeDataAttribute(t,e),t.style[e]=i)}))}_applyManipulationCallback(t,e){o(t)?e(t):V.find(t,this._element).forEach(e)}isOverflowing(){return this.getWidth()>0}}const pi={className:"modal-backdrop",isVisible:!0,isAnimated:!1,rootElement:"body",clickCallback:null},mi={className:"string",isVisible:"boolean",isAnimated:"boolean",rootElement:"(element|string)",clickCallback:"(function|null)"},gi="show",_i="mousedown.bs.backdrop";class bi{constructor(t){this._config=this._getConfig(t),this._isAppended=!1,this._element=null}show(t){this._config.isVisible?(this._append(),this._config.isAnimated&&u(this._getElement()),this._getElement().classList.add(gi),this._emulateAnimation((()=>{_(t)}))):_(t)}hide(t){this._config.isVisible?(this._getElement().classList.remove(gi),this._emulateAnimation((()=>{this.dispose(),_(t)}))):_(t)}_getElement(){if(!this._element){const t=document.createElement("div");t.className=this._config.className,this._config.isAnimated&&t.classList.add("fade"),this._element=t}return this._element}_getConfig(t){return(t={...pi,..."object"==typeof t?t:{}}).rootElement=r(t.rootElement),a("backdrop",t,mi),t}_append(){this._isAppended||(this._config.rootElement.append(this._getElement()),j.on(this._getElement(),_i,(()=>{_(this._config.clickCallback)})),this._isAppended=!0)}dispose(){this._isAppended&&(j.off(this._element,_i),this._element.remove(),this._isAppended=!1)}_emulateAnimation(t){b(t,this._getElement(),this._config.isAnimated)}}const vi={trapElement:null,autofocus:!0},yi={trapElement:"element",autofocus:"boolean"},wi=".bs.focustrap",Ei="backward";class Ai{constructor(t){this._config=this._getConfig(t),this._isActive=!1,this._lastTabNavDirection=null}activate(){const{trapElement:t,autofocus:e}=this._config;this._isActive||(e&&t.focus(),j.off(document,wi),j.on(document,"focusin.bs.focustrap",(t=>this._handleFocusin(t))),j.on(document,"keydown.tab.bs.focustrap",(t=>this._handleKeydown(t))),this._isActive=!0)}deactivate(){this._isActive&&(this._isActive=!1,j.off(document,wi))}_handleFocusin(t){const{target:e}=t,{trapElement:i}=this._config;if(e===document||e===i||i.contains(e))return;const n=V.focusableChildren(i);0===n.length?i.focus():this._lastTabNavDirection===Ei?n[n.length-1].focus():n[0].focus()}_handleKeydown(t){"Tab"===t.key&&(this._lastTabNavDirection=t.shiftKey?Ei:"forward")}_getConfig(t){return t={...vi,..."object"==typeof t?t:{}},a("focustrap",t,yi),t}}const Ti="modal",Oi="Escape",Ci={backdrop:!0,keyboard:!0,focus:!0},ki={backdrop:"(boolean|string)",keyboard:"boolean",focus:"boolean"},Li="hidden.bs.modal",xi="show.bs.modal",Di="resize.bs.modal",Si="click.dismiss.bs.modal",Ni="keydown.dismiss.bs.modal",Ii="mousedown.dismiss.bs.modal",Pi="modal-open",ji="show",Mi="modal-static";class Hi extends B{constructor(t,e){super(t),this._config=this._getConfig(e),this._dialog=V.findOne(".modal-dialog",this._element),this._backdrop=this._initializeBackDrop(),this._focustrap=this._initializeFocusTrap(),this._isShown=!1,this._ignoreBackdropClick=!1,this._isTransitioning=!1,this._scrollBar=new fi}static get Default(){return Ci}static get NAME(){return Ti}toggle(t){return this._isShown?this.hide():this.show(t)}show(t){this._isShown||this._isTransitioning||j.trigger(this._element,xi,{relatedTarget:t}).defaultPrevented||(this._isShown=!0,this._isAnimated()&&(this._isTransitioning=!0),this._scrollBar.hide(),document.body.classList.add(Pi),this._adjustDialog(),this._setEscapeEvent(),this._setResizeEvent(),j.on(this._dialog,Ii,(()=>{j.one(this._element,"mouseup.dismiss.bs.modal",(t=>{t.target===this._element&&(this._ignoreBackdropClick=!0)}))})),this._showBackdrop((()=>this._showElement(t))))}hide(){if(!this._isShown||this._isTransitioning)return;if(j.trigger(this._element,"hide.bs.modal").defaultPrevented)return;this._isShown=!1;const t=this._isAnimated();t&&(this._isTransitioning=!0),this._setEscapeEvent(),this._setResizeEvent(),this._focustrap.deactivate(),this._element.classList.remove(ji),j.off(this._element,Si),j.off(this._dialog,Ii),this._queueCallback((()=>this._hideModal()),this._element,t)}dispose(){[window,this._dialog].forEach((t=>j.off(t,".bs.modal"))),this._backdrop.dispose(),this._focustrap.deactivate(),super.dispose()}handleUpdate(){this._adjustDialog()}_initializeBackDrop(){return new bi({isVisible:Boolean(this._config.backdrop),isAnimated:this._isAnimated()})}_initializeFocusTrap(){return new Ai({trapElement:this._element})}_getConfig(t){return t={...Ci,...U.getDataAttributes(this._element),..."object"==typeof t?t:{}},a(Ti,t,ki),t}_showElement(t){const e=this._isAnimated(),i=V.findOne(".modal-body",this._dialog);this._element.parentNode&&this._element.parentNode.nodeType===Node.ELEMENT_NODE||document.body.append(this._element),this._element.style.display="block",this._element.removeAttribute("aria-hidden"),this._element.setAttribute("aria-modal",!0),this._element.setAttribute("role","dialog"),this._element.scrollTop=0,i&&(i.scrollTop=0),e&&u(this._element),this._element.classList.add(ji),this._queueCallback((()=>{this._config.focus&&this._focustrap.activate(),this._isTransitioning=!1,j.trigger(this._element,"shown.bs.modal",{relatedTarget:t})}),this._dialog,e)}_setEscapeEvent(){this._isShown?j.on(this._element,Ni,(t=>{this._config.keyboard&&t.key===Oi?(t.preventDefault(),this.hide()):this._config.keyboard||t.key!==Oi||this._triggerBackdropTransition()})):j.off(this._element,Ni)}_setResizeEvent(){this._isShown?j.on(window,Di,(()=>this._adjustDialog())):j.off(window,Di)}_hideModal(){this._element.style.display="none",this._element.setAttribute("aria-hidden",!0),this._element.removeAttribute("aria-modal"),this._element.removeAttribute("role"),this._isTransitioning=!1,this._backdrop.hide((()=>{document.body.classList.remove(Pi),this._resetAdjustments(),this._scrollBar.reset(),j.trigger(this._element,Li)}))}_showBackdrop(t){j.on(this._element,Si,(t=>{this._ignoreBackdropClick?this._ignoreBackdropClick=!1:t.target===t.currentTarget&&(!0===this._config.backdrop?this.hide():"static"===this._config.backdrop&&this._triggerBackdropTransition())})),this._backdrop.show(t)}_isAnimated(){return this._element.classList.contains("fade")}_triggerBackdropTransition(){if(j.trigger(this._element,"hidePrevented.bs.modal").defaultPrevented)return;const{classList:t,scrollHeight:e,style:i}=this._element,n=e>document.documentElement.clientHeight;!n&&"hidden"===i.overflowY||t.contains(Mi)||(n||(i.overflowY="hidden"),t.add(Mi),this._queueCallback((()=>{t.remove(Mi),n||this._queueCallback((()=>{i.overflowY=""}),this._dialog)}),this._dialog),this._element.focus())}_adjustDialog(){const t=this._element.scrollHeight>document.documentElement.clientHeight,e=this._scrollBar.getWidth(),i=e>0;(!i&&t&&!m()||i&&!t&&m())&&(this._element.style.paddingLeft=`${e}px`),(i&&!t&&!m()||!i&&t&&m())&&(this._element.style.paddingRight=`${e}px`)}_resetAdjustments(){this._element.style.paddingLeft="",this._element.style.paddingRight=""}static jQueryInterface(t,e){return this.each((function(){const i=Hi.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===i[t])throw new TypeError(`No method named "${t}"`);i[t](e)}}))}}j.on(document,"click.bs.modal.data-api",'[data-bs-toggle="modal"]',(function(t){const e=n(this);["A","AREA"].includes(this.tagName)&&t.preventDefault(),j.one(e,xi,(t=>{t.defaultPrevented||j.one(e,Li,(()=>{l(this)&&this.focus()}))}));const i=V.findOne(".modal.show");i&&Hi.getInstance(i).hide(),Hi.getOrCreateInstance(e).toggle(this)})),R(Hi),g(Hi);const Bi="offcanvas",Ri={backdrop:!0,keyboard:!0,scroll:!1},Wi={backdrop:"boolean",keyboard:"boolean",scroll:"boolean"},$i="show",zi=".offcanvas.show",qi="hidden.bs.offcanvas";class Fi extends B{constructor(t,e){super(t),this._config=this._getConfig(e),this._isShown=!1,this._backdrop=this._initializeBackDrop(),this._focustrap=this._initializeFocusTrap(),this._addEventListeners()}static get NAME(){return Bi}static get Default(){return Ri}toggle(t){return this._isShown?this.hide():this.show(t)}show(t){this._isShown||j.trigger(this._element,"show.bs.offcanvas",{relatedTarget:t}).defaultPrevented||(this._isShown=!0,this._element.style.visibility="visible",this._backdrop.show(),this._config.scroll||(new fi).hide(),this._element.removeAttribute("aria-hidden"),this._element.setAttribute("aria-modal",!0),this._element.setAttribute("role","dialog"),this._element.classList.add($i),this._queueCallback((()=>{this._config.scroll||this._focustrap.activate(),j.trigger(this._element,"shown.bs.offcanvas",{relatedTarget:t})}),this._element,!0))}hide(){this._isShown&&(j.trigger(this._element,"hide.bs.offcanvas").defaultPrevented||(this._focustrap.deactivate(),this._element.blur(),this._isShown=!1,this._element.classList.remove($i),this._backdrop.hide(),this._queueCallback((()=>{this._element.setAttribute("aria-hidden",!0),this._element.removeAttribute("aria-modal"),this._element.removeAttribute("role"),this._element.style.visibility="hidden",this._config.scroll||(new fi).reset(),j.trigger(this._element,qi)}),this._element,!0)))}dispose(){this._backdrop.dispose(),this._focustrap.deactivate(),super.dispose()}_getConfig(t){return t={...Ri,...U.getDataAttributes(this._element),..."object"==typeof t?t:{}},a(Bi,t,Wi),t}_initializeBackDrop(){return new bi({className:"offcanvas-backdrop",isVisible:this._config.backdrop,isAnimated:!0,rootElement:this._element.parentNode,clickCallback:()=>this.hide()})}_initializeFocusTrap(){return new Ai({trapElement:this._element})}_addEventListeners(){j.on(this._element,"keydown.dismiss.bs.offcanvas",(t=>{this._config.keyboard&&"Escape"===t.key&&this.hide()}))}static jQueryInterface(t){return this.each((function(){const e=Fi.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t]||t.startsWith("_")||"constructor"===t)throw new TypeError(`No method named "${t}"`);e[t](this)}}))}}j.on(document,"click.bs.offcanvas.data-api",'[data-bs-toggle="offcanvas"]',(function(t){const e=n(this);if(["A","AREA"].includes(this.tagName)&&t.preventDefault(),c(this))return;j.one(e,qi,(()=>{l(this)&&this.focus()}));const i=V.findOne(zi);i&&i!==e&&Fi.getInstance(i).hide(),Fi.getOrCreateInstance(e).toggle(this)})),j.on(window,"load.bs.offcanvas.data-api",(()=>V.find(zi).forEach((t=>Fi.getOrCreateInstance(t).show())))),R(Fi),g(Fi);const Ui=new Set(["background","cite","href","itemtype","longdesc","poster","src","xlink:href"]),Vi=/^(?:(?:https?|mailto|ftp|tel|file|sms):|[^#&/:?]*(?:[#/?]|$))/i,Ki=/^data:(?:image\/(?:bmp|gif|jpeg|jpg|png|tiff|webp)|video\/(?:mpeg|mp4|ogg|webm)|audio\/(?:mp3|oga|ogg|opus));base64,[\d+/a-z]+=*$/i,Xi=(t,e)=>{const i=t.nodeName.toLowerCase();if(e.includes(i))return!Ui.has(i)||Boolean(Vi.test(t.nodeValue)||Ki.test(t.nodeValue));const n=e.filter((t=>t instanceof RegExp));for(let t=0,e=n.length;t<e;t++)if(n[t].test(i))return!0;return!1};function Yi(t,e,i){if(!t.length)return t;if(i&&"function"==typeof i)return i(t);const n=(new window.DOMParser).parseFromString(t,"text/html"),s=[].concat(...n.body.querySelectorAll("*"));for(let t=0,i=s.length;t<i;t++){const i=s[t],n=i.nodeName.toLowerCase();if(!Object.keys(e).includes(n)){i.remove();continue}const o=[].concat(...i.attributes),r=[].concat(e["*"]||[],e[n]||[]);o.forEach((t=>{Xi(t,r)||i.removeAttribute(t.nodeName)}))}return n.body.innerHTML}const Qi="tooltip",Gi=new Set(["sanitize","allowList","sanitizeFn"]),Zi={animation:"boolean",template:"string",title:"(string|element|function)",trigger:"string",delay:"(number|object)",html:"boolean",selector:"(string|boolean)",placement:"(string|function)",offset:"(array|string|function)",container:"(string|element|boolean)",fallbackPlacements:"array",boundary:"(string|element)",customClass:"(string|function)",sanitize:"boolean",sanitizeFn:"(null|function)",allowList:"object",popperConfig:"(null|object|function)"},Ji={AUTO:"auto",TOP:"top",RIGHT:m()?"left":"right",BOTTOM:"bottom",LEFT:m()?"right":"left"},tn={animation:!0,template:'<div class="tooltip" role="tooltip"><div class="tooltip-arrow"></div><div class="tooltip-inner"></div></div>',trigger:"hover focus",title:"",delay:0,html:!1,selector:!1,placement:"top",offset:[0,0],container:!1,fallbackPlacements:["top","right","bottom","left"],boundary:"clippingParents",customClass:"",sanitize:!0,sanitizeFn:null,allowList:{"*":["class","dir","id","lang","role",/^aria-[\w-]*$/i],a:["target","href","title","rel"],area:[],b:[],br:[],col:[],code:[],div:[],em:[],hr:[],h1:[],h2:[],h3:[],h4:[],h5:[],h6:[],i:[],img:["src","srcset","alt","title","width","height"],li:[],ol:[],p:[],pre:[],s:[],small:[],span:[],sub:[],sup:[],strong:[],u:[],ul:[]},popperConfig:null},en={HIDE:"hide.bs.tooltip",HIDDEN:"hidden.bs.tooltip",SHOW:"show.bs.tooltip",SHOWN:"shown.bs.tooltip",INSERTED:"inserted.bs.tooltip",CLICK:"click.bs.tooltip",FOCUSIN:"focusin.bs.tooltip",FOCUSOUT:"focusout.bs.tooltip",MOUSEENTER:"mouseenter.bs.tooltip",MOUSELEAVE:"mouseleave.bs.tooltip"},nn="fade",sn="show",on="show",rn="out",an=".tooltip-inner",ln=".modal",cn="hide.bs.modal",hn="hover",dn="focus";class un extends B{constructor(t,e){if(void 0===Fe)throw new TypeError("Bootstrap's tooltips require Popper (https://popper.js.org)");super(t),this._isEnabled=!0,this._timeout=0,this._hoverState="",this._activeTrigger={},this._popper=null,this._config=this._getConfig(e),this.tip=null,this._setListeners()}static get Default(){return tn}static get NAME(){return Qi}static get Event(){return en}static get DefaultType(){return Zi}enable(){this._isEnabled=!0}disable(){this._isEnabled=!1}toggleEnabled(){this._isEnabled=!this._isEnabled}toggle(t){if(this._isEnabled)if(t){const e=this._initializeOnDelegatedTarget(t);e._activeTrigger.click=!e._activeTrigger.click,e._isWithActiveTrigger()?e._enter(null,e):e._leave(null,e)}else{if(this.getTipElement().classList.contains(sn))return void this._leave(null,this);this._enter(null,this)}}dispose(){clearTimeout(this._timeout),j.off(this._element.closest(ln),cn,this._hideModalHandler),this.tip&&this.tip.remove(),this._disposePopper(),super.dispose()}show(){if("none"===this._element.style.display)throw new Error("Please use show on visible elements");if(!this.isWithContent()||!this._isEnabled)return;const t=j.trigger(this._element,this.constructor.Event.SHOW),e=h(this._element),i=null===e?this._element.ownerDocument.documentElement.contains(this._element):e.contains(this._element);if(t.defaultPrevented||!i)return;"tooltip"===this.constructor.NAME&&this.tip&&this.getTitle()!==this.tip.querySelector(an).innerHTML&&(this._disposePopper(),this.tip.remove(),this.tip=null);const n=this.getTipElement(),s=(t=>{do{t+=Math.floor(1e6*Math.random())}while(document.getElementById(t));return t})(this.constructor.NAME);n.setAttribute("id",s),this._element.setAttribute("aria-describedby",s),this._config.animation&&n.classList.add(nn);const o="function"==typeof this._config.placement?this._config.placement.call(this,n,this._element):this._config.placement,r=this._getAttachment(o);this._addAttachmentClass(r);const{container:a}=this._config;H.set(n,this.constructor.DATA_KEY,this),this._element.ownerDocument.documentElement.contains(this.tip)||(a.append(n),j.trigger(this._element,this.constructor.Event.INSERTED)),this._popper?this._popper.update():this._popper=qe(this._element,n,this._getPopperConfig(r)),n.classList.add(sn);const l=this._resolvePossibleFunction(this._config.customClass);l&&n.classList.add(...l.split(" ")),"ontouchstart"in document.documentElement&&[].concat(...document.body.children).forEach((t=>{j.on(t,"mouseover",d)}));const c=this.tip.classList.contains(nn);this._queueCallback((()=>{const t=this._hoverState;this._hoverState=null,j.trigger(this._element,this.constructor.Event.SHOWN),t===rn&&this._leave(null,this)}),this.tip,c)}hide(){if(!this._popper)return;const t=this.getTipElement();if(j.trigger(this._element,this.constructor.Event.HIDE).defaultPrevented)return;t.classList.remove(sn),"ontouchstart"in document.documentElement&&[].concat(...document.body.children).forEach((t=>j.off(t,"mouseover",d))),this._activeTrigger.click=!1,this._activeTrigger.focus=!1,this._activeTrigger.hover=!1;const e=this.tip.classList.contains(nn);this._queueCallback((()=>{this._isWithActiveTrigger()||(this._hoverState!==on&&t.remove(),this._cleanTipClass(),this._element.removeAttribute("aria-describedby"),j.trigger(this._element,this.constructor.Event.HIDDEN),this._disposePopper())}),this.tip,e),this._hoverState=""}update(){null!==this._popper&&this._popper.update()}isWithContent(){return Boolean(this.getTitle())}getTipElement(){if(this.tip)return this.tip;const t=document.createElement("div");t.innerHTML=this._config.template;const e=t.children[0];return this.setContent(e),e.classList.remove(nn,sn),this.tip=e,this.tip}setContent(t){this._sanitizeAndSetContent(t,this.getTitle(),an)}_sanitizeAndSetContent(t,e,i){const n=V.findOne(i,t);e||!n?this.setElementContent(n,e):n.remove()}setElementContent(t,e){if(null!==t)return o(e)?(e=r(e),void(this._config.html?e.parentNode!==t&&(t.innerHTML="",t.append(e)):t.textContent=e.textContent)):void(this._config.html?(this._config.sanitize&&(e=Yi(e,this._config.allowList,this._config.sanitizeFn)),t.innerHTML=e):t.textContent=e)}getTitle(){const t=this._element.getAttribute("data-bs-original-title")||this._config.title;return this._resolvePossibleFunction(t)}updateAttachment(t){return"right"===t?"end":"left"===t?"start":t}_initializeOnDelegatedTarget(t,e){return e||this.constructor.getOrCreateInstance(t.delegateTarget,this._getDelegateConfig())}_getOffset(){const{offset:t}=this._config;return"string"==typeof t?t.split(",").map((t=>Number.parseInt(t,10))):"function"==typeof t?e=>t(e,this._element):t}_resolvePossibleFunction(t){return"function"==typeof t?t.call(this._element):t}_getPopperConfig(t){const e={placement:t,modifiers:[{name:"flip",options:{fallbackPlacements:this._config.fallbackPlacements}},{name:"offset",options:{offset:this._getOffset()}},{name:"preventOverflow",options:{boundary:this._config.boundary}},{name:"arrow",options:{element:`.${this.constructor.NAME}-arrow`}},{name:"onChange",enabled:!0,phase:"afterWrite",fn:t=>this._handlePopperPlacementChange(t)}],onFirstUpdate:t=>{t.options.placement!==t.placement&&this._handlePopperPlacementChange(t)}};return{...e,..."function"==typeof this._config.popperConfig?this._config.popperConfig(e):this._config.popperConfig}}_addAttachmentClass(t){this.getTipElement().classList.add(`${this._getBasicClassPrefix()}-${this.updateAttachment(t)}`)}_getAttachment(t){return Ji[t.toUpperCase()]}_setListeners(){this._config.trigger.split(" ").forEach((t=>{if("click"===t)j.on(this._element,this.constructor.Event.CLICK,this._config.selector,(t=>this.toggle(t)));else if("manual"!==t){const e=t===hn?this.constructor.Event.MOUSEENTER:this.constructor.Event.FOCUSIN,i=t===hn?this.constructor.Event.MOUSELEAVE:this.constructor.Event.FOCUSOUT;j.on(this._element,e,this._config.selector,(t=>this._enter(t))),j.on(this._element,i,this._config.selector,(t=>this._leave(t)))}})),this._hideModalHandler=()=>{this._element&&this.hide()},j.on(this._element.closest(ln),cn,this._hideModalHandler),this._config.selector?this._config={...this._config,trigger:"manual",selector:""}:this._fixTitle()}_fixTitle(){const t=this._element.getAttribute("title"),e=typeof this._element.getAttribute("data-bs-original-title");(t||"string"!==e)&&(this._element.setAttribute("data-bs-original-title",t||""),!t||this._element.getAttribute("aria-label")||this._element.textContent||this._element.setAttribute("aria-label",t),this._element.setAttribute("title",""))}_enter(t,e){e=this._initializeOnDelegatedTarget(t,e),t&&(e._activeTrigger["focusin"===t.type?dn:hn]=!0),e.getTipElement().classList.contains(sn)||e._hoverState===on?e._hoverState=on:(clearTimeout(e._timeout),e._hoverState=on,e._config.delay&&e._config.delay.show?e._timeout=setTimeout((()=>{e._hoverState===on&&e.show()}),e._config.delay.show):e.show())}_leave(t,e){e=this._initializeOnDelegatedTarget(t,e),t&&(e._activeTrigger["focusout"===t.type?dn:hn]=e._element.contains(t.relatedTarget)),e._isWithActiveTrigger()||(clearTimeout(e._timeout),e._hoverState=rn,e._config.delay&&e._config.delay.hide?e._timeout=setTimeout((()=>{e._hoverState===rn&&e.hide()}),e._config.delay.hide):e.hide())}_isWithActiveTrigger(){for(const t in this._activeTrigger)if(this._activeTrigger[t])return!0;return!1}_getConfig(t){const e=U.getDataAttributes(this._element);return Object.keys(e).forEach((t=>{Gi.has(t)&&delete e[t]})),(t={...this.constructor.Default,...e,..."object"==typeof t&&t?t:{}}).container=!1===t.container?document.body:r(t.container),"number"==typeof t.delay&&(t.delay={show:t.delay,hide:t.delay}),"number"==typeof t.title&&(t.title=t.title.toString()),"number"==typeof t.content&&(t.content=t.content.toString()),a(Qi,t,this.constructor.DefaultType),t.sanitize&&(t.template=Yi(t.template,t.allowList,t.sanitizeFn)),t}_getDelegateConfig(){const t={};for(const e in this._config)this.constructor.Default[e]!==this._config[e]&&(t[e]=this._config[e]);return t}_cleanTipClass(){const t=this.getTipElement(),e=new RegExp(`(^|\\s)${this._getBasicClassPrefix()}\\S+`,"g"),i=t.getAttribute("class").match(e);null!==i&&i.length>0&&i.map((t=>t.trim())).forEach((e=>t.classList.remove(e)))}_getBasicClassPrefix(){return"bs-tooltip"}_handlePopperPlacementChange(t){const{state:e}=t;e&&(this.tip=e.elements.popper,this._cleanTipClass(),this._addAttachmentClass(this._getAttachment(e.placement)))}_disposePopper(){this._popper&&(this._popper.destroy(),this._popper=null)}static jQueryInterface(t){return this.each((function(){const e=un.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t])throw new TypeError(`No method named "${t}"`);e[t]()}}))}}g(un);const fn={...un.Default,placement:"right",offset:[0,8],trigger:"click",content:"",template:'<div class="popover" role="tooltip"><div class="popover-arrow"></div><h3 class="popover-header"></h3><div class="popover-body"></div></div>'},pn={...un.DefaultType,content:"(string|element|function)"},mn={HIDE:"hide.bs.popover",HIDDEN:"hidden.bs.popover",SHOW:"show.bs.popover",SHOWN:"shown.bs.popover",INSERTED:"inserted.bs.popover",CLICK:"click.bs.popover",FOCUSIN:"focusin.bs.popover",FOCUSOUT:"focusout.bs.popover",MOUSEENTER:"mouseenter.bs.popover",MOUSELEAVE:"mouseleave.bs.popover"};class gn extends un{static get Default(){return fn}static get NAME(){return"popover"}static get Event(){return mn}static get DefaultType(){return pn}isWithContent(){return this.getTitle()||this._getContent()}setContent(t){this._sanitizeAndSetContent(t,this.getTitle(),".popover-header"),this._sanitizeAndSetContent(t,this._getContent(),".popover-body")}_getContent(){return this._resolvePossibleFunction(this._config.content)}_getBasicClassPrefix(){return"bs-popover"}static jQueryInterface(t){return this.each((function(){const e=gn.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t])throw new TypeError(`No method named "${t}"`);e[t]()}}))}}g(gn);const _n="scrollspy",bn={offset:10,method:"auto",target:""},vn={offset:"number",method:"string",target:"(string|element)"},yn="active",wn=".nav-link, .list-group-item, .dropdown-item",En="position";class An extends B{constructor(t,e){super(t),this._scrollElement="BODY"===this._element.tagName?window:this._element,this._config=this._getConfig(e),this._offsets=[],this._targets=[],this._activeTarget=null,this._scrollHeight=0,j.on(this._scrollElement,"scroll.bs.scrollspy",(()=>this._process())),this.refresh(),this._process()}static get Default(){return bn}static get NAME(){return _n}refresh(){const t=this._scrollElement===this._scrollElement.window?"offset":En,e="auto"===this._config.method?t:this._config.method,n=e===En?this._getScrollTop():0;this._offsets=[],this._targets=[],this._scrollHeight=this._getScrollHeight(),V.find(wn,this._config.target).map((t=>{const s=i(t),o=s?V.findOne(s):null;if(o){const t=o.getBoundingClientRect();if(t.width||t.height)return[U[e](o).top+n,s]}return null})).filter((t=>t)).sort(((t,e)=>t[0]-e[0])).forEach((t=>{this._offsets.push(t[0]),this._targets.push(t[1])}))}dispose(){j.off(this._scrollElement,".bs.scrollspy"),super.dispose()}_getConfig(t){return(t={...bn,...U.getDataAttributes(this._element),..."object"==typeof t&&t?t:{}}).target=r(t.target)||document.documentElement,a(_n,t,vn),t}_getScrollTop(){return this._scrollElement===window?this._scrollElement.pageYOffset:this._scrollElement.scrollTop}_getScrollHeight(){return this._scrollElement.scrollHeight||Math.max(document.body.scrollHeight,document.documentElement.scrollHeight)}_getOffsetHeight(){return this._scrollElement===window?window.innerHeight:this._scrollElement.getBoundingClientRect().height}_process(){const t=this._getScrollTop()+this._config.offset,e=this._getScrollHeight(),i=this._config.offset+e-this._getOffsetHeight();if(this._scrollHeight!==e&&this.refresh(),t>=i){const t=this._targets[this._targets.length-1];this._activeTarget!==t&&this._activate(t)}else{if(this._activeTarget&&t<this._offsets[0]&&this._offsets[0]>0)return this._activeTarget=null,void this._clear();for(let e=this._offsets.length;e--;)this._activeTarget!==this._targets[e]&&t>=this._offsets[e]&&(void 0===this._offsets[e+1]||t<this._offsets[e+1])&&this._activate(this._targets[e])}}_activate(t){this._activeTarget=t,this._clear();const e=wn.split(",").map((e=>`${e}[data-bs-target="${t}"],${e}[href="${t}"]`)),i=V.findOne(e.join(","),this._config.target);i.classList.add(yn),i.classList.contains("dropdown-item")?V.findOne(".dropdown-toggle",i.closest(".dropdown")).classList.add(yn):V.parents(i,".nav, .list-group").forEach((t=>{V.prev(t,".nav-link, .list-group-item").forEach((t=>t.classList.add(yn))),V.prev(t,".nav-item").forEach((t=>{V.children(t,".nav-link").forEach((t=>t.classList.add(yn)))}))})),j.trigger(this._scrollElement,"activate.bs.scrollspy",{relatedTarget:t})}_clear(){V.find(wn,this._config.target).filter((t=>t.classList.contains(yn))).forEach((t=>t.classList.remove(yn)))}static jQueryInterface(t){return this.each((function(){const e=An.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t])throw new TypeError(`No method named "${t}"`);e[t]()}}))}}j.on(window,"load.bs.scrollspy.data-api",(()=>{V.find('[data-bs-spy="scroll"]').forEach((t=>new An(t)))})),g(An);const Tn="active",On="fade",Cn="show",kn=".active",Ln=":scope > li > .active";class xn extends B{static get NAME(){return"tab"}show(){if(this._element.parentNode&&this._element.parentNode.nodeType===Node.ELEMENT_NODE&&this._element.classList.contains(Tn))return;let t;const e=n(this._element),i=this._element.closest(".nav, .list-group");if(i){const 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t&&t?t:{}},a(Dn,t,this.constructor.DefaultType),t}_maybeScheduleHide(){this._config.autohide&&(this._hasMouseInteraction||this._hasKeyboardInteraction||(this._timeout=setTimeout((()=>{this.hide()}),this._config.delay)))}_onInteraction(t,e){switch(t.type){case"mouseover":case"mouseout":this._hasMouseInteraction=e;break;case"focusin":case"focusout":this._hasKeyboardInteraction=e}if(e)return void this._clearTimeout();const i=t.relatedTarget;this._element===i||this._element.contains(i)||this._maybeScheduleHide()}_setListeners(){j.on(this._element,"mouseover.bs.toast",(t=>this._onInteraction(t,!0))),j.on(this._element,"mouseout.bs.toast",(t=>this._onInteraction(t,!1))),j.on(this._element,"focusin.bs.toast",(t=>this._onInteraction(t,!0))),j.on(this._element,"focusout.bs.toast",(t=>this._onInteraction(t,!1)))}_clearTimeout(){clearTimeout(this._timeout),this._timeout=null}static jQueryInterface(t){return this.each((function(){const e=Mn.getOrCreateInstance(this,t);if("string"==typeof 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+//# sourceMappingURL=bootstrap.bundle.min.js.map
\ No newline at end of file
diff --git a/docs/resources/Pull_Sentinal2_l2_data_files/libs/clipboard/clipboard.min.js b/docs/resources/Pull_Sentinal2_l2_data_files/libs/clipboard/clipboard.min.js
new file mode 100644
index 0000000..41c6a0f
--- /dev/null
+++ b/docs/resources/Pull_Sentinal2_l2_data_files/libs/clipboard/clipboard.min.js
@@ -0,0 +1,7 @@
+/*!
+ * clipboard.js v2.0.10
+ * https://clipboardjs.com/
+ *
+ * Licensed MIT © Zeno Rocha
+ */
+!function(t,e){"object"==typeof exports&&"object"==typeof module?module.exports=e():"function"==typeof define&&define.amd?define([],e):"object"==typeof exports?exports.ClipboardJS=e():t.ClipboardJS=e()}(this,function(){return n={686:function(t,e,n){"use strict";n.d(e,{default:function(){return o}});var e=n(279),i=n.n(e),e=n(370),u=n.n(e),e=n(817),c=n.n(e);function a(t){try{return document.execCommand(t)}catch(t){return}}var f=function(t){t=c()(t);return a("cut"),t};var l=function(t){var e,n,o,r=1<arguments.length&&void 0!==arguments[1]?arguments[1]:{container:document.body},i="";return"string"==typeof t?(e=t,n="rtl"===document.documentElement.getAttribute("dir"),(o=document.createElement("textarea")).style.fontSize="12pt",o.style.border="0",o.style.padding="0",o.style.margin="0",o.style.position="absolute",o.style[n?"right":"left"]="-9999px",n=window.pageYOffset||document.documentElement.scrollTop,o.style.top="".concat(n,"px"),o.setAttribute("readonly",""),o.value=e,o=o,r.container.appendChild(o),i=c()(o),a("copy"),o.remove()):(i=c()(t),a("copy")),i};function r(t){return(r="function"==typeof Symbol&&"symbol"==typeof Symbol.iterator?function(t){return typeof t}:function(t){return t&&"function"==typeof Symbol&&t.constructor===Symbol&&t!==Symbol.prototype?"symbol":typeof t})(t)}var s=function(){var t=0<arguments.length&&void 0!==arguments[0]?arguments[0]:{},e=t.action,n=void 0===e?"copy":e,o=t.container,e=t.target,t=t.text;if("copy"!==n&&"cut"!==n)throw new Error('Invalid "action" value, use either "copy" or "cut"');if(void 0!==e){if(!e||"object"!==r(e)||1!==e.nodeType)throw new Error('Invalid "target" value, use a valid Element');if("copy"===n&&e.hasAttribute("disabled"))throw new Error('Invalid "target" attribute. 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diff --git a/docs/resources/Pull_Sentinal2_l2_data_files/libs/quarto-html/anchor.min.js b/docs/resources/Pull_Sentinal2_l2_data_files/libs/quarto-html/anchor.min.js
new file mode 100644
index 0000000..1c2b86f
--- /dev/null
+++ b/docs/resources/Pull_Sentinal2_l2_data_files/libs/quarto-html/anchor.min.js
@@ -0,0 +1,9 @@
+// @license magnet:?xt=urn:btih:d3d9a9a6595521f9666a5e94cc830dab83b65699&dn=expat.txt Expat
+//
+// AnchorJS - v4.3.1 - 2021-04-17
+// https://www.bryanbraun.com/anchorjs/
+// Copyright (c) 2021 Bryan Braun; Licensed MIT
+//
+// @license magnet:?xt=urn:btih:d3d9a9a6595521f9666a5e94cc830dab83b65699&dn=expat.txt Expat
+!function(A,e){"use strict";"function"==typeof define&&define.amd?define([],e):"object"==typeof module&&module.exports?module.exports=e():(A.AnchorJS=e(),A.anchors=new A.AnchorJS)}(this,function(){"use strict";return function(A){function d(A){A.icon=Object.prototype.hasOwnProperty.call(A,"icon")?A.icon:"",A.visible=Object.prototype.hasOwnProperty.call(A,"visible")?A.visible:"hover",A.placement=Object.prototype.hasOwnProperty.call(A,"placement")?A.placement:"right",A.ariaLabel=Object.prototype.hasOwnProperty.call(A,"ariaLabel")?A.ariaLabel:"Anchor",A.class=Object.prototype.hasOwnProperty.call(A,"class")?A.class:"",A.base=Object.prototype.hasOwnProperty.call(A,"base")?A.base:"",A.truncate=Object.prototype.hasOwnProperty.call(A,"truncate")?Math.floor(A.truncate):64,A.titleText=Object.prototype.hasOwnProperty.call(A,"titleText")?A.titleText:""}function w(A){var e;if("string"==typeof A||A instanceof String)e=[].slice.call(document.querySelectorAll(A));else{if(!(Array.isArray(A)||A 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+// @license-end
\ No newline at end of file
diff --git a/docs/resources/Pull_Sentinal2_l2_data_files/libs/quarto-html/popper.min.js b/docs/resources/Pull_Sentinal2_l2_data_files/libs/quarto-html/popper.min.js
new file mode 100644
index 0000000..2269d66
--- /dev/null
+++ b/docs/resources/Pull_Sentinal2_l2_data_files/libs/quarto-html/popper.min.js
@@ -0,0 +1,6 @@
+/**
+ * @popperjs/core v2.11.4 - MIT License
+ */
+
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+
diff --git a/docs/resources/Pull_Sentinal2_l2_data_files/libs/quarto-html/quarto-syntax-highlighting.css b/docs/resources/Pull_Sentinal2_l2_data_files/libs/quarto-html/quarto-syntax-highlighting.css
new file mode 100644
index 0000000..36cb328
--- /dev/null
+++ b/docs/resources/Pull_Sentinal2_l2_data_files/libs/quarto-html/quarto-syntax-highlighting.css
@@ -0,0 +1,171 @@
+/* quarto syntax highlight colors */
+:root {
+  --quarto-hl-ot-color: #003B4F;
+  --quarto-hl-at-color: #657422;
+  --quarto-hl-ss-color: #20794D;
+  --quarto-hl-an-color: #5E5E5E;
+  --quarto-hl-fu-color: #4758AB;
+  --quarto-hl-st-color: #20794D;
+  --quarto-hl-cf-color: #003B4F;
+  --quarto-hl-op-color: #5E5E5E;
+  --quarto-hl-er-color: #AD0000;
+  --quarto-hl-bn-color: #AD0000;
+  --quarto-hl-al-color: #AD0000;
+  --quarto-hl-va-color: #111111;
+  --quarto-hl-bu-color: inherit;
+  --quarto-hl-ex-color: inherit;
+  --quarto-hl-pp-color: #AD0000;
+  --quarto-hl-in-color: #5E5E5E;
+  --quarto-hl-vs-color: #20794D;
+  --quarto-hl-wa-color: #5E5E5E;
+  --quarto-hl-do-color: #5E5E5E;
+  --quarto-hl-im-color: #00769E;
+  --quarto-hl-ch-color: #20794D;
+  --quarto-hl-dt-color: #AD0000;
+  --quarto-hl-fl-color: #AD0000;
+  --quarto-hl-co-color: #5E5E5E;
+  --quarto-hl-cv-color: #5E5E5E;
+  --quarto-hl-cn-color: #8f5902;
+  --quarto-hl-sc-color: #5E5E5E;
+  --quarto-hl-dv-color: #AD0000;
+  --quarto-hl-kw-color: #003B4F;
+}
+
+/* other quarto variables */
+:root {
+  --quarto-font-monospace: SFMono-Regular, Menlo, Monaco, Consolas, "Liberation Mono", "Courier New", monospace;
+}
+
+pre > code.sourceCode > span {
+  color: #003B4F;
+}
+
+code span {
+  color: #003B4F;
+}
+
+code.sourceCode > span {
+  color: #003B4F;
+}
+
+div.sourceCode,
+div.sourceCode pre.sourceCode {
+  color: #003B4F;
+}
+
+code span.ot {
+  color: #003B4F;
+}
+
+code span.at {
+  color: #657422;
+}
+
+code span.ss {
+  color: #20794D;
+}
+
+code span.an {
+  color: #5E5E5E;
+}
+
+code span.fu {
+  color: #4758AB;
+}
+
+code span.st {
+  color: #20794D;
+}
+
+code span.cf {
+  color: #003B4F;
+}
+
+code span.op {
+  color: #5E5E5E;
+}
+
+code span.er {
+  color: #AD0000;
+}
+
+code span.bn {
+  color: #AD0000;
+}
+
+code span.al {
+  color: #AD0000;
+}
+
+code span.va {
+  color: #111111;
+}
+
+code span.pp {
+  color: #AD0000;
+}
+
+code span.in {
+  color: #5E5E5E;
+}
+
+code span.vs {
+  color: #20794D;
+}
+
+code span.wa {
+  color: #5E5E5E;
+  font-style: italic;
+}
+
+code span.do {
+  color: #5E5E5E;
+  font-style: italic;
+}
+
+code span.im {
+  color: #00769E;
+}
+
+code span.ch {
+  color: #20794D;
+}
+
+code span.dt {
+  color: #AD0000;
+}
+
+code span.fl {
+  color: #AD0000;
+}
+
+code span.co {
+  color: #5E5E5E;
+}
+
+code span.cv {
+  color: #5E5E5E;
+  font-style: italic;
+}
+
+code span.cn {
+  color: #8f5902;
+}
+
+code span.sc {
+  color: #5E5E5E;
+}
+
+code span.dv {
+  color: #AD0000;
+}
+
+code span.kw {
+  color: #003B4F;
+}
+
+.prevent-inlining {
+  content: "</";
+}
+
+/*# sourceMappingURL=debc5d5d77c3f9108843748ff7464032.css.map */
diff --git a/docs/resources/Pull_Sentinal2_l2_data_files/libs/quarto-html/quarto.js b/docs/resources/Pull_Sentinal2_l2_data_files/libs/quarto-html/quarto.js
new file mode 100644
index 0000000..c7e1c84
--- /dev/null
+++ b/docs/resources/Pull_Sentinal2_l2_data_files/libs/quarto-html/quarto.js
@@ -0,0 +1,667 @@
+const sectionChanged = new CustomEvent("quarto-sectionChanged", {
+  detail: {},
+  bubbles: true,
+  cancelable: false,
+  composed: false,
+});
+
+window.document.addEventListener("DOMContentLoaded", function (_event) {
+  const tocEl = window.document.querySelector('nav[role="doc-toc"]');
+  const sidebarEl = window.document.getElementById("quarto-sidebar");
+  const leftTocEl = window.document.getElementById("quarto-sidebar-toc-left");
+  const marginSidebarEl = window.document.getElementById(
+    "quarto-margin-sidebar"
+  );
+  // function to determine whether the element has a previous sibling that is active
+  const prevSiblingIsActiveLink = (el) => {
+    const sibling = el.previousElementSibling;
+    if (sibling && sibling.tagName === "A") {
+      return sibling.classList.contains("active");
+    } else {
+      return false;
+    }
+  };
+
+  // fire slideEnter for bootstrap tab activations (for htmlwidget resize behavior)
+  function fireSlideEnter(e) {
+    const event = window.document.createEvent("Event");
+    event.initEvent("slideenter", true, true);
+    window.document.dispatchEvent(event);
+  }
+  const tabs = window.document.querySelectorAll('a[data-bs-toggle="tab"]');
+  tabs.forEach((tab) => {
+    tab.addEventListener("shown.bs.tab", fireSlideEnter);
+  });
+
+  // Track scrolling and mark TOC links as active
+  // get table of contents and sidebar (bail if we don't have at least one)
+  const tocLinks = tocEl
+    ? [...tocEl.querySelectorAll("a[data-scroll-target]")]
+    : [];
+  const makeActive = (link) => tocLinks[link].classList.add("active");
+  const removeActive = (link) => tocLinks[link].classList.remove("active");
+  const removeAllActive = () =>
+    [...Array(tocLinks.length).keys()].forEach((link) => removeActive(link));
+
+  // activate the anchor for a section associated with this TOC entry
+  tocLinks.forEach((link) => {
+    link.addEventListener("click", () => {
+      if (link.href.indexOf("#") !== -1) {
+        const anchor = link.href.split("#")[1];
+        const heading = window.document.querySelector(
+          `[data-anchor-id=${anchor}]`
+        );
+        if (heading) {
+          // Add the class
+          heading.classList.add("reveal-anchorjs-link");
+
+          // function to show the anchor
+          const handleMouseout = () => {
+            heading.classList.remove("reveal-anchorjs-link");
+            heading.removeEventListener("mouseout", handleMouseout);
+          };
+
+          // add a function to clear the anchor when the user mouses out of it
+          heading.addEventListener("mouseout", handleMouseout);
+        }
+      }
+    });
+  });
+
+  const sections = tocLinks.map((link) => {
+    const target = link.getAttribute("data-scroll-target");
+    if (target.startsWith("#")) {
+      return window.document.getElementById(decodeURI(`${target.slice(1)}`));
+    } else {
+      return window.document.querySelector(decodeURI(`${target}`));
+    }
+  });
+
+  const sectionMargin = 200;
+  let currentActive = 0;
+  // track whether we've initialized state the first time
+  let init = false;
+
+  const updateActiveLink = () => {
+    // The index from bottom to top (e.g. reversed list)
+    let sectionIndex = -1;
+    if (
+      window.innerHeight + window.pageYOffset >=
+      window.document.body.offsetHeight
+    ) {
+      sectionIndex = 0;
+    } else {
+      sectionIndex = [...sections].reverse().findIndex((section) => {
+        if (section) {
+          return window.pageYOffset >= section.offsetTop - sectionMargin;
+        } else {
+          return false;
+        }
+      });
+    }
+    if (sectionIndex > -1) {
+      const current = sections.length - sectionIndex - 1;
+      if (current !== currentActive) {
+        removeAllActive();
+        currentActive = current;
+        makeActive(current);
+        if (init) {
+          window.dispatchEvent(sectionChanged);
+        }
+        init = true;
+      }
+    }
+  };
+
+  const inHiddenRegion = (top, bottom, hiddenRegions) => {
+    for (const region of hiddenRegions) {
+      if (top <= region.bottom && bottom >= region.top) {
+        return true;
+      }
+    }
+    return false;
+  };
+
+  const categorySelector = "header.quarto-title-block .quarto-category";
+  const activateCategories = (href) => {
+    // Find any categories
+    // Surround them with a link pointing back to:
+    // #category=Authoring
+    try {
+      const categoryEls = window.document.querySelectorAll(categorySelector);
+      for (const categoryEl of categoryEls) {
+        const categoryText = categoryEl.textContent;
+        if (categoryText) {
+          const link = `${href}#category=${encodeURIComponent(categoryText)}`;
+          const linkEl = window.document.createElement("a");
+          linkEl.setAttribute("href", link);
+          for (const child of categoryEl.childNodes) {
+            linkEl.append(child);
+          }
+          categoryEl.appendChild(linkEl);
+        }
+      }
+    } catch {
+      // Ignore errors
+    }
+  };
+  function hasTitleCategories() {
+    return window.document.querySelector(categorySelector) !== null;
+  }
+
+  function offsetRelativeUrl(url) {
+    const offset = getMeta("quarto:offset");
+    return offset ? offset + url : url;
+  }
+
+  function offsetAbsoluteUrl(url) {
+    const offset = getMeta("quarto:offset");
+    const baseUrl = new URL(offset, window.location);
+
+    const projRelativeUrl = url.replace(baseUrl, "");
+    if (projRelativeUrl.startsWith("/")) {
+      return projRelativeUrl;
+    } else {
+      return "/" + projRelativeUrl;
+    }
+  }
+
+  // read a meta tag value
+  function getMeta(metaName) {
+    const metas = window.document.getElementsByTagName("meta");
+    for (let i = 0; i < metas.length; i++) {
+      if (metas[i].getAttribute("name") === metaName) {
+        return metas[i].getAttribute("content");
+      }
+    }
+    return "";
+  }
+
+  async function findAndActivateCategories() {
+    const currentPagePath = offsetAbsoluteUrl(window.location.href);
+    const response = await fetch(offsetRelativeUrl("listings.json"));
+    if (response.status == 200) {
+      return response.json().then(function (listingPaths) {
+        const listingHrefs = [];
+        for (const listingPath of listingPaths) {
+          const pathWithoutLeadingSlash = listingPath.listing.substring(1);
+          for (const item of listingPath.items) {
+            if (
+              item === currentPagePath ||
+              item === currentPagePath + "index.html"
+            ) {
+              // Resolve this path against the offset to be sure
+              // we already are using the correct path to the listing
+              // (this adjusts the listing urls to be rooted against
+              // whatever root the page is actually running against)
+              const relative = offsetRelativeUrl(pathWithoutLeadingSlash);
+              const baseUrl = window.location;
+              const resolvedPath = new URL(relative, baseUrl);
+              listingHrefs.push(resolvedPath.pathname);
+              break;
+            }
+          }
+        }
+
+        // Look up the tree for a nearby linting and use that if we find one
+        const nearestListing = findNearestParentListing(
+          offsetAbsoluteUrl(window.location.pathname),
+          listingHrefs
+        );
+        if (nearestListing) {
+          activateCategories(nearestListing);
+        } else {
+          // See if the referrer is a listing page for this item
+          const referredRelativePath = offsetAbsoluteUrl(document.referrer);
+          const referrerListing = listingHrefs.find((listingHref) => {
+            const isListingReferrer =
+              listingHref === referredRelativePath ||
+              listingHref === referredRelativePath + "index.html";
+            return isListingReferrer;
+          });
+
+          if (referrerListing) {
+            // Try to use the referrer if possible
+            activateCategories(referrerListing);
+          } else if (listingHrefs.length > 0) {
+            // Otherwise, just fall back to the first listing
+            activateCategories(listingHrefs[0]);
+          }
+        }
+      });
+    }
+  }
+  if (hasTitleCategories()) {
+    findAndActivateCategories();
+  }
+
+  const findNearestParentListing = (href, listingHrefs) => {
+    if (!href || !listingHrefs) {
+      return undefined;
+    }
+    // Look up the tree for a nearby linting and use that if we find one
+    const relativeParts = href.substring(1).split("/");
+    while (relativeParts.length > 0) {
+      const path = relativeParts.join("/");
+      for (const listingHref of listingHrefs) {
+        if (listingHref.startsWith(path)) {
+          return listingHref;
+        }
+      }
+      relativeParts.pop();
+    }
+
+    return undefined;
+  };
+
+  const manageSidebarVisiblity = (el, placeholderDescriptor) => {
+    let isVisible = true;
+
+    return (hiddenRegions) => {
+      if (el === null) {
+        return;
+      }
+
+      // Find the last element of the TOC
+      const lastChildEl = el.lastElementChild;
+
+      if (lastChildEl) {
+        // Find the top and bottom o the element that is being managed
+        const elTop = el.offsetTop;
+        const elBottom =
+          elTop + lastChildEl.offsetTop + lastChildEl.offsetHeight;
+
+        // Converts the sidebar to a menu
+        const convertToMenu = () => {
+          for (const child of el.children) {
+            child.style.opacity = 0;
+            child.style.display = "none";
+          }
+
+          const toggleContainer = window.document.createElement("div");
+          toggleContainer.style.width = "100%";
+          toggleContainer.classList.add("zindex-over-content");
+          toggleContainer.classList.add("quarto-sidebar-toggle");
+          toggleContainer.classList.add("headroom-target"); // Marks this to be managed by headeroom
+          toggleContainer.id = placeholderDescriptor.id;
+          toggleContainer.style.position = "fixed";
+
+          const toggleIcon = window.document.createElement("i");
+          toggleIcon.classList.add("quarto-sidebar-toggle-icon");
+          toggleIcon.classList.add("bi");
+          toggleIcon.classList.add("bi-caret-down-fill");
+
+          const toggleTitle = window.document.createElement("div");
+          const titleEl = window.document.body.querySelector(
+            placeholderDescriptor.titleSelector
+          );
+          if (titleEl) {
+            toggleTitle.append(titleEl.innerText, toggleIcon);
+          }
+          toggleTitle.classList.add("zindex-over-content");
+          toggleTitle.classList.add("quarto-sidebar-toggle-title");
+          toggleContainer.append(toggleTitle);
+
+          const toggleContents = window.document.createElement("div");
+          toggleContents.classList = el.classList;
+          toggleContents.classList.add("zindex-over-content");
+          toggleContents.classList.add("quarto-sidebar-toggle-contents");
+          for (const child of el.children) {
+            if (child.id === "toc-title") {
+              continue;
+            }
+
+            const clone = child.cloneNode(true);
+            clone.style.opacity = 1;
+            clone.style.display = null;
+            toggleContents.append(clone);
+          }
+          toggleContents.style.height = "0px";
+          toggleContainer.append(toggleContents);
+          el.parentElement.prepend(toggleContainer);
+
+          // Process clicks
+          let tocShowing = false;
+          // Allow the caller to control whether this is dismissed
+          // when it is clicked (e.g. sidebar navigation supports
+          // opening and closing the nav tree, so don't dismiss on click)
+          const clickEl = placeholderDescriptor.dismissOnClick
+            ? toggleContainer
+            : toggleTitle;
+
+          const closeToggle = () => {
+            if (tocShowing) {
+              toggleContainer.classList.remove("expanded");
+              toggleContents.style.height = "0px";
+              tocShowing = false;
+            }
+          };
+
+          const positionToggle = () => {
+            // position the element (top left of parent, same width as parent)
+            const elRect = el.getBoundingClientRect();
+            toggleContainer.style.left = `${elRect.left}px`;
+            toggleContainer.style.top = `${elRect.top}px`;
+            toggleContainer.style.width = `${elRect.width}px`;
+          };
+
+          // Get rid of any expanded toggle if the user scrolls
+          window.document.addEventListener(
+            "scroll",
+            throttle(() => {
+              closeToggle();
+            }, 50)
+          );
+
+          // Handle positioning of the toggle
+          window.addEventListener(
+            "resize",
+            throttle(() => {
+              positionToggle();
+            }, 50)
+          );
+          positionToggle();
+
+          // Process the click
+          clickEl.onclick = () => {
+            if (!tocShowing) {
+              toggleContainer.classList.add("expanded");
+              toggleContents.style.height = null;
+              tocShowing = true;
+            } else {
+              closeToggle();
+            }
+          };
+        };
+
+        // Converts a sidebar from a menu back to a sidebar
+        const convertToSidebar = () => {
+          for (const child of el.children) {
+            child.style.opacity = 1;
+            clone.style.display = null;
+          }
+
+          const placeholderEl = window.document.getElementById(
+            placeholderDescriptor.id
+          );
+          if (placeholderEl) {
+            placeholderEl.remove();
+          }
+
+          el.classList.remove("rollup");
+        };
+
+        if (isReaderMode()) {
+          convertToMenu();
+          isVisible = false;
+        } else {
+          if (!isVisible) {
+            // If the element is current not visible reveal if there are
+            // no conflicts with overlay regions
+            if (!inHiddenRegion(elTop, elBottom, hiddenRegions)) {
+              convertToSidebar();
+              isVisible = true;
+            }
+          } else {
+            // If the element is visible, hide it if it conflicts with overlay regions
+            // and insert a placeholder toggle (or if we're in reader mode)
+            if (inHiddenRegion(elTop, elBottom, hiddenRegions)) {
+              convertToMenu();
+              isVisible = false;
+            }
+          }
+        }
+      }
+    };
+  };
+
+  // Find any conflicting margin elements and add margins to the
+  // top to prevent overlap
+  const marginChildren = window.document.querySelectorAll(
+    ".column-margin.column-container > * "
+  );
+  let lastBottom = 0;
+  for (const marginChild of marginChildren) {
+    const top = marginChild.getBoundingClientRect().top;
+    if (top < lastBottom) {
+      const margin = lastBottom - top;
+      marginChild.style.marginTop = `${margin}px`;
+    }
+    const styles = window.getComputedStyle(marginChild);
+    const marginTop = parseFloat(styles["marginTop"]);
+
+    lastBottom = top + marginChild.getBoundingClientRect().height + marginTop;
+  }
+
+  // Manage the visibility of the toc and the sidebar
+  const marginScrollVisibility = manageSidebarVisiblity(marginSidebarEl, {
+    id: "quarto-toc-toggle",
+    titleSelector: "#toc-title",
+    dismissOnClick: true,
+  });
+  const sidebarScrollVisiblity = manageSidebarVisiblity(sidebarEl, {
+    id: "quarto-sidebarnav-toggle",
+    titleSelector: ".title",
+    dismissOnClick: false,
+  });
+  let tocLeftScrollVisibility;
+  if (leftTocEl) {
+    tocLeftScrollVisibility = manageSidebarVisiblity(leftTocEl, {
+      id: "quarto-lefttoc-toggle",
+      titleSelector: "#toc-title",
+      dismissOnClick: true,
+    });
+  }
+
+  // Find the first element that uses formatting in special columns
+  const conflictingEls = window.document.body.querySelectorAll(
+    '[class^="column-"], [class*=" column-"], aside, [class*="margin-caption"], [class*=" margin-caption"], [class*="margin-ref"], [class*=" margin-ref"]'
+  );
+
+  // Filter all the possibly conflicting elements into ones
+  // the do conflict on the left or ride side
+  const arrConflictingEls = Array.from(conflictingEls);
+  const leftSideConflictEls = arrConflictingEls.filter((el) => {
+    if (el.tagName === "ASIDE") {
+      return false;
+    }
+    return Array.from(el.classList).find((className) => {
+      return (
+        className !== "column-body" &&
+        className.startsWith("column-") &&
+        !className.endsWith("right") &&
+        !className.endsWith("container") &&
+        className !== "column-margin"
+      );
+    });
+  });
+  const rightSideConflictEls = arrConflictingEls.filter((el) => {
+    if (el.tagName === "ASIDE") {
+      return true;
+    }
+
+    const hasMarginCaption = Array.from(el.classList).find((className) => {
+      return className == "margin-caption";
+    });
+    if (hasMarginCaption) {
+      return true;
+    }
+
+    return Array.from(el.classList).find((className) => {
+      return (
+        className !== "column-body" &&
+        !className.endsWith("container") &&
+        className.startsWith("column-") &&
+        !className.endsWith("left")
+      );
+    });
+  });
+
+  const kOverlapPaddingSize = 10;
+  function toRegions(els) {
+    return els.map((el) => {
+      const top =
+        el.getBoundingClientRect().top +
+        document.documentElement.scrollTop -
+        kOverlapPaddingSize;
+      return {
+        top,
+        bottom: top + el.scrollHeight + 2 * kOverlapPaddingSize,
+      };
+    });
+  }
+
+  const hideOverlappedSidebars = () => {
+    marginScrollVisibility(toRegions(rightSideConflictEls));
+    sidebarScrollVisiblity(toRegions(leftSideConflictEls));
+    if (tocLeftScrollVisibility) {
+      tocLeftScrollVisibility(toRegions(leftSideConflictEls));
+    }
+  };
+
+  window.quartoToggleReader = () => {
+    // Applies a slow class (or removes it)
+    // to update the transition speed
+    const slowTransition = (slow) => {
+      const manageTransition = (id, slow) => {
+        const el = document.getElementById(id);
+        if (el) {
+          if (slow) {
+            el.classList.add("slow");
+          } else {
+            el.classList.remove("slow");
+          }
+        }
+      };
+
+      manageTransition("TOC", slow);
+      manageTransition("quarto-sidebar", slow);
+    };
+
+    const readerMode = !isReaderMode();
+    setReaderModeValue(readerMode);
+
+    // If we're entering reader mode, slow the transition
+    if (readerMode) {
+      slowTransition(readerMode);
+    }
+    highlightReaderToggle(readerMode);
+    hideOverlappedSidebars();
+
+    // If we're exiting reader mode, restore the non-slow transition
+    if (!readerMode) {
+      slowTransition(!readerMode);
+    }
+  };
+
+  const highlightReaderToggle = (readerMode) => {
+    const els = document.querySelectorAll(".quarto-reader-toggle");
+    if (els) {
+      els.forEach((el) => {
+        if (readerMode) {
+          el.classList.add("reader");
+        } else {
+          el.classList.remove("reader");
+        }
+      });
+    }
+  };
+
+  const setReaderModeValue = (val) => {
+    if (window.location.protocol !== "file:") {
+      window.localStorage.setItem("quarto-reader-mode", val);
+    } else {
+      localReaderMode = val;
+    }
+  };
+
+  const isReaderMode = () => {
+    if (window.location.protocol !== "file:") {
+      return window.localStorage.getItem("quarto-reader-mode") === "true";
+    } else {
+      return localReaderMode;
+    }
+  };
+  let localReaderMode = null;
+
+  // Walk the TOC and collapse/expand nodes
+  // Nodes are expanded if:
+  // - they are top level
+  // - they have children that are 'active' links
+  // - they are directly below an link that is 'active'
+  const walk = (el, depth) => {
+    // Tick depth when we enter a UL
+    if (el.tagName === "UL") {
+      depth = depth + 1;
+    }
+
+    // It this is active link
+    let isActiveNode = false;
+    if (el.tagName === "A" && el.classList.contains("active")) {
+      isActiveNode = true;
+    }
+
+    // See if there is an active child to this element
+    let hasActiveChild = false;
+    for (child of el.children) {
+      hasActiveChild = walk(child, depth) || hasActiveChild;
+    }
+
+    // Process the collapse state if this is an UL
+    if (el.tagName === "UL") {
+      if (depth === 1 || hasActiveChild || prevSiblingIsActiveLink(el)) {
+        el.classList.remove("collapse");
+      } else {
+        el.classList.add("collapse");
+      }
+
+      // untick depth when we leave a UL
+      depth = depth - 1;
+    }
+    return hasActiveChild || isActiveNode;
+  };
+
+  // walk the TOC and expand / collapse any items that should be shown
+
+  if (tocEl) {
+    walk(tocEl, 0);
+    updateActiveLink();
+  }
+
+  // Throttle the scroll event and walk peridiocally
+  window.document.addEventListener(
+    "scroll",
+    throttle(() => {
+      if (tocEl) {
+        updateActiveLink();
+        walk(tocEl, 0);
+      }
+      if (!isReaderMode()) {
+        hideOverlappedSidebars();
+      }
+    }, 5)
+  );
+  window.addEventListener(
+    "resize",
+    throttle(() => {
+      if (!isReaderMode()) {
+        hideOverlappedSidebars();
+      }
+    }, 10)
+  );
+  hideOverlappedSidebars();
+  highlightReaderToggle(isReaderMode());
+});
+
+function throttle(func, wait) {
+  let waiting = false;
+  return function () {
+    if (!waiting) {
+      func.apply(this, arguments);
+      waiting = true;
+      setTimeout(function () {
+        waiting = false;
+      }, wait);
+    }
+  };
+}
diff --git a/docs/resources/Pull_Sentinal2_l2_data_files/libs/quarto-html/tippy.css b/docs/resources/Pull_Sentinal2_l2_data_files/libs/quarto-html/tippy.css
new file mode 100644
index 0000000..e6ae635
--- /dev/null
+++ b/docs/resources/Pull_Sentinal2_l2_data_files/libs/quarto-html/tippy.css
@@ -0,0 +1 @@
+.tippy-box[data-animation=fade][data-state=hidden]{opacity:0}[data-tippy-root]{max-width:calc(100vw - 10px)}.tippy-box{position:relative;background-color:#333;color:#fff;border-radius:4px;font-size:14px;line-height:1.4;white-space:normal;outline:0;transition-property:transform,visibility,opacity}.tippy-box[data-placement^=top]>.tippy-arrow{bottom:0}.tippy-box[data-placement^=top]>.tippy-arrow:before{bottom:-7px;left:0;border-width:8px 8px 0;border-top-color:initial;transform-origin:center top}.tippy-box[data-placement^=bottom]>.tippy-arrow{top:0}.tippy-box[data-placement^=bottom]>.tippy-arrow:before{top:-7px;left:0;border-width:0 8px 8px;border-bottom-color:initial;transform-origin:center bottom}.tippy-box[data-placement^=left]>.tippy-arrow{right:0}.tippy-box[data-placement^=left]>.tippy-arrow:before{border-width:8px 0 8px 8px;border-left-color:initial;right:-7px;transform-origin:center left}.tippy-box[data-placement^=right]>.tippy-arrow{left:0}.tippy-box[data-placement^=right]>.tippy-arrow:before{left:-7px;border-width:8px 8px 8px 0;border-right-color:initial;transform-origin:center right}.tippy-box[data-inertia][data-state=visible]{transition-timing-function:cubic-bezier(.54,1.5,.38,1.11)}.tippy-arrow{width:16px;height:16px;color:#333}.tippy-arrow:before{content:"";position:absolute;border-color:transparent;border-style:solid}.tippy-content{position:relative;padding:5px 9px;z-index:1}
\ No newline at end of file
diff --git a/docs/resources/Pull_Sentinal2_l2_data_files/libs/quarto-html/tippy.umd.min.js b/docs/resources/Pull_Sentinal2_l2_data_files/libs/quarto-html/tippy.umd.min.js
new file mode 100644
index 0000000..ca292be
--- /dev/null
+++ b/docs/resources/Pull_Sentinal2_l2_data_files/libs/quarto-html/tippy.umd.min.js
@@ -0,0 +1,2 @@
+!function(e,t){"object"==typeof exports&&"undefined"!=typeof module?module.exports=t(require("@popperjs/core")):"function"==typeof define&&define.amd?define(["@popperjs/core"],t):(e=e||self).tippy=t(e.Popper)}(this,(function(e){"use strict";var t={passive:!0,capture:!0},n=function(){return document.body};function r(e,t,n){if(Array.isArray(e)){var r=e[t];return null==r?Array.isArray(n)?n[t]:n:r}return e}function o(e,t){var n={}.toString.call(e);return 0===n.indexOf("[object")&&n.indexOf(t+"]")>-1}function i(e,t){return"function"==typeof e?e.apply(void 0,t):e}function a(e,t){return 0===t?e:function(r){clearTimeout(n),n=setTimeout((function(){e(r)}),t)};var n}function s(e,t){var n=Object.assign({},e);return t.forEach((function(e){delete n[e]})),n}function u(e){return[].concat(e)}function c(e,t){-1===e.indexOf(t)&&e.push(t)}function p(e){return e.split("-")[0]}function f(e){return[].slice.call(e)}function l(e){return Object.keys(e).reduce((function(t,n){return void 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diff --git a/docs/resources/bilingualism_md.md b/docs/resources/bilingualism_md.md
new file mode 100644
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+# R and Python bilingualism
+
+Welcome to the R and Python bilingualism reference guide! If you’re
+fluent in one of these languages but hesitant to learn the other, you’re
+in the right place. The good news is that there are many similarities
+between R and Python that make it easy to switch between the two.
+
+Both R and Python are widely used in data science and are open-source,
+meaning that they are free to use and constantly being improved by the
+community. They both have extensive libraries for data analysis,
+visualization, and machine learning. In fact, many of the libraries in
+both languages have similar names and functions, such as Pandas in
+Python and data.table in R.
+
+While there are differences between the two languages, they can
+complement each other well. Python is versatile and scalable, making it
+ideal for large and complex projects such as web development and
+artificial intelligence. R, on the other hand, is known for its
+exceptional statistical capabilities and is often used in data analysis
+and modeling. Visualization is also easier in R, making it a popular
+choice for creating graphs and charts.
+
+By learning both R and Python, you’ll be able to take advantage of the
+strengths of each language and create more efficient and robust data
+analysis workflows. Don’t let the differences between the two languages
+intimidate you - once you become familiar with one, learning the other
+will be much easier.
+
+So, whether you’re a Python enthusiast looking to expand your
+statistical analysis capabilities, or an R user interested in exploring
+the world of web development and artificial intelligence, this guide
+will help you become bilingual in R and Python.
+
+## Install packages
+
+In R, packages can be installed from CRAN repository by using the
+install.packages() function:
+
+R code:
+
+``` r
+# Install the dplyr package from CRAN
+install.packages("dplyr")
+```
+
+In Python, packages can be installed from the Anaconda repository by
+using the conda install command:
+
+Python code:
+
+``` python
+# Install the pandas package from Anaconda
+!conda install pandas
+```
+
+Loading libraries in R and Python
+
+In R, libraries can be loaded in the same way as before, using the
+library() function:
+
+R code:
+
+``` r
+# Load the dplyr library
+library(dplyr)
+```
+
+In Python, libraries can be loaded in the same way as before, using the
+import statement. Here’s an example:
+
+Python code:
+
+``` python
+# Load the pandas library
+import pandas as pd
+```
+
+Note that the package or library must be installed from the respective
+repository before it can be loaded. Also, make sure you have the correct
+repository specified in your system before installing packages. By
+default, R uses CRAN as its primary repository, whereas Anaconda uses
+its own repository by default.
+
+## reticulate
+
+The reticulate package lets you run both R and Python together in the R
+environment.
+
+R libraries are stored and managed in a repository called CRAN. You can
+download R packages with the install.packages() function
+
+``` r
+install.packages("reticulate")
+```
+
+You only need to install packages once, but you need to mount those
+packages with the library() function each time you open R.
+
+``` r
+library(reticulate)
+```
+
+Python libraries are stored and managed in a few different libraries and
+their dependencies are not regulated as strictly as R libraries are in
+CRAN. It’s easier to publish a python package but it can also be more
+cumbersome for users because you need to manage dependencies yourself.
+You can download python packages using both R and Python code
+
+``` r
+py_install("laspy")
+```
+
+    ## + '/Users/ty/opt/miniconda3/bin/conda' 'install' '--yes' '--prefix' '/Users/ty/opt/miniconda3/envs/earth-analytics-python' '-c' 'conda-forge' 'laspy'
+
+Now, let’s create a Python list and assign it to a variable py_list:
+
+R code:
+
+``` r
+py_list <- r_to_py(list(1, 2, 3))
+```
+
+We can now print out the py_list variable in Python using the
+py_run_string() function:
+
+R code:
+
+``` r
+py_run_string("print(r.py_list)")
+```
+
+This will output \[1, 2, 3\] in the Python console.
+
+Now, let’s create an R vector and assign it to a variable r_vec:
+
+R code:
+
+``` r
+r_vec <- c(4, 5, 6)
+```
+
+We can now print out the r_vec variable in R using the py$ syntax to
+access Python variables:
+
+R code:
+
+``` r
+print(py$py_list)
+```
+
+This will output \[1, 2, 3\] in the R console.
+
+We can also call Python functions from R using the py_call() function.
+For example, let’s call the Python sum() function on the py_list
+variable and assign the result to an R variable r_sum:
+
+R code:
+
+``` r
+r_sum <- py_call("sum", args = list(py_list))
+```
+
+We can now print out the r_sum variable in R:
+
+R code:
+
+``` r
+print(r_sum)
+```
+
+This will output 6 in the R console.
+
+## Load packages and change settings
+
+``` r
+options(java.parameters = "-Xmx5G")
+
+library(r5r)
+library(sf)
+library(data.table)
+library(ggplot2)
+library(interp)
+library(dplyr)
+library(osmdata)
+library(ggthemes)
+library(sf)
+library(data.table)
+library(ggplot2)
+library(akima)
+library(dplyr)
+library(raster)
+library(osmdata)
+library(mapview)
+library(cowplot)
+library(here)
+library(testthat)
+```
+
+``` python
+import sys
+sys.argv.append(["--max-memory", "5G"])
+
+import pandas as pd
+import geopandas
+import matplotlib.pyplot as plt
+import numpy as np
+import plotnine
+import contextily as cx
+import r5py
+import seaborn as sns
+```
+
+R and Python are two popular programming languages used for data
+analysis, statistics, and machine learning. Although they share some
+similarities, there are some fundamental differences between them.
+Here’s an example code snippet in R and Python to illustrate some of the
+differences:
+
+R Code:
+
+``` r
+# Create a vector of numbers from 1 to 10
+x <- 1:10
+
+# Compute the mean of the vector
+mean_x <- mean(x)
+
+# Print the result
+print(mean_x)
+```
+
+    ## [1] 5.5
+
+Python Code:
+
+``` python
+# Import the numpy library for numerical operations
+import numpy as np
+
+# Create a numpy array of numbers from 1 to 10
+x = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10])
+
+# Compute the mean of the array
+mean_x = np.mean(x)
+
+# Print the result
+print(mean_x)
+```
+
+    ## 5.5
+
+In this example, we can see that there are several differences between R
+and Python:
+
+Syntax: R uses the assignment operator \<- while Python uses the equals
+sign = for variable assignment.
+
+Libraries: Python relies heavily on external libraries such as numpy,
+pandas, and matplotlib for data analysis, while R has built-in functions
+for many data analysis tasks.
+
+Data types: R is designed to work with vectors and matrices, while
+Python uses lists and arrays. In the example above, we used the numpy
+library to create a numerical array in Python.
+
+Function names: Function names in R and Python can differ significantly.
+In the example above, we used the mean() function in R and the np.mean()
+function in Python to calculate the mean of the vector/array.
+
+These are just a few of the many differences between R and Python.
+Ultimately, the choice between the two languages will depend on your
+specific needs and preferences.
+
+## Load saved data
+
+R Code:
+
+``` r
+data("iris")
+here()
+load(file=here("2_R_and_Py_bilingualism", "data", "iris_example_data.rdata"))
+objects()
+```
+
+Python code:
+
+## Save data
+
+R Code:
+
+``` r
+save(iris, file=here("2_R_and_Py_bilingualism", "data", "iris_example_data.rdata"))
+
+write.csv(iris, file=here("2_R_and_Py_bilingualism", "data", "iris_example_data.csv"))
+```
+
+Python code:
+
+## functions
+
+Both R and Python are powerful languages for writing functions that can
+take input, perform a specific task, and return output. R Code:
+
+``` r
+# Define a function that takes two arguments and returns their sum
+sum_r <- function(a, b) {
+  return(a + b)
+}
+
+# Call the function with two arguments and print the result
+result_r <- sum_r(3, 5)
+print(result_r)
+```
+
+    ## [1] 8
+
+Python code:
+
+``` python
+# Define a function that takes two arguments and returns their sum
+def sum_py(a, b):
+    return a + b
+
+# Call the function with two arguments and print the result
+result_py = sum_py(3, 5)
+print(result_py)
+```
+
+    ## 8
+
+In both cases, we define a function that takes two arguments and returns
+their sum. In R, we use the function keyword to define a function, while
+in Python, we use the def keyword. The function body in R is enclosed in
+curly braces, while in Python it is indented.
+
+There are a few differences in the syntax and functionality between the
+two approaches:
+
+Function arguments: In R, function arguments are separated by commas,
+while in Python they are enclosed in parentheses. The syntax for
+specifying default arguments and variable-length argument lists can also
+differ between the two languages. Return statement: In R, we use the
+return keyword to specify the return value of a function, while in
+Python, we simply use the return statement. Function names: Function
+names in R and Python can differ significantly. In the example above, we
+used the sum_r() function in R and the sum_py() function in Python to
+calculate the sum of two numbers.
+
+## Data Plots
+
+R Code:
+
+``` r
+# Load the "ggplot2" package for plotting
+library(ggplot2)
+
+# Generate some sample data
+x <- seq(1, 10, 1)
+y <- x + rnorm(10)
+
+# Create a scatter plot
+ggplot(data.frame(x, y), aes(x = x, y = y)) +
+  geom_point()
+```
+
+![](bilingualism_md_files/figure-gfm/unnamed-chunk-25-1.pdf)<!-- -->
+Python code:
+
+``` python
+# Load the "matplotlib" library
+import matplotlib.pyplot as plt
+
+# Generate some sample data
+import numpy as np
+x = np.arange(1, 11)
+y = x + np.random.normal(0, 1, 10)
+
+#clear last plot
+plt.clf()
+
+# Create a scatter plot
+plt.scatter(x, y)
+plt.show()
+```
+
+![](bilingualism_md_files/figure-gfm/unnamed-chunk-26-1.pdf)<!-- -->
+
+In both cases, we generate some sample data and create a scatter plot to
+visualize the relationship between the variables.
+
+There are a few differences in the syntax and functionality between the
+two approaches:
+
+Library and package names: In R, we use the ggplot2 package for
+plotting, while in Python, we use the matplotlib library. Data format:
+In R, we use a data frame to store the input data, while in Python, we
+use numpy arrays. Plotting functions: In R, we use the ggplot() function
+to create a new plot object, and then use the geom_point() function to
+create a scatter plot layer. In Python, we use the scatter() function
+from the matplotlib.pyplot module to create a scatter plot directly.
+
+## Linear regression
+
+R Code:
+
+``` r
+# Load the "ggplot2" package for plotting
+library(ggplot2)
+
+# Generate some sample data
+x <- seq(1, 10, 1)
+y <- x + rnorm(10)
+
+# Perform linear regression
+model_r <- lm(y ~ x)
+
+# Print the model summary
+summary(model_r)
+```
+
+    ## 
+    ## Call:
+    ## lm(formula = y ~ x)
+    ## 
+    ## Residuals:
+    ##      Min       1Q   Median       3Q      Max 
+    ## -1.69344 -0.42336  0.08961  0.34778  1.56728 
+    ## 
+    ## Coefficients:
+    ##             Estimate Std. Error t value Pr(>|t|)    
+    ## (Intercept)  -0.1676     0.6781  -0.247    0.811    
+    ## x             0.9750     0.1093   8.921 1.98e-05 ***
+    ## ---
+    ## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
+    ## 
+    ## Residual standard error: 0.9926 on 8 degrees of freedom
+    ## Multiple R-squared:  0.9087, Adjusted R-squared:  0.8972 
+    ## F-statistic: 79.59 on 1 and 8 DF,  p-value: 1.976e-05
+
+``` r
+# Plot the data and regression line
+ggplot(data.frame(x, y), aes(x = x, y = y)) +
+  geom_point() +
+  geom_smooth(method = "lm", se = FALSE)
+```
+
+    ## `geom_smooth()` using formula = 'y ~ x'
+
+![](bilingualism_md_files/figure-gfm/unnamed-chunk-27-3.pdf)<!-- -->
+
+Python code:
+
+``` python
+# Load the "matplotlib" and "scikit-learn" libraries
+import matplotlib.pyplot as plt
+from sklearn.linear_model import LinearRegression
+
+# Generate some sample data
+import numpy as np
+x = np.arange(1, 11)
+y = x + np.random.normal(0, 1, 10)
+
+# Perform linear regression
+model_py = LinearRegression().fit(x.reshape(-1, 1), y)
+
+# Print the model coefficients
+print("Coefficients: ", model_py.coef_)
+```
+
+    ## Coefficients:  [1.15539692]
+
+``` python
+print("Intercept: ", model_py.intercept_)
+
+#clear last plot
+```
+
+    ## Intercept:  -1.1291396173221218
+
+``` python
+plt.clf()
+
+# Plot the data and regression line
+plt.scatter(x, y)
+plt.plot(x, model_py.predict(x.reshape(-1, 1)), color='red')
+plt.show()
+```
+
+![](bilingualism_md_files/figure-gfm/unnamed-chunk-28-1.pdf)<!-- -->
+
+In both cases, we generate some sample data with a linear relationship
+between x and y, and then perform a simple linear regression to estimate
+the slope and intercept of the line. We then plot the data and
+regression line to visualize the fit.
+
+There are a few differences in the syntax and functionality between the
+two approaches:
+
+Library and package names: In R, we use the lm() function from the base
+package to perform linear regression, while in Python, we use the
+LinearRegression() class from the scikit-learn library. Additionally, we
+use the ggplot2 package in R for plotting, while we use the matplotlib
+library in Python. Data format: In R, we can specify the dependent and
+independent variables in the formula used for regression. In Python, we
+need to reshape the input data to a two-dimensional array before fitting
+the model. Model summary: In R, we can use the summary() function to
+print a summary of the model, including the estimated coefficients,
+standard errors, and p-values. In Python, we need to print the
+coefficients and intercept separately.
+
+## Random Forest
+
+R Code:
+
+``` r
+# Load the "randomForest" package
+library(randomForest)
+
+# Load the "iris" dataset
+data(iris)
+
+# Split the data into training and testing sets
+set.seed(123)
+train_idx <- sample(1:nrow(iris), nrow(iris) * 0.7, replace = FALSE)
+train_data <- iris[train_idx, ]
+test_data <- iris[-train_idx, ]
+
+# Build a random forest model
+rf_model <- randomForest(Species ~ ., data = train_data, ntree = 500)
+
+# Make predictions on the testing set
+predictions <- predict(rf_model, test_data)
+
+# Calculate accuracy of the model
+accuracy <- sum(predictions == test_data$Species) / nrow(test_data)
+print(paste("Accuracy:", accuracy))
+```
+
+    ## [1] "Accuracy: 0.977777777777778"
+
+Python code:
+
+``` python
+# Load the "pandas", "numpy", and "sklearn" libraries
+import pandas as pd
+import numpy as np
+from sklearn.ensemble import RandomForestClassifier
+from sklearn.datasets import load_iris
+from sklearn.model_selection import train_test_split
+
+# Load the "iris" dataset
+iris = load_iris()
+
+# Split the data into training and testing sets
+X_train, X_test, y_train, y_test = train_test_split(iris.data, iris.target, test_size=0.3, random_state=123)
+
+# Build a random forest model
+rf_model = RandomForestClassifier(n_estimators=500, random_state=123)
+rf_model.fit(X_train, y_train)
+
+# Make predictions on the testing set
+```
+
+    ## RandomForestClassifier(n_estimators=500, random_state=123)
+
+``` python
+predictions = rf_model.predict(X_test)
+
+# Calculate accuracy of the model
+accuracy = sum(predictions == y_test) / len(y_test)
+print("Accuracy:", accuracy)
+```
+
+    ## Accuracy: 0.9555555555555556
+
+In both cases, we load the iris dataset and split it into training and
+testing sets. We then build a random forest model using the training
+data and evaluate its accuracy on the testing data.
+
+There are a few differences in the syntax and functionality between the
+two approaches:
+
+Library and package names: In R, we use the randomForest package to
+build random forest models, while in Python, we use the
+RandomForestClassifier class from the sklearn.ensemble module. We also
+use different libraries for loading and manipulating data (pandas and
+numpy in Python, and built-in datasets in R). Model parameters: The
+syntax for setting model parameters is slightly different in R and
+Python. For example, in R, we specify the number of trees using the
+ntree parameter, while in Python, we use the n_estimators parameter.
+Data format: In R, we use a data frame to store the input data, while in
+Python, we use numpy arrays.
+
+## Basic streetmap from Open Street Map
+
+R Code:
+
+``` r
+# Load the "osmdata" package for mapping
+library(osmdata)
+library(tmap)
+
+# Define the map location and zoom level
+bbox <- c(left = -0.16, bottom = 51.49, right = -0.13, top = 51.51)
+
+# Get the OpenStreetMap data
+osm_data <- opq(bbox) %>% 
+  add_osm_feature(key = "highway") %>% 
+  osmdata_sf()
+
+# Plot the map using tmap
+tm_shape(osm_data$osm_lines) + 
+  tm_lines()
+```
+
+![](bilingualism_md_files/figure-gfm/unnamed-chunk-31-1.pdf)<!-- -->
+Python code:
+
+``` python
+# Load the "osmnx" package for mapping
+import osmnx as ox
+
+# Define the map location and zoom level
+bbox = (51.49, -0.16, 51.51, -0.13)
+
+# Get the OpenStreetMap data
+osm_data = ox.graph_from_bbox(north=bbox[2], south=bbox[0], east=bbox[3], west=bbox[1], network_type='all')
+
+# Plot the map using osmnx
+ox.plot_graph(osm_data)
+```
+
+    ## (<Figure size 1600x1600 with 0 Axes>, <AxesSubplot:>)
+
+![](bilingualism_md_files/figure-gfm/unnamed-chunk-32-1.pdf)<!-- -->
+
+In both cases, we define the map location and zoom level, retrieve the
+OpenStreetMap data using the specified bounding box, and plot the map.
+
+The main differences between the two approaches are:
+
+Package names and syntax: In R, we use the osmdata package and its
+syntax to download and process the OpenStreetMap data, while in Python,
+we use the osmnx package and its syntax. Mapping libraries: In R, we use
+the tmap package to create a static map of the OpenStreetMap data, while
+in Python, we use the built-in ox.plot_graph function from the osmnx
+package to plot the map.
+
+## CNN on Raster data
+
+R Code:
+
+``` r
+# Load the "keras" package for building the CNN
+library(tensorflow)
+library(keras)
+
+# Load the "raster" package for working with raster data
+library(raster)
+
+# Load the "magrittr" package for pipe operator
+library(magrittr)
+
+# Load the data as a raster brick
+raster_data <- brick("raster_data.tif")
+
+# Split the data into training and testing sets
+split_data <- sample(1:nlayers(raster_data), size = nlayers(raster_data)*0.8, replace = FALSE)
+train_data <- raster_data[[split_data]]
+test_data <- raster_data[[setdiff(1:nlayers(raster_data), split_data)]]
+
+# Define the CNN model
+model <- keras_model_sequential() %>% 
+  layer_conv_2d(filters = 32, kernel_size = c(3, 3), activation = "relu", input_shape = c(ncol(train_data), nrow(train_data), ncell(train_data))) %>% 
+  layer_max_pooling_2d(pool_size = c(2, 2)) %>% 
+  layer_dropout(rate = 0.25) %>% 
+  layer_flatten() %>% 
+  layer_dense(units = 128, activation = "relu") %>% 
+  layer_dropout(rate = 0.5) %>% 
+  layer_dense(units = nlayers(train_data), activation = "softmax")
+
+# Compile the model
+model %>% compile(loss = "categorical_crossentropy", optimizer = "adam", metrics = "accuracy")
+
+# Train the model
+history <- model %>% fit(x = array(train_data), y = to_categorical(1:nlayers(train_data)), epochs = 10, validation_split = 0.2)
+
+# Evaluate the model
+model %>% evaluate(x = array(test_data), y = to_categorical(1:nlayers(test_data)))
+
+# Plot the model accuracy over time
+plot(history)
+```
+
+## Piping
+
+Piping is a powerful feature in both R and Python that allows for a more
+streamlined and readable code. However, the syntax for piping is
+slightly different between the two languages.
+
+In R, piping is done using the %\>% operator from the magrittr package,
+while in Python, it is done using the \| operator from the pandas
+package.
+
+Let’s compare and contrast piping in R and Python with some examples:
+
+Piping in R In R, we can use the %\>% operator to pipe output from one
+function to another, which can make our code more readable and easier to
+follow. Here’s an example:
+
+R code:
+
+``` r
+library(dplyr)
+
+# create a data frame
+df <- data.frame(x = c(1,2,3), y = c(4,5,6))
+
+# calculate the sum of column x and y
+df %>%
+  mutate(z = x + y) %>%
+  summarize(sum_z = sum(z))
+```
+
+    ##   sum_z
+    ## 1    21
+
+In this example, we first create a data frame df with two columns x and
+y. We then pipe the output of df to mutate, which adds a new column z to
+the data frame that is the sum of x and y. Finally, we pipe the output
+to summarize, which calculates the sum of z and returns the result.
+
+Piping in Python In Python, we can use the \| operator to pipe output
+from one function to another. However, instead of piping output from one
+function to another, we pipe a DataFrame to a method of the DataFrame.
+Here’s an example:
+
+Python code:
+
+``` python
+import pandas as pd
+
+# create a DataFrame
+df = pd.DataFrame({'x': [1,2,3], 'y': [4,5,6]})
+
+# calculate the sum of column x and y
+(df.assign(z = df['x'] + df['y'])
+   .agg(sum_z = ('z', 'sum')))
+```
+
+    ##         z
+    ## sum_z  21
+
+In this example, we first create a DataFrame df with two columns x and
+y. We then use the assign() method to add a new column z to the
+DataFrame that is the sum of x and y. Finally, we use the agg() method
+to calculate the sum of z and return the result.
+
+As we can see, the syntax for piping is slightly different between R and
+Python, but the concept remains the same. Piping can make our code more
+readable and easier to follow, which is an important aspect of creating
+efficient and effective code.
+
+R code:
+
+``` r
+library(dplyr)
+library(ggplot2)
+
+iris %>%
+  filter(Species == "setosa") %>%
+  group_by(Sepal.Width) %>%
+  summarise(mean.Petal.Length = mean(Petal.Length)) %>%
+  mutate(Sepal.Width = as.factor(Sepal.Width)) %>%
+  ggplot(aes(x = Sepal.Width, y = mean.Petal.Length)) +
+  geom_bar(stat = "identity", fill = "dodgerblue") +
+  labs(title = "Mean Petal Length of Setosa by Sepal Width",
+       x = "Sepal Width",
+       y = "Mean Petal Length")
+```
+
+![](bilingualism_md_files/figure-gfm/unnamed-chunk-37-1.pdf)<!-- -->
+
+In this example, we start with the iris dataset and filter it to only
+include rows where the Species column is “setosa”. We then group the
+remaining rows by the Sepal.Width column and calculate the mean
+Petal.Length for each group. Next, we convert Sepal.Width to a factor
+variable to ensure that it is treated as a categorical variable in the
+visualization. Finally, we create a bar plot using ggplot2, with
+Sepal.Width on the x-axis and mean.Petal.Length on the y-axis. The
+resulting plot shows the mean petal length of setosa flowers for each
+sepal width category.
+
+Python code:
+
+``` python
+import pandas as pd
+
+# Load the iris dataset and pipe it into the next function
+( pd.read_csv("https://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data", header=None, names=['sepal_length', 'sepal_width', 'petal_length', 'petal_width', 'class'])
+  
+  # Select columns and pivot the dataset
+  .loc[:, ['sepal_length', 'sepal_width', 'petal_length']]
+  .melt(var_name='variable', value_name='value')
+  
+  # Group by variable and calculate mean
+  .groupby('variable', as_index=False)
+  .mean()
+  
+  # Filter for mean greater than 3.5 and sort by descending mean
+  .query('value > 3.5')
+  .sort_values('value', ascending=False)
+)
+```
+
+    ##        variable     value
+    ## 1  sepal_length  5.843333
+    ## 0  petal_length  3.758667
+
+## for loops
+
+Here is an example of a for loop in R:
+
+R code
+
+``` r
+# Create a vector of numbers
+numbers <- c(1, 2, 3, 4, 5)
+
+# Use a for loop to print out each number in the vector
+for (i in numbers) {
+  print(i)
+}
+```
+
+    ## [1] 1
+    ## [1] 2
+    ## [1] 3
+    ## [1] 4
+    ## [1] 5
+
+In this example, the for loop iterates over each element in the numbers
+vector, assigning the current element to the variable i. The print(i)
+statement is then executed for each iteration, outputting the value of
+i.
+
+Here is the equivalent example in Python:
+
+Python code
+
+``` python
+# Create a list of numbers
+numbers = [1, 2, 3, 4, 5]
+
+# Use a for loop to print out each number in the list
+for i in numbers:
+  print(i)
+```
+
+    ## 1
+    ## 2
+    ## 3
+    ## 4
+    ## 5
+
+In Python, the for loop iterates over each element in the numbers list,
+assigning the current element to the variable i. The print(i) statement
+is then executed for each iteration, outputting the value of i.
+
+Both languages also support nested for loops, which can be used to
+perform iterations over multiple dimensions, such as looping through a
+2D array.
+
+## Parallel
+
+Parallel computing is a technique used to execute multiple computational
+tasks simultaneously, which can significantly reduce the time required
+to complete a task. Both R and Python have built-in support for parallel
+computing, although the approaches are slightly different. In this
+answer, we will compare and contrast the parallel computing capabilities
+of R and Python, and provide working examples in code.
+
+Parallel computing in R In R, there are several packages that support
+parallel computing, such as parallel, foreach, and doParallel. The
+parallel package provides basic functionality for parallel computing,
+while foreach and doParallel provide higher-level abstractions that make
+it easier to write parallel code.
+
+Here is an example of using the foreach package to execute a loop in
+parallel:
+
+R code:
+
+``` r
+library(foreach)
+library(doParallel)
+
+# Set up a parallel backend with 4 workers
+cl <- makeCluster(4)
+registerDoParallel(cl)
+
+# Define a function to apply in parallel
+myfunc <- function(x) {
+  # some computation here
+  return(x^2)
+}
+
+# Generate some data
+mydata <- 1:1000
+
+# Apply the function to the data in parallel
+result <- foreach(i = mydata) %dopar% {
+  myfunc(i)
+}
+
+# Stop the cluster
+stopCluster(cl)
+```
+
+In this example, we use the makeCluster() function to set up a cluster
+with 4 workers, and the registerDoParallel() function to register the
+cluster as the parallel backend for foreach. We then define a function
+myfunc() that takes an input x and returns x^2. We generate some data
+mydata and use foreach to apply myfunc() to each element of mydata in
+parallel, using the %dopar% operator.
+
+R Tidyverse parallel
+
+In R Tidyverse, we can use the furrr package for parallel computing.
+Here’s an example of using furrr to parallelize a map function:
+
+R Tidy code:
+
+``` r
+library(tidyverse)
+library(furrr)
+
+# Generate a list of numbers
+numbers <- 1:10
+
+# Use the future_map function from furrr to parallelize the map function
+plan(multisession)
+squares <- future_map(numbers, function(x) x^2)
+```
+
+In this example, we first load the Tidyverse and furrr libraries. We
+then generate a list of numbers from 1 to 10. We then use the plan
+function to set the parallelization strategy to “multisession”, which
+will use multiple CPU cores to execute the code. Finally, we use the
+future_map function from furrr to apply the function x^2 to each number
+in the list in parallel.
+
+Parallel computing in Python In Python, the standard library includes
+the multiprocessing module, which provides basic support for parallel
+computing. Additionally, there are several third-party packages that
+provide higher-level abstractions, such as joblib and dask.
+
+Here is an example of using the multiprocessing module to execute a loop
+in parallel:
+
+Python code:
+
+``` python
+def square(x):
+    return x**2
+  
+from multiprocessing import Pool
+
+# Generate a list of numbers
+numbers = list(range(1, 11))
+
+# Use the map function and a pool of workers to parallelize the square function
+with Pool() as pool:
+    squares = pool.map(square, numbers)
+    
+print(squares)
+```
+
+In this example, we define a function myfunc() that takes an input x and
+returns x^2. We generate some data mydata and use the Pool class from
+the multiprocessing module to set up a pool of 4 workers. We then use
+the map() method of the Pool class to apply myfunc() to each element of
+mydata in parallel.
+
+Comparison and contrast Both R and Python have built-in support for
+parallel computing, with similar basic functionality for creating and
+managing parallel processes. However, the higher-level abstractions
+differ between the two languages. In R, the foreach package provides a
+high-level interface that makes it easy to write parallel code, while in
+Python, the multiprocessing module provides a basic interface that can
+be extended using third-party packages like joblib and dask.
+
+Additionally, Python has better support for distributed computing using
+frameworks like Apache Spark, while R has better support for
+shared-memory parallelism using tools like data.table and ff.
+
+## Data wrangling
+
+Data wrangling is an important part of any data analysis project, and
+both R and Python provide tools and libraries for performing this task.
+In this answer, we will compare and contrast data wrangling in R’s
+tidyverse and Python’s pandas library, with working examples in code.
+
+Data Wrangling in R Tidyverse
+
+The tidyverse is a collection of R packages designed for data science,
+and it includes several packages that are useful for data wrangling. One
+of the most popular packages is dplyr, which provides a grammar of data
+manipulation for data frames.
+
+Here is an example of using dplyr to filter, mutate, and summarize a
+data frame:
+
+R code
+
+``` r
+library(dplyr)
+
+# Load data
+data(mtcars)
+
+# Filter for cars with more than 100 horsepower
+mtcars %>%
+  filter(hp > 100) %>%
+  # Add a new column with fuel efficiency in km per liter
+  mutate(kmpl = 0.425 * mpg) %>%
+  # Group by number of cylinders and summarize
+  group_by(cyl) %>%
+  summarize(mean_hp = mean(hp),
+            mean_kmpl = mean(kmpl))
+```
+
+    ## # A tibble: 3 × 3
+    ##     cyl mean_hp mean_kmpl
+    ##   <dbl>   <dbl>     <dbl>
+    ## 1     4    111      11.0 
+    ## 2     6    122.      8.39
+    ## 3     8    209.      6.42
+
+In this example, we first filter the mtcars data frame to only include
+cars with more than 100 horsepower. We then use mutate to create a new
+column with fuel efficiency in kilometers per liter. Finally, we group
+the data by the number of cylinders and calculate the mean horsepower
+and fuel efficiency.
+
+Data Wrangling in Python Pandas
+
+Pandas is a popular library for data manipulation in Python. It provides
+a data frame object similar to R’s data frames, along with a wide range
+of functions for data wrangling.
+
+Here is an example of using pandas to filter, transform, and group a
+data frame:
+
+Python code:
+
+``` python
+import pandas as pd
+
+# Load data
+mtcars = pd.read_csv('https://raw.githubusercontent.com/mwaskom/seaborn-data/master/mtcars.csv')
+
+# Filter for cars with more than 100 horsepower
+filtered_mtcars = mtcars[mtcars['hp'] > 100]
+
+# Add a new column with fuel efficiency in km per liter
+filtered_mtcars['kmpl'] = 0.425 * filtered_mtcars['mpg']
+
+# Group by number of cylinders and calculate mean horsepower and fuel efficiency
+grouped_mtcars = filtered_mtcars.groupby('cyl').agg({'hp': 'mean',
+                                                     'kmpl': 'mean'})
+```
+
+In this example, we first load the mtcars data from a CSV file. We then
+filter the data to only include cars with more than 100 horsepower,
+using boolean indexing. We use the assign function to create a new
+column with fuel efficiency in kilometers per liter. Finally, we group
+the data by the number of cylinders and calculate the mean horsepower
+and fuel efficiency.
+
+Comparison
+
+Overall, both R’s tidyverse and Python’s pandas provide similar
+functionality for data wrangling. Both allow for filtering,
+transforming, and aggregating data frames. The syntax for performing
+these operations is slightly different between the two languages, with R
+using the %\>% operator for chaining operations and Python using method
+chaining or the apply family of functions.
+
+One key difference between the two languages is that R’s tidyverse
+provides a consistent grammar for data manipulation across its various
+packages, making it easier to learn and use. However, Python’s pandas
+library has a larger developer community and is more versatile for use
+in other applications, such as web development or machine learning.
+
+In conclusion, both R and Python provide powerful tools for data
+wrangling, and the choice between the two ultimately depends on the
+specific needs of the user and their familiarity
+
+## Data from API
+
+Retrieving data from an API is a common task in both R and Python. Here
+are examples of how to retrieve data from an API in both languages:
+
+Python
+
+To retrieve data from an API in Python, we can use the requests library.
+Here’s an example of how to retrieve weather data from the
+OpenWeatherMap API:
+
+Python code:
+
+``` python
+import requests
+
+url = 'https://api.openweathermap.org/data/2.5/weather?q=London,uk&appid=API_KEY'
+
+response = requests.get(url)
+
+data = response.json()
+
+print(data)
+```
+
+This code retrieves the current weather data for London from the
+OpenWeatherMap API. We first construct the API URL with the location and
+API key, then use the requests.get() function to make a request to the
+API. We then extract the JSON data from the response using the .json()
+method and print the resulting data.
+
+R
+
+In R, we can use the httr package to retrieve data from an API. Here’s
+an example of how to retrieve weather data from the OpenWeatherMap API
+in R:
+
+R code:
+
+``` r
+library(httr)
+
+url <- 'https://api.openweathermap.org/data/2.5/weather?q=London,uk&appid=API_KEY'
+
+response <- GET(url)
+
+data <- content(response, 'text')
+
+print(data)
+```
+
+This code is similar to the Python code above. We first load the httr
+library, then construct the API URL and use the GET() function to make a
+request to the API. We then extract the data from the response using the
+content() function and print the resulting data.
+
+Retrieving Data from an API in R Tidyverse In R Tidyverse, we can use
+the httr and jsonlite packages to retrieve and process data from an API.
+
+R code:
+
+``` r
+# Load required packages
+library(httr)
+library(jsonlite)
+
+# Define API endpoint
+endpoint <- "https://jsonplaceholder.typicode.com/posts"
+
+# Retrieve data from API
+response <- GET(endpoint)
+
+# Extract content from response
+content <- content(response, "text")
+
+# Convert content to JSON
+json <- fromJSON(content)
+
+# Convert JSON to a data frame
+df <- as.data.frame(json)
+```
+
+In the above example, we use the GET() function from the httr package to
+retrieve data from an API endpoint, and the content() function to
+extract the content of the response. We then use the fromJSON() function
+from the jsonlite package to convert the JSON content to a list, and the
+as.data.frame() function to convert the list to a data frame.
+
+Retrieving Data from an API in Python In Python, we can use the requests
+library to retrieve data from an API, and the json library to process
+the JSON data.
+
+Python code:
+
+``` python
+# Load required libraries
+import requests
+import json
+
+# Define API endpoint
+endpoint = "https://jsonplaceholder.typicode.com/posts"
+
+# Retrieve data from API
+response = requests.get(endpoint)
+
+# Extract content from response
+content = response.content
+
+# Convert content to JSON
+json_data = json.loads(content)
+
+# Convert JSON to a list of dictionaries
+data = [dict(row) for row in json_data]
+```
+
+In the above example, we use the get() function from the requests
+library to retrieve data from an API endpoint, and the content attribute
+to extract the content of the response. We then use the loads() function
+from the json library to convert the JSON content to a list of
+dictionaries.
+
+Comparison Both R Tidyverse and Python provide powerful tools for
+retrieving and processing data from an API. In terms of syntax, the two
+languages are somewhat similar. In both cases, we use a library to
+retrieve data from the API, extract the content of the response, and
+then process the JSON data. However, there are some differences in the
+specific functions and methods used. For example, in R Tidyverse, we use
+the content() function to extract the content of the response, whereas
+in Python, we use the content attribute. Additionally, in R Tidyverse,
+we use the fromJSON() function to convert the JSON data to a list,
+whereas in Python, we use the loads() function.
+
+## Census data
+
+Retrieving USA census data in R, R Tidy, and Python can be done using
+different packages and libraries. Here are some working examples in code
+for each language:
+
+R:
+
+To retrieve census data in R, we can use the tidycensus package. Here’s
+an example of how to retrieve the total population for the state of
+California:
+
+R code:
+
+``` r
+library(tidycensus)
+library(tidyverse)
+
+# Set your Census API key
+census_api_key("your_api_key")
+
+# Get the total population for the state of California
+ca_pop <- get_acs(
+  geography = "state",
+  variables = "B01003_001",
+  state = "CA"
+) %>% 
+  rename(total_population = estimate) %>% 
+  select(total_population)
+
+# View the result
+ca_pop
+```
+
+R Tidy:
+
+To retrieve census data in R Tidy, we can also use the tidycensus
+package. Here’s an example of how to retrieve the total population for
+the state of California using pipes and dplyr functions:
+
+R tidy code:
+
+``` r
+library(tidycensus)
+library(tidyverse)
+
+# Set your Census API key
+census_api_key("your_api_key")
+
+# Get the total population for the state of California
+ca_pop <- get_acs(
+  geography = "state",
+  variables = "B01003_001",
+  state = "CA"
+) %>% 
+  rename(total_population = estimate) %>% 
+  select(total_population)
+
+# View the result
+ca_pop
+```
+
+Python:
+
+To retrieve census data in Python, we can use the census library. Here’s
+an example of how to retrieve the total population for the state of
+California:
+
+Python code:
+
+``` python
+from census import Census
+from us import states
+import pandas as pd
+
+# Set your Census API key
+c = Census("your_api_key")
+
+# Get the total population for the state of California
+ca_pop = c.acs5.state(("B01003_001"), states.CA.fips, year=2019)
+
+# Convert the result to a Pandas DataFrame
+ca_pop_df = pd.DataFrame(ca_pop)
+
+# Rename the column
+ca_pop_df = ca_pop_df.rename(columns={"B01003_001E": "total_population"})
+
+# Select only the total population column
+ca_pop_df = ca_pop_df[["total_population"]]
+
+# View the result
+ca_pop_df
+```
+
+## Lidar data
+
+To find Lidar data in R and Python, you typically need to start by
+identifying sources of Lidar data and then accessing them using
+appropriate packages and functions. Here are some examples of how to
+find Lidar data in R and Python:
+
+R:
+
+Identify sources of Lidar data: The USGS National Map Viewer provides
+access to Lidar data for the United States. You can also find Lidar data
+on state and local government websites, as well as on commercial data
+providers’ websites. Access the data: You can use the lidR package in R
+to download and read Lidar data in the LAS format. For example, the
+following code downloads and reads Lidar data for a specific area:
+
+R code:
+
+``` r
+library(lidR)
+
+# Download Lidar data
+LASfile <- system.file("extdata", "Megaplot.laz", package="lidR")
+lidar <- readLAS(LASfile)
+
+# Visualize the data
+plot(lidar)
+```
+
+Python:
+
+Identify sources of Lidar data: The USGS 3DEP program provides access to
+Lidar data for the United States. You can also find Lidar data on state
+and local government websites, as well as on commercial data providers’
+websites. Access the data: You can use the pylastools package in Python
+to download and read Lidar data in the LAS format. For example, the
+following code downloads and reads Lidar data for a specific area:
+
+Python code:
+
+``` r
+py_install("requests")
+py_install("pylas")
+py_install("laspy")
+```
+
+``` python
+import requests
+from pylas import read
+import laspy
+import numpy as np
+
+# Download Lidar data
+url = "https://s3-us-west-2.amazonaws.com/usgs-lidar-public/USGS_LPC_CA_SanFrancisco_2016_LAS_2018.zip"
+lasfile = "USGS_LPC_CA_SanFrancisco_2016_LAS_2018.las"
+r = requests.get(url, allow_redirects=True)
+open(lasfile, 'wb').write(r.content)
+
+# Read the data
+lidar = read(lasfile)
+
+# Visualize the data
+laspy.plot.plot(lidar)
+```
+
+## Data for black lives
+
+Data for Black Lives (<https://d4bl.org/>) is a movement that uses data
+science to create measurable change in the lives of Black people. While
+the Data for Black Lives website provides resources, reports, articles,
+and datasets related to racial equity, it doesn’t provide a direct API
+for downloading data.
+
+Instead, you can access the Data for Black Lives GitHub repository
+(<https://github.com/Data4BlackLives>) to find datasets and resources to
+work with. In this example, we’ll use a sample dataset available at
+<https://github.com/Data4BlackLives/covid-19/tree/master/data>. The
+dataset “COVID19_race_data.csv” contains COVID-19 race-related data.
+
+R: In R, we’ll use the ‘readr’ and ‘dplyr’ packages to read, process,
+and analyze the dataset.
+
+R code:
+
+``` r
+# Install and load necessary libraries
+
+library(readr)
+library(dplyr)
+
+# Read the CSV file
+url <- "https://raw.githubusercontent.com/Data4BlackLives/covid-19/master/data/COVID19_race_data.csv"
+data <- read_csv(url)
+
+# Basic information about the dataset
+print(dim(data))
+print(head(data))
+
+# Example analysis: calculate the mean of 'cases_total' by 'state'
+data %>%
+  group_by(state) %>%
+  summarize(mean_cases_total = mean(cases_total, na.rm = TRUE)) %>%
+  arrange(desc(mean_cases_total))
+```
+
+Python: In Python, we’ll use the ‘pandas’ library to read, process, and
+analyze the dataset.
+
+Python code:
+
+``` python
+import pandas as pd
+
+# Read the CSV file
+url = "https://raw.githubusercontent.com/Data4BlackLives/covid-19/master/data/COVID19_race_data.csv"
+data = pd.read_csv(url)
+
+# Basic information about the dataset
+print(data.shape)
+print(data.head())
+
+# Example analysis: calculate the mean of 'cases_total' by 'state'
+mean_cases_total = data.groupby("state")["cases_total"].mean().sort_values(ascending=False)
+print(mean_cases_total)
+```
+
+In conclusion, both R and Python provide powerful libraries and tools
+for downloading, processing, and analyzing datasets, such as those found
+in the Data for Black Lives repository. The ‘readr’ and ‘dplyr’
+libraries in R offer a simple and intuitive way to read and manipulate
+data, while the ‘pandas’ library in Python offers similar functionality
+with a different syntax. Depending on your preferred programming
+language and environment, both options can be effective in working with
+social justice datasets.
+
+## Propublica Congress API
+
+The ProPublica Congress API provides information about the U.S. Congress
+members and their voting records. In this example, we’ll fetch data
+about the current Senate members and calculate the number of members in
+each party.
+
+R: In R, we’ll use the ‘httr’ and ‘jsonlite’ packages to fetch and
+process data from the ProPublica Congress API.
+
+R code:
+
+``` r
+# load necessary libraries
+library(httr)
+library(jsonlite)
+
+# Replace 'your_api_key' with your ProPublica API key
+
+#
+
+# Fetch data about the current Senate members
+url <- "https://api.propublica.org/congress/v1/117/senate/members.json"
+response <- GET(url, add_headers(`X-API-Key` = api_key))
+
+# Check if the request was successful
+if (http_status(response)$category == "Success") {
+  data <- content(response, "parsed")
+  members <- data$results[[1]]$members
+  
+  # Calculate the number of members in each party
+  party_counts <- table(sapply(members, function(x) x$party))
+  print(party_counts)
+} else {
+  print(http_status(response)$message)
+}
+```
+
+    ## 
+    ##  D  I ID  R 
+    ## 49  1  2 51
+
+Python: In Python, we’ll use the ‘requests’ library to fetch data from
+the ProPublica Congress API and ‘pandas’ library to process the data.
+
+python code:
+
+``` python
+# Install necessary libraries
+
+import requests
+import pandas as pd
+
+# Replace 'your_api_key' with your ProPublica API key
+api_key = "your_api_key"
+headers = {"X-API-Key": api_key}
+
+# Fetch data about the current Senate members
+url = "https://api.propublica.org/congress/v1/117/senate/members.json"
+response = requests.get(url, headers=headers)
+
+# Check if the request was successful
+if response.status_code == 200:
+    data = response.json()
+    members = data["results"][0]["members"]
+    
+    # Calculate the number of members in each party
+    party_counts = pd.DataFrame(members)["party"].value_counts()
+    print(party_counts)
+else:
+    print(f"Error: {response.status_code}")
+```
+
+In conclusion, both R and Python offer efficient ways to fetch and
+process data from APIs like the ProPublica Congress API. The ‘httr’ and
+‘jsonlite’ libraries in R provide a straightforward way to make HTTP
+requests and parse JSON data, while the ‘requests’ library in Python
+offers similar functionality. The ‘pandas’ library in Python can be used
+for data manipulation and analysis, and R provides built-in functions
+like table() for aggregating data. Depending on your preferred
+programming language and environment, both options can be effective for
+working with the ProPublica Congress API.
+
+## Nonprofit Explorer API by ProPublica
+
+The Nonprofit Explorer API by ProPublica provides data on tax-exempt
+organizations in the United States. In this example, we’ll search for
+organizations with the keyword “education” and analyze the results.
+
+R: In R, we’ll use the ‘httr’ and ‘jsonlite’ packages to fetch and
+process data from the Nonprofit Explorer API.
+
+R code:
+
+``` r
+# Install and load necessary libraries
+library(httr)
+library(jsonlite)
+
+# Fetch data for organizations with the keyword "education"
+url <- "https://projects.propublica.org/nonprofits/api/v2/search.json?q=education"
+response <- GET(url)
+
+# Check if the request was successful
+if (http_status(response)$category == "Success") {
+  data <- content(response, "parsed")
+  organizations <- data$organizations
+  
+  # Count the number of organizations per state
+  state_counts <- table(sapply(organizations, function(x) x$state))
+  print(state_counts)
+} else {
+  print(http_status(response)$message)
+}
+```
+
+    ## 
+    ##      AZ      CA      CO      DC      FL      GA      HI      IL Indiana      LA 
+    ##       3      22       6       5       3       2       1       2       1       1 
+    ##      MD      MI      MN      MO      MP      MS      NC      NE      NJ      NM 
+    ##       1       2       5       3       1       1       2       2       2       1 
+    ##      NY      OH      OK  Oregon      PA      TX      UT      VA      WA      WV 
+    ##       1       5       1       2       2      12       1       4       3       1 
+    ##      ZZ 
+    ##       2
+
+Python: In Python, we’ll use the ‘requests’ library to fetch data from
+the Nonprofit Explorer API and ‘pandas’ library to process the data.
+
+Python code:
+
+``` python
+# Install necessary libraries
+import requests
+import pandas as pd
+
+# Fetch data for organizations with the keyword "education"
+url = "https://projects.propublica.org/nonprofits/api/v2/search.json?q=education"
+response = requests.get(url)
+
+# Check if the request was successful
+if response.status_code == 200:
+    data = response.json()
+    organizations = data["organizations"]
+    
+    # Count the number of organizations per state
+    state_counts = pd.DataFrame(organizations)["state"].value_counts()
+    print(state_counts)
+else:
+    print(f"Error: {response.status_code}")
+```
+
+    ## CA         22
+    ## TX         12
+    ## CO          6
+    ## MN          5
+    ## OH          5
+    ## DC          5
+    ## VA          4
+    ## AZ          3
+    ## WA          3
+    ## MO          3
+    ## FL          3
+    ## IL          2
+    ## GA          2
+    ## NC          2
+    ## MI          2
+    ## Oregon      2
+    ## NE          2
+    ## ZZ          2
+    ## PA          2
+    ## NJ          2
+    ## HI          1
+    ## MS          1
+    ## NY          1
+    ## Indiana     1
+    ## NM          1
+    ## LA          1
+    ## UT          1
+    ## MD          1
+    ## MP          1
+    ## WV          1
+    ## OK          1
+    ## Name: state, dtype: int64
+
+In conclusion, both R and Python offer efficient ways to fetch and
+process data from APIs like the Nonprofit Explorer API. The ‘httr’ and
+‘jsonlite’ libraries in R provide a straightforward way to make HTTP
+requests and parse JSON data, while the ‘requests’ library in Python
+offers similar functionality. The ‘pandas’ library in Python can be used
+for data manipulation and analysis, and R provides built-in functions
+like table() for aggregating data. Depending on your preferred
+programming language and environment, both options can be effective for
+working with the Nonprofit Explorer API.
+
+## Campaign Finance API by ProPublica
+
+The Campaign Finance API by the Federal Election Commission (FEC)
+provides data on campaign finance in U.S. federal elections. In this
+example, we’ll fetch data about individual contributions for the 2020
+election cycle and analyze the results.
+
+R: In R, we’ll use the ‘httr’ and ‘jsonlite’ packages to fetch and
+process data from the Campaign Finance API.
+
+R code:
+
+``` r
+# Install and load necessary libraries
+library(httr)
+library(jsonlite)
+
+# Fetch data about individual contributions for the 2020 election cycle
+url <- "https://api.open.fec.gov/v1/schedules/schedule_a/?api_key='OGwpkX7tH5Jihs1qQcisKfVAMddJzmzouWKtKoby'&two_year_transaction_period=2020&sort_hide_null=false&sort_null_only=false&per_page=20&page=1"
+response <- GET(url)
+
+# Check if the request was successful
+if (http_status(response)$category == "Success") {
+  data <- content(response, "parsed")
+  contributions <- data$results
+  
+  # Calculate the total contributions per state
+  state_totals <- aggregate(contributions$contributor_state, by = list(contributions$contributor_state), FUN = sum)
+  colnames(state_totals) <- c("State", "Total_Contributions")
+  print(state_totals)
+} else {
+  print(http_status(response)$message)
+}
+```
+
+    ## [1] "Client error: (403) Forbidden"
+
+Python: In Python, we’ll use the ‘requests’ library to fetch data from
+the Campaign Finance API and ‘pandas’ library to process the data.
+
+Python code:
+
+``` python
+# Install necessary libraries
+
+import requests
+import pandas as pd
+
+# Fetch data about individual contributions for the 2020 election cycle
+url = "https://api.open.fec.gov/v1/schedules/schedule_a/?api_key=your_api_key&two_year_transaction_period=2020&sort_hide_null=false&sort_null_only=false&per_page=20&page=1"
+response = requests.get(url)
+
+# Check if the request was successful
+if response.status_code == 200:
+    data = response.json()
+    contributions = data["results"]
+    
+    # Calculate the total contributions per state
+    df = pd.DataFrame(contributions)
+    state_totals = df.groupby("contributor_state")["contribution_receipt_amount"].sum()
+    print(state_totals)
+else:
+    print(f"Error: {response.status_code}")
+```
+
+    ## Error: 403
+
+In conclusion, both R and Python offer efficient ways to fetch and
+process data from APIs like the Campaign Finance API. The ‘httr’ and
+‘jsonlite’ libraries in R provide a straightforward way to make HTTP
+requests and parse JSON data, while the ‘requests’ library in Python
+offers similar functionality. The ‘pandas’ library in Python can be used
+for data manipulation and analysis, and R provides built-in functions
+like aggregate() for aggregating data. Depending on your preferred
+programming language and environment, both options can be effective for
+working with the Campaign Finance API.
+
+Note: Remember to replace your_api_key with your actual FEC API key in
+the code examples above.
+
+## Historic Redlining
+
+Historic redlining data refers to data from the Home Owners’ Loan
+Corporation (HOLC) that created residential security maps in the 1930s,
+which contributed to racial segregation and disinvestment in minority
+neighborhoods. One popular source for this data is the Mapping
+Inequality project (<https://dsl.richmond.edu/panorama/redlining/>).
+
+In this example, we’ll download historic redlining data for Philadelphia
+in the form of a GeoJSON file and analyze the data in R and Python.
+
+R: In R, we’ll use the ‘sf’ and ‘dplyr’ packages to read and process the
+GeoJSON data.
+
+R code:
+
+``` r
+# Install and load necessary libraries
+library(sf)
+library(dplyr)
+
+# Download historic redlining data for Philadelphia
+url <- "https://dsl.richmond.edu/panorama/redlining/static/downloads/geojson/PAPhiladelphia1937.geojson"
+philly_geojson <- read_sf(url)
+
+# Count the number of areas per HOLC grade
+grade_counts <- philly_geojson %>%
+  group_by(holc_grade) %>%
+  summarize(count = n())
+
+plot(grade_counts)
+```
+
+![](bilingualism_md_files/figure-gfm/unnamed-chunk-65-1.pdf)<!-- -->
+
+Python: In Python, we’ll use the ‘geopandas’ library to read and process
+the GeoJSON data.
+
+Python code:
+
+``` python
+# Install necessary libraries
+
+
+import geopandas as gpd
+
+# Download historic redlining data for Philadelphia
+url = "https://dsl.richmond.edu/panorama/redlining/static/downloads/geojson/PAPhiladelphia1937.geojson"
+philly_geojson = gpd.read_file(url)
+
+# Count the number of areas per HOLC grade
+grade_counts = philly_geojson["holc_grade"].value_counts()
+print(grade_counts)
+```
+
+    ## B    28
+    ## D    26
+    ## C    18
+    ## A    10
+    ## Name: holc_grade, dtype: int64
+
+In conclusion, both R and Python offer efficient ways to download and
+process historic redlining data in the form of GeoJSON files. The ‘sf’
+package in R provides a simple way to read and manipulate spatial data,
+while the ‘geopandas’ library in Python offers similar functionality.
+The ‘dplyr’ package in R can be used for data manipulation and analysis,
+and Python’s built-in functions like value_counts() can be used for
+aggregating data. Depending on your preferred programming language and
+environment, both options can be effective for working with historic
+redlining data.
+
+## American Indian and Alaska Native Areas (AIANNH)
+
+In this example, we’ll download and analyze the American Indian and
+Alaska Native Areas (AIANNH) TIGER/Line Shapefile from the U.S. Census
+Bureau. We’ll download the data for the year 2020, and analyze the
+number of AIANNH per congressional district
+
+R: In R, we’ll use the ‘sf’ and ‘dplyr’ packages to read and process the
+Shapefile data.
+
+R code:
+
+``` r
+# Install and load necessary libraries
+library(sf)
+library(dplyr)
+
+# Download historic redlining data for Philadelphia
+url <- "https://www2.census.gov/geo/tiger/TIGER2020/AIANNH/tl_2020_us_aiannh.zip"
+temp_file <- tempfile(fileext = ".zip")
+download.file(url, temp_file, mode = "wb")
+unzip(temp_file, exdir = tempdir())
+
+# Read the Shapefile
+shapefile_path <- file.path(tempdir(), "tl_2020_us_aiannh.shp")
+aiannh <- read_sf(shapefile_path)
+
+# Count the number of AIANNH per congressional district
+state_counts <- aiannh %>%
+  group_by(LSAD) %>%
+  summarize(count = n())
+
+print(state_counts[order(-state_counts$count),])
+```
+
+    ## Simple feature collection with 26 features and 2 fields
+    ## Geometry type: GEOMETRY
+    ## Dimension:     XY
+    ## Bounding box:  xmin: -174.236 ymin: 18.91069 xmax: -67.03552 ymax: 71.34019
+    ## Geodetic CRS:  NAD83
+    ## # A tibble: 26 × 3
+    ##    LSAD  count                                                          geometry
+    ##    <chr> <int>                                                <MULTIPOLYGON [°]>
+    ##  1 79      221 (((-166.5331 65.33918, -166.5331 65.33906, -166.533 65.33699, -1…
+    ##  2 86      206 (((-83.38811 35.46645, -83.38342 35.46596, -83.38316 35.46593, -…
+    ##  3 OT      155 (((-92.32972 47.81374, -92.3297 47.81305, -92.32967 47.81196, -9…
+    ##  4 78       75 (((-155.729 20.02457, -155.7288 20.02428, -155.7288 20.02427, -1…
+    ##  5 85       46 (((-122.3355 37.95215, -122.3354 37.95206, -122.3352 37.95199, -…
+    ##  6 92       35 (((-93.01356 31.56287, -93.01354 31.56251, -93.01316 31.56019, -…
+    ##  7 88       25 (((-97.35299 36.908, -97.35291 36.90801, -97.35287 36.908, -97.3…
+    ##  8 96       19 (((-116.48 32.63814, -116.48 32.63718, -116.4794 32.63716, -116.…
+    ##  9 84       16 (((-105.5937 36.40379, -105.5937 36.40324, -105.5937 36.40251, -…
+    ## 10 89       11 (((-95.91705 41.28037, -95.91653 41.28036, -95.91653 41.28125, -…
+    ## # ℹ 16 more rows
+
+Python: In Python, we’ll use the ‘geopandas’ library to read and process
+the Shapefile data.
+
+Python code:
+
+``` python
+import geopandas as gpd
+import pandas as pd
+import requests
+import zipfile
+import os
+from io import BytesIO
+
+# Download historic redlining data for Philadelphia
+url = "https://www2.census.gov/geo/tiger/TIGER2020/AIANNH/tl_2020_us_aiannh.zip"
+response = requests.get(url)
+zip_file = zipfile.ZipFile(BytesIO(response.content))
+
+# Extract Shapefile
+temp_dir = "temp"
+if not os.path.exists(temp_dir):
+    os.makedirs(temp_dir)
+
+zip_file.extractall(path=temp_dir)
+shapefile_path = os.path.join(temp_dir, "tl_2020_us_aiannh.shp")
+
+# Read the Shapefile
+aiannh = gpd.read_file(shapefile_path)
+
+# Count the number of AIANNH per congressional district
+state_counts = aiannh.groupby("LSAD").size().reset_index(name="count")
+
+# Sort by descending count
+state_counts_sorted = state_counts.sort_values(by="count", ascending=False)
+
+print(state_counts_sorted)
+```
+
+    ##    LSAD  count
+    ## 2    79    221
+    ## 9    86    206
+    ## 25   OT    155
+    ## 1    78     75
+    ## 8    85     46
+    ## 15   92     35
+    ## 11   88     25
+    ## 19   96     19
+    ## 7    84     16
+    ## 12   89     11
+    ## 5    82      8
+    ## 3    80      7
+    ## 4    81      6
+    ## 21   98      5
+    ## 20   97      5
+    ## 13   90      4
+    ## 18   95      3
+    ## 6    83      3
+    ## 17   94      2
+    ## 16   93      1
+    ## 14   91      1
+    ## 10   87      1
+    ## 22   99      1
+    ## 23   9C      1
+    ## 24   9D      1
+    ## 0    00      1
+
+In conclusion, both R and Python offer efficient ways to download and
+process AIANNH TIGER/Line Shapefile data from the U.S. Census Bureau.
+The ‘sf’ package in R provides a simple way to read and manipulate
+spatial data, while the ‘geopandas’ library in Python offers similar
+functionality. The ‘dplyr’ package in R can be used for data
+manipulation and analysis, and Python’s built-in functions like
+value_counts() can be used for aggregating data. Depending on your
+preferred programming language and environment, both options can be
+effective for working with AIANNH data.
+
+## Indian Entities Recognized and Eligible To Receive Services by BIA
+
+The Bureau of Indian Affairs (BIA) provides a PDF document containing a
+list of Indian Entities Recognized and Eligible To Receive Services. To
+analyze the data, we’ll first need to extract the information from the
+PDF. In this example, we’ll extract the names of the recognized tribes
+and count the number of tribes per state.
+
+R: In R, we’ll use the ‘pdftools’ package to extract text from the PDF
+and the ‘stringr’ package to process the text data.
+
+R code:
+
+``` r
+# Install and load necessary libraries
+library(pdftools)
+library(stringr)
+library(dplyr)
+
+# Download the BIA PDF
+url <- "https://www.govinfo.gov/content/pkg/FR-2022-01-28/pdf/2022-01789.pdf"
+temp_file <- tempfile(fileext = ".pdf")
+download.file(url, temp_file, mode = "wb")
+
+# Extract text from the PDF
+pdf_text <- pdf_text(temp_file)
+tribe_text <- pdf_text[4:length(pdf_text)]
+
+# Define helper functions
+tribe_state_extractor <- function(text_line) {
+  regex_pattern <- "(.*),\\s+([A-Z]{2})$"
+  tribe_state <- str_match(text_line, regex_pattern)
+  return(tribe_state)
+}
+
+is_valid_tribe_line <- function(text_line) {
+  regex_pattern <- "^\\d+\\s+"
+  return(!is.na(str_match(text_line, regex_pattern)))
+}
+
+# Process text data to extract tribes and states
+tribe_states <- sapply(tribe_text, tribe_state_extractor)
+valid_lines <- sapply(tribe_text, is_valid_tribe_line)
+tribe_states <- tribe_states[valid_lines, 2:3]
+
+# Count the number of tribes per state
+tribe_data <- as.data.frame(tribe_states)
+colnames(tribe_data) <- c("Tribe", "State")
+state_counts <- tribe_data %>%
+  group_by(State) %>%
+  summarise(Count = n())
+
+print(state_counts)
+```
+
+    ## # A tibble: 0 × 2
+    ## # ℹ 2 variables: State <chr>, Count <int>
+
+Python: In Python, we’ll use the ‘PyPDF2’ library to extract text from
+the PDF and the ‘re’ module to process the text data.
+
+Python code:
+
+``` python
+# Install necessary libraries
+import requests
+import PyPDF2
+import io
+import re
+from collections import Counter
+
+# Download the BIA PDF
+url = "https://www.bia.gov/sites/bia.gov/files/assets/public/raca/online-tribal-leaders-directory/tribal_leaders_2021-12-27.pdf"
+response = requests.get(url)
+
+# Extract text from the PDF
+pdf_reader = PyPDF2.PdfFileReader(io.BytesIO(response.content))
+tribe_text = [pdf_reader.getPage(i).extractText() for i in range(3, pdf_reader.numPages)]
+
+# Process text data to extract tribes and states
+tribes = [re.findall(r'^\d+\s+(.+),\s+([A-Z]{2})', line) for text in tribe_text for line in text.split('\n') if line]
+tribe_states = [state for tribe, state in tribes]
+
+# Count the number of tribes per state
+state_counts = Counter(tribe_states)
+print(state_counts)
+```
+
+In conclusion, both R and Python offer efficient ways to download and
+process the list of Indian Entities Recognized and Eligible To Receive
+Services from the BIA. The ‘pdftools’ package in R provides a simple way
+to extract text from PDF files, while the ‘PyPDF2’ library in Python
+offers similar functionality. The ‘stringr’ package in R and the ‘re’
+module in Python can be used to process and analyze text data. Depending
+on your preferred programming language and environment, both options can
+be effective for working with BIA data.
+
+## National Atlas - Indian Lands of the United States dataset
+
+In this example, we will download and analyze the National Atlas -
+Indian Lands of the United States dataset in both R and Python. We will
+read the dataset and count the number of Indian lands per state.
+
+R: In R, we’ll use the ‘sf’ package to read the Shapefile and the
+‘dplyr’ package to process the data.
+
+R code:
+
+``` r
+# Install and load necessary libraries
+
+library(sf)
+library(dplyr)
+
+# Download the Indian Lands dataset
+url <- "https://prd-tnm.s3.amazonaws.com/StagedProducts/Small-scale/data/Boundaries/indlanp010g.shp_nt00968.tar.gz"
+temp_file <- tempfile(fileext = ".tar.gz")
+download.file(url, temp_file, mode = "wb")
+untar(temp_file, exdir = tempdir())
+
+# Read the Shapefile
+shapefile_path <- file.path(tempdir(), "indlanp010g.shp")
+indian_lands <- read_sf(shapefile_path)
+
+# Count the number of Indian lands per state
+# state_counts <- indian_lands %>%
+#   group_by(STATE) %>%
+#   summarize(count = n())
+
+plot(indian_lands)
+```
+
+    ## Warning: plotting the first 9 out of 23 attributes; use max.plot = 23 to plot
+    ## all
+
+![](bilingualism_md_files/figure-gfm/unnamed-chunk-71-1.pdf)<!-- -->
+
+Python: In Python, we’ll use the ‘geopandas’ and ‘pandas’ libraries to
+read the Shapefile and process the data.
+
+Python code:
+
+``` python
+import geopandas as gpd
+import pandas as pd
+import requests
+import tarfile
+import os
+from io import BytesIO
+
+# Download the Indian Lands dataset
+url = "https://prd-tnm.s3.amazonaws.com/StagedProducts/Small-scale/data/Boundaries/indlanp010g.shp_nt00966.tar.gz"
+response = requests.get(url)
+tar_file = tarfile.open(fileobj=BytesIO(response.content), mode='r:gz')
+
+# Extract Shapefile
+temp_dir = "temp"
+if not os.path.exists(temp_dir):
+    os.makedirs(temp_dir)
+
+tar_file.extractall(path=temp_dir)
+shapefile_path = os.path.join(temp_dir, "indlanp010g.shp")
+
+# Read the Shapefile
+indian_lands = gpd.read_file(shapefile_path)
+
+# Count the number of Indian lands per state
+state_counts = indian_lands.groupby("STATE").size().reset_index(name="count")
+
+print(state_counts)
+```
+
+Both R and Python codes download the dataset and read the Shapefile
+using the respective packages. They then group the data by the ‘STATE’
+attribute and calculate the count of Indian lands per state.
diff --git a/docs/resources/citations.md b/docs/resources/citations.md
new file mode 100644
index 0000000..df0c869
--- /dev/null
+++ b/docs/resources/citations.md
@@ -0,0 +1,64 @@
+# Citation Management and Notes Collection in Markdown
+
+## Introduction
+
+This document serves as a guide for managing citations and collecting research notes for our project. We'll use a combination of a `.bib` file for bibliographic references and Markdown for note-taking.
+
+## Part 1: Setting Up Your .bib File for Citations
+
+### Creating a .bib File
+
+1. **Create a new file** with a `.bib` extension, for example, `project_references.bib`.
+2. **Add bibliographic entries** to this file. Each entry should follow the BibTeX format.
+
+### Example of a .bib Entry
+
+```bibtex
+@article{Doe2021,
+  author  = {Jane Doe and John Smith},
+  title   = {Insights into Environmental Data Science},
+  journal = {Journal of Data Science},
+  year    = {2021},
+  volume  = {15},
+  number  = {4},
+  pages   = {123-145},
+  doi     = {10.1000/jds.2021.15.4}
+}
+
+
+
+## Part 2: Using Citations in Markdown
+
+### Citing in Your Markdown Document
+
+- Refer to works in your `.bib` file using citation keys, like `[@Doe2021]`.
+
+### Converting Markdown to PDF with Citations
+
+- Use Pandoc: `pandoc yourdoc.md --bibliography=project_references.bib --citeproc -o output.pdf`
+
+## Part 3: Collecting Citations and Research Notes
+
+### Structuring Your Notes
+
+#### Notes on Doe 2021 `[@Doe2021]`
+
+- **Key Points:**
+  - Summary of the article's main arguments.
+  - Notable methodologies.
+
+- **Relevance to Our Project:**
+  - How this research informs our project.
+  - Applicable methodologies or theories.
+
+#### Notes on Another Article `[@Another2021]`
+
+- **Key Points:**
+  - ...
+
+- **Relevance to Our Project:**
+  - ...
+
+## Conclusion
+
+This document facilitates efficient management of references and collaborative knowledge building for our project.
diff --git a/docs/resources/code-of-conduct.md b/docs/resources/code-of-conduct.md
new file mode 100644
index 0000000..16fd587
--- /dev/null
+++ b/docs/resources/code-of-conduct.md
@@ -0,0 +1,199 @@
+# Code of Conduct and Respectful Inclusive Collaboration Guidelines
+
+CIRES Earth Lab and Environmental Data Science Innovation & Inclusion Lab (ESIIL) are committed to building, maintaining, and fostering an inclusive, kind, collaborative, and diverse transdisciplinary environmental data science community, whose members feel welcome, supported, and safe to contribute ideas and knowledge.
+
+The ESIIL postdoc program will follow all aspects of the ESIIL Code of Conduct (below).
+
+**All community members are responsible for creating this culture, embodying our values, welcoming diverse perspectives and ways of knowing, creating safe inclusive spaces, and conducting ethical science as guided by FAIR (Findable, Accessible, Interoperable, Reusable) and CARE (Collective Benefit, Authority to Control, Responsibility, and Ethics) principles for scientific and Indigenous data management, governance, and stewardship.**
+
+### Our values
+
+ESIIL’s vision is grounded in the conviction that innovation and breakthroughs in environmental data science will be precipitated by a diverse, collaborative, curious, and inclusive research community empowered by open data and infrastructure, cross-sector and community partnerships, team science, and engaged learning.
+
+As such, our core values center people through inclusion, kindness, respect, collaboration, and genuine relationships. They also center innovation, driven by collaborative, cross-sector science and synthesis, open, accessible data and tools, and fun, diverse teams. Finally, they center learning, propelled by curiosity and accessible, inclusive training, and education opportunities.
+
+### When and how to use these guidelines
+
+These guidelines outline behavior expectations for ESIIL community members. Your participation in the ESIIL network is contingent upon following these guidelines in all ESIIL activities, including, but not limited to, participating in meetings, webinars, hackathons, working groups, hosted or funded by ESIIL, as well as email lists and online forums such as GutHub, Slack, and Twitter. These guidelines have been adapted from those of the International Arctic Research Policy Committee, the Geological Society of America, the American Geophysical Union, the University Corporation for Atmospheric Research, The Carpentries, and others. We encourage other organizations to adapt these guidelines for use in their own meetings.
+
+**Note:** Working groups and hackathon/codefest teams are encouraged to discuss these guidelines and what they mean to them, and will have the opportunity to add to them to specifically support and empower their team. Collaborative and behavior commitments complement data use, management, authorship, and access plans that commit to CARE and FAIR principles.
+
+# Behavior Agreements
+
+ESIIL community members are expected to act professionally and respectfully in all activities, such that each person, regardless of gender, gender identity or expression, sexual orientation, disability, physical appearance, age, body size, race, religion, national origin, ethnicity, level of experience, language fluency, political affiliation, veteran status, pregnancy, country of origin, and any other characteristic protected under state or federal law, feels safe and welcome in our activities and community. We gain strength from diversity and actively seek participation from those who enhance it.
+
+In order to garner the benefits of a diverse community and to reach the full potential of our mission and charge, ESIIL participants must be allowed to develop a sense of belonging and trust within a respectful, inclusive, and collaborative culture. Guiding behaviors that contribute to this culture include, but are not limited to:
+
+## Showing Respect
+
+- **Listen carefully** – we each bring our own styles of communication, language, and ideas, and we must do our best to accept and accommodate differences. Do not interrupt when someone is speaking and maintain an open mind when others have different ideas than yours.
+
+- **Be present** – when engaging with others, give them your full attention. If you need to respond to outside needs, please step away from the group quietly.
+
+- **Be kind** – offer positive, supportive comments and constructive feedback. Critique ideas, not people. Harassment, discrimination, bullying, aggression, including offensive comments, jokes, and imagery, are unacceptable, regardless of intent, and will not be tolerated.
+
+- **Be punctual** - adhere to the schedule provided by the organizers and avoid disruptive behavior during presentations, trainings, or working sessions.
+
+- **Respect privacy** - be mindful of the confidentiality of others. Always obtain explicit consent before recording, sharing, or using someone else’s personal information, photos, or recordings.
+
+- **Practice good digital etiquette (netiquette)** when communicating online, whether in emails, messages, or social media - think before posting online and consider the potential impact on others. Do not share or distribute content generated by or involving others without their explicit consent.
+
+## Being Inclusive
+
+- **Create space for everyone to participate** – be thoughtful about who is at the table; openly address accessibility needs, and provide multiple ways to contribute.
+
+- **Be welcoming** – ESIIL participants come from a wide range of skill levels and career stages, backgrounds, and cultures. Demonstrate that you value these different perspectives and identities through your words and actions, including through correct use of names, titles, and pronouns.
+
+- **Be self-aware** – recognize that positionality, identity, unconscious biases, and upbringing can all affect how words and behaviors are perceived. Ensure that your words and behavior make others feel welcome.
+
+- **Commit to ongoing learning** – the move toward inclusive, equitable, and just environmental data science is a collective journey. Continue to learn about and apply practices of inclusion, anti-racism, bystander intervention, and cultural sensitivity. None of us is perfect; all of us will, from time to time, fail to live up to our own high standards. Being perfect is not what matters; owning our mistakes and committing to clear and persistent efforts to grow and improve is.
+
+# Being Curious
+
+- **Check your presumptions** – we each bring our own ideas and assumptions about how the world should and does work – what are yours, and how do they affect how you interact with others? How do they shape your perception of new ideas?
+
+- **Ask questions** – one of the strengths of interdisciplinary and diverse teams is that we all bring different knowledge and viewpoints; no one person is expected to know everything. So don’t be afraid to ask, to learn, and to share.
+
+- **Be bold** – significant innovations don’t come from incremental efforts. Be brave in proposing and testing new ideas. When things don’t work, learn from the experience.
+
+- **Invite feedback** – new ideas and improvements can emerge from many places when we’re open to hearing them. Check your defensiveness and listen; accept feedback as a gift toward improving our work and ourselves.
+
+## Being Collaborative
+
+- **Recognize that everyone is bringing something different to the table** – take the time to get to know each other. Keep an open mind, encourage ideas that are different from yours, and learn from each other’s expertise and experience.
+
+- **Be accountable** - great team science depends on trust, communication, respect, and delivering on your commitments. Be clear about your needs, as both a requester and a responder, realistic about your time and capacity commitments, and communicate timelines and standards in advance.
+
+- **Make assumptions explicit and provide context wherever possible** - misunderstandings are common on transdisciplinary and cross-cultural teams and can best be managed with intentionality. Check in about assumptions, and be willing to share and correct misunderstandings or mistakes when they happen. Make use of collaboration agreements, communicate clearly and avoid jargon wherever possible.
+
+- **Respect intellectual property and Indigenous data sovereignty** – ESIIL recognizes the extractive and abusive history of scientific engagement with Native peoples, and is committed to doing better. Indigenous knowledge holders are under no obligation to share their data, stories or knowledge. Their work should always be credited, and only shared with permission. Follow guidelines for authorship, Indigenous data sovereignty, and CARE principles. Acknowledge and credit the ideas and work of others.
+
+- **Use the resources that we provide** - take advantage of the cyberinfrastructure and data cube at your disposal, but do not use them for unrelated tasks, as it could disrupt the event, introduce security risks, undermine the spirit of collaboration and fair play, and erode trust within the event community.
+
+- **Be safe** - never share sensitive personal information; use strong passwords for your Cyverse and GitHub accounts and do not share them with other participants; be cautious of unsolicited emails, messages, or links; and verify online contacts. If you encounter any illegal or harmful activities online related to this event, report them to Tyler McIntosh or Susan Sullivan.
+
+**Finally, speak up if you experience or notice a dangerous situation, or someone in distress!**
+
+# Code of Conduct: Unacceptable behaviors
+
+We adopt the full Code of Conduct of our home institution, the University of Colorado, details of which are found [here](#). To summarize, examples of unacceptable and reportable behaviors include, but are not limited to:
+
+- Harassment, intimidation, or discrimination in any form
+- Physical or verbal abuse by anyone to anyone, including but not limited to a participant, member of the public, guest, member of any institution or sponsor
+- Unwelcome sexual attention or advances
+- Personal attacks directed at other guests, members, participants, etc.
+- Alarming, intimidating, threatening, or hostile comments or conduct
+- Inappropriate use of nudity and/or sexual images in public spaces or in presentations
+- Threatening or stalking anyone
+- Unauthorized use or sharing of personal or confidential information or private communication
+- Continuing interactions, including but not limited to conversations, photographies, recordings, instant messages, and emails, after being asked to stop
+- Ethical and scientific misconduct, including failing to credit contributions or respect intellectual property
+- Engaging in any illegal activities, including hacking, cheating, or unauthorized access to systems or data
+- Using the cyberinfrastructure provided by the organizers for activities unrelated to this event.
+- Other conduct which could reasonably be considered inappropriate in a professional setting. 
+
+The University of Colorado recognizes all Federal and State protected classes, which include the following: race, color, national origin, sex, pregnancy, age, marital status, disability, creed, religion, sexual orientation, gender identity, gender expression, veteran status, political affiliation or political philosophy. Mistreatment or harassment not related to protected class also has a negative impact and will be addressed by the ESIIL team.
+
+Anyone requested to stop unacceptable behavior is expected to comply immediately.
+
+If there is a clear violation of the code of conduct during an ESIIL event—for example, a meeting is Zoom bombed or a team member is verbally abusing another participant during a workshop— ESIIL leaders, facilitators (or their designee) or campus/local police may take any action deemed necessary and appropriate, including expelling the violator, or immediate removal of the violator from any online or in-person event or platform without warning or refund. If such actions are necessary, there will be follow up with the ESIIL Diversity Equity and Inclusion (DEI) team to determine what further action is needed (see Reporting Process and Consequences below).
+
+## Addressing Behavior Directly
+
+For smaller incidents that might be settled with a brief conversation, you may choose to contact the person in question or set up a (video) conversation to discuss how the behavior affected you. Please use this approach only if you feel comfortable; you do not have to carry the weight of addressing these issues yourself. If you are interested in this option but unsure how to go about it, please contact the ESIIL DEI lead, Susan Sullivan, first—she will have advice on how to make the conversation happen and is available to join you in a conversation as requested.
+
+# Reporting Process and Consequences
+
+We take any reports of Code of Conduct violations seriously, and aim to support those who are impacted and ensure that problematic behavior doesn’t happen again.
+
+## Making a Report
+
+If you believe you’re experiencing or have experienced unacceptable behavior that is counter to this code of conduct, or you are witness to this behavior happening to someone else, we encourage you to contact our DEI lead:
+
+- **Susan Sullivan, CIRES**
+  - Email: [susan.sullivan@colorado.edu](mailto:susan.sullivan@colorado.edu)
+
+You may also choose to anonymously report behavior to ESIIL using [this form](#).
+
+The DEI team will keep reports as confidential as possible. However, as mandatory reporters, we have an obligation to report alleged protected class violations to our home institution or to law enforcement.
+
+### Specifically:
+
+- Cases of potential protected-class harassment will be reported to the CU Office of Institutional Equity and Compliance.
+- If the violation is made by a member of another institution, that information may also be shared with that member’s home institution by the CU Office of Institutional Equity and Compliance under Title IX.
+- In some instances, harassment information may be shared with the National Science Foundation, who are the funding organization of ESIIL.
+
+When we discuss incidents with people who are accused of misconduct (the respondent), we will anonymize details as much as possible to protect the privacy of the reporter and the person who was impacted (the complainant). In some cases, even when the details are anonymized, the respondent may guess at the identities of the reporter and complainants. If you have concerns about retaliation or your personal safety, please let us know (or note that in your report). We encourage you to report in any case, so that we can support you while keeping ESIIL members safe. In some cases, we are able to compile several anonymized reports into a pattern of behavior, and take action based on that pattern.
+
+If you prefer to speak with someone who is not on the ESIIL leadership team, or who can maintain confidentiality, you may contact:
+
+- **CU Ombuds**
+  - Phone: 303-492-5077 (for guidance and support navigating difficult conversations)
+- **CU Office of Victim Assistance**
+  - Phone: 303-492-8855 
+
+If you want more information about when to report, or how to help someone who needs to report, please review the resources at [Don’t Ignore It](#).
+
+**Note:** The reporting party does not need to be directly involved in a code of conduct violation incident. Please make a bystander report if you observe a potentially dangerous situation, someone in distress, or violations of these guidelines, even if the situation is not happening to you.
+
+# What Happens After a Report Is Filed
+
+After a member of the ESIIL DEI team takes your report, they will (if necessary) consult with the appropriate support people at CU. The ESIIL DEI team will respond with a status update within 5 business days.
+
+During this time, they, or members of the CU Office of Institutional Equity and Compliance, will:
+
+- Meet with you or review report documentation to determine what happened
+- Consult documentation of past incidents for patterns of behavior
+- Discuss appropriate response(s) to the incident
+- Connect with the appropriate offices and/or make those response(s)
+- Determine the follow-up actions for any impacted people and/or the reporter
+- Follow up with the impacted people, including connecting them with support and resources.
+
+## As a result of this process, in minor cases ESIIL DEI may communicate with the respondent to:
+
+- Explain what happened and the impact of their behavior
+- Offer concrete examples of how to improve their behavior
+- Explain consequences of their behavior, or future consequences if the behavior is repeated.
+
+For significant infractions, follow up to the report may be turned over to the CU Office of Institutional Equity and Compliance and/or campus police.
+
+## Possible Consequences to Code of Conduct Violations
+
+What follows are examples of possible responses to an incident report. This list is not inclusive, and ESIIL reserves the right to take any action it deems necessary. Generally speaking, the strongest response ESIIL may take is to completely ban a user from further engagement with ESIIL activities and, as is required, report a person to the CU Office of Institutional Equity and Compliance and/or their home institution and NSF. If law enforcement should be involved, they will recommend that the complainant make that contact. Employees of CU Boulder may also be subject to consequences as determined by the institution.
+
+In addition to the responses above, ESIIL responses may include but are not limited to the following:
+
+- A verbal discussion in person or via phone/Zoom followed by documentation of the conversation via email
+- Not publishing the video or slides of a talk that violated the code of conduct
+- Not allowing a speaker who violated the code of conduct to give (further) talks
+- Immediately ending any team leadership, membership, or other responsibilities and privileges that a person holds
+- Temporarily banning a person from ESIIL activities
+- Permanently banning a person from ESIIL activities
+- Nothing, if the behavior is determined to not be a code of conduct violation
+
+Do you need more resources?
+
+Please don’t hesitate to contact the ESIIL DEI lead, Susan Sullivan, if you have questions or
+concerns.
+
+The CU Office of Institutional Equity and Compliance is a resource for all of us in navigating this space. They also offer resource materials that can assist you in exploring various topics and skills here.
+
+If you have questions about what, when or how to report, or how to help someone else with
+concerns, Don’t Ignore It.
+
+CU Ombud’s Office: Confidential support to navigate university situations. (Most universities
+have these resources)
+
+The CU Office of Victims Assistance (counseling limited to CU students/staff/faculty, though
+advocacy is open to everyone engaged with a CU-sponsored activity. Please look for a similar resource on your campus if you are from another institution).
+
+National Crisis Hotlines
+
+How are we doing?
+
+Despite our best intentions, in some cases we may not be living up to our ideals of a positive,
+supportive, inclusive, respectful and collaborative community. If you feel we could do better, we welcome your feedback. Comments, suggestions and praise are also very welcome!
+Acknowledgment
+By participating in this event, you agree to abide by this code of conduct and understand the consequences of violating it. We believe that a respectful and inclusive environment benefits all participants and leads to more creative and successful outcomes.
+Thank you for your cooperation in making the this event a welcoming event for all. Have fun!
+
diff --git a/docs/resources/cyverse_basics.md b/docs/resources/cyverse_basics.md
new file mode 100644
index 0000000..6b5d7bd
--- /dev/null
+++ b/docs/resources/cyverse_basics.md
@@ -0,0 +1,91 @@
+# Connecting Cyverse to GitHub
+
+## Log in to Cyverse
+
+1. Go to the Cyverse user account website [https://user.cyverse.org/](https://user.cyverse.org/)
+
+<img width="881" alt="image" src="https://github.com/CU-ESIIL/hackathon2023_datacube/assets/3465768/61b8c22a-bed3-457a-b603-736fd8e59568">
+
+2. Click `Sign up` (if you do not already have an account)
+
+   <img width="881" alt="image" src="https://github.com/CU-ESIIL/hackathon2023_datacube/assets/3465768/73dc39a4-30f2-4017-8f0d-1006db24d25b">
+
+3. Head over to the Cyverse Discovery Environment [https://de.cyverse.org](https://de.cyverse.org), and log in with your new account.
+
+   <img width="881" alt="image" src="https://github.com/CU-ESIIL/hackathon2023_datacube/assets/3465768/41970a8d-c434-4075-9dd4-fbcd0f2ea07c">
+
+   You should now see the Discovery Environment:
+
+   <img width="881" alt="image" src="https://github.com/CU-ESIIL/hackathon2023_datacube/assets/3465768/0dcd0048-a4e3-469c-bd28-5a5574c5dec3">
+
+4. We will give you permissions to access the Hackathon app. If you haven't already, let us know that you need access
+
+## Open up an analysis with the hackathon environment (Jupyter Lab)
+
+1. From the Cyverse Discovery Environment, click on `Apps` in the left menu
+   ![apps](../assets/cyverse_basics/apps.png)
+
+2. Select `JupyterLab ESIIL`
+   ![use_this_app](../assets/cyverse_basics/use_this_app.png)
+
+3. Configure and launch your analysis - when choosing the disk size, make sure to choose 64GB or greater. The rest of the settings you can change to suit your computing needs:
+   ![app_launch](../assets/cyverse_basics/app_launch.png)
+
+   ![app_settings](../assets/cyverse_basics/app_settings.png)
+
+   ![launch](../assets/cyverse_basics/launch.png)
+
+4. Click `Go to analysis`:
+   ![go_to_analysis](../assets/cyverse_basics/go_to_analysis.png)
+
+5. Now you should see Jupyter Lab!
+   ![jupyterlab](../assets/cyverse_basics/jupyterlab.png)
+
+## Set up your GitHub credentials
+
+### If you would prefer to follow a video instead of a written outline, we have prepared a video here:
+<a href="https://www.youtube.com/watch?v=nOwOzPJEQbU">
+    <img src="https://img.youtube.com/vi/nOwOzPJEQbU/0.jpg" style="width: 100%;">
+</a>
+
+1. From Jupyter Lab, click on the Git Extension icon on the left menu:
+   ![jupyterlab](../assets/cyverse_basics/jupyterlab.png)
+
+2. Click `Clone a Repository` and Paste the link to the cyverse-utils [https://github.com/CU-ESIIL/cyverse-utils.git](https://github.com/CU-ESIIL/cyverse-utils.git) and click `Clone`:
+   ![clone](../assets/cyverse_basics/clone.png)
+   
+3. You should now see the `cyverse-utils` folder in your directory tree (provided you haven't changed directories from the default `/home/jovyan/data-store`
+   ![cyverse-utils](../assets/cyverse_basics/cyverse-utils.png)
+
+4. Go into the `cyverse-utils` folder:
+   ![click_cyverse_utils](../assets/cyverse_basics/click_cyverse_utils.png)
+
+5. open up the `create_github_keypair.ipynb` notebook if you prefer Python or the 'create_github_keypair.R' script if you prefer R by double-clicking and then select the default 'macrosystems' kernel:
+![open_cyverse_utils](../assets/cyverse_basics/open_cyverse_utils.png)
+
+6. Now you should see the notebook open. Click the `play` button at the top. You will be prompted to enter your GitHub username and email:
+   ![script_1](../assets/cyverse_basics/script_1.png)
+
+   ![username](../assets/cyverse_basics/username.png)
+
+   ![email](../assets/cyverse_basics/email.png)
+
+7. You should now see your Public Key. Copy the WHOLE LINE including `ssh-ed25519` at the beginning and the `jovyan@...` at the end
+![key](../assets/cyverse_basics/key.png)
+
+8. Go to your GitHub settings page (you may need to log in to GitHub first):
+   ![settings](../assets/cyverse_basics/settings.png)
+
+9. Select `SSH and GPG keys`
+   ![ssh](../assets/cyverse_basics/ssh.png)
+
+10. Select `New SSH key`
+   ![new_key](../assets/cyverse_basics/new_key.png)
+
+11. Give your key a descriptive name, paste your ENTIRE public key in the `Key` input box, and click `Add SSH Key`. You may need to re-authenticate with your password or two-factor authentication.:
+   ![paste_key](../assets/cyverse_basics/paste_key.png)
+
+12. You should now see your new SSH key in your `Authentication Keys` list! Now you will be able to clone private repositories and push changes to GitHub from your Cyverse analysis!
+   ![final](../assets/cyverse_basics/final.png)
+
+> NOTE! Your GitHub authentication is ONLY for the analysis you're working with right now. You will be able to use it as long as you want there, but once you start a new analysis you will need to go through this process again. Feel free to delete keys from old analyses that have been shut down.
diff --git a/docs/resources/cyverse_hacks.md b/docs/resources/cyverse_hacks.md
new file mode 100644
index 0000000..7a99f61
--- /dev/null
+++ b/docs/resources/cyverse_hacks.md
@@ -0,0 +1,36 @@
+# Transitioning Workflows to CyVerse: A Guide for ESIIL Postdocs
+
+## Earth Lab Data Storage
+- **Path:** `/home/jovyan/data-store/iplant/home/shared/earthlab/`
+- Ensure your project has a directory within the Earth Lab data storage.
+
+## Setup
+1. **CyVerse Account:**
+   - Create an account if not already owned.
+   - Contact Tyson for account upgrades after maximizing current limits.
+
+## GitHub Connection
+- Follow Elsa Culler's guide for connecting GitHub to CyVerse.
+- Select “JupyterLab ESIIL” and choose “macrosystems” in the version dropdown.
+- Clone into `/home/jovyan/data-store`.
+- Clone `innovation-summit-utils` for SSH connection to GitHub.
+- Run `conda install -c conda-forge openssh` in the terminal if encountering errors.
+- GitHub authentication is session-specific.
+
+## RStudio in DE
+1. Copy your instance ID. It can be found in your analyis URL in form https://<instance_id>.cyverse.run/lab.
+2. Use your ID in these links:  
+   - `https://<id>.cyverse.run/rstudio/auth-sign-in` 
+   - `https://<id>.cyverse.run/rstudio/` 
+
+## Package Requests
+- List desired packages here for future container updates.
+
+## Data Transfer to CyVerse
+- Use GoCommands for HPC/CyVerse transfers.
+- **Installation:**
+  - **Linux:** (Command)
+  - **Windows Powershell:** (Command)
+- **Usage:** 
+  - Use `put` for upload and `get` for download.
+  - Ensure correct CyVerse directory path.
diff --git a/docs/resources/data_analysis.md b/docs/resources/data_analysis.md
new file mode 100644
index 0000000..effdfe3
--- /dev/null
+++ b/docs/resources/data_analysis.md
@@ -0,0 +1,36 @@
+# Data Analysis Documentation
+
+## Overview
+Brief overview of the data analysis goals and the analytical questions being addressed.
+
+## Analysis Methodology
+Description of the analytical approach, methods used, and justification for the chosen techniques.
+
+## Code Overview
+Explanation of the structure of the analysis code, including key functions and their roles.
+
+## Running the Analysis
+Instructions and example commands for executing the analysis scripts.
+```bash
+python analysis_script.py
+```
+
+## Analysis Results
+
+Summary of key findings from the analysis, including interpretation and relevance.
+
+## Challenges and Solutions
+
+Discussion of challenges faced during the analysis and solutions or workarounds implemented.
+
+## Conclusions
+
+Concluding remarks on the analysis, insights gained, and their potential impact.
+
+## Future Work
+
+Suggestions for extending or refining the analysis and potential areas for further research.
+
+## References
+
+Citations or references to external sources or literature used.
\ No newline at end of file
diff --git a/docs/resources/data_processing.md b/docs/resources/data_processing.md
new file mode 100644
index 0000000..ebc29dc
--- /dev/null
+++ b/docs/resources/data_processing.md
@@ -0,0 +1,41 @@
+# Data Processing Documentation
+
+## Overview
+Brief description of the data processing objectives and scope. Reminder to adhere to data ownership and usage guidelines.
+
+## Data Sources
+List and describe data sources used, including links to cloud-optimized sources. Highlight permissions and compliance with data ownership guidelines.
+
+## CyVerse Discovery Environment
+Instructions for setting up and using the CyVerse Discovery Environment for data processing. Tips for cloud-based data access and processing.
+
+## Data Processing Steps
+
+### Using GDAL VSI
+Guidance on using GDAL VSI (Virtual System Interface) for data access and processing. Example commands or scripts:
+```bash
+gdal_translate /vsicurl/http://example.com/data.tif output.tif
+```
+
+## Cloud-Optimized Data
+Advantages of using cloud-optimized data formats and processing data without downloading. Instructions for such processes.
+
+## Data Storage
+
+Information on storing processed data, with guidelines for choosing between the repository and CyVerse Data Store.
+
+## Best Practices
+
+Recommendations for efficient and responsible data processing in the cloud. Tips to ensure data integrity and reproducibility.
+
+## Challenges and Troubleshooting
+
+Common challenges in data processing and potential solutions. Resources for troubleshooting in the CyVerse Discovery Environment.
+
+## Conclusions
+
+Summary of the data processing phase and its outcomes. Reflect on the methods used.
+
+## References
+
+Citations of tools, data sources, and other references used in the data processing phase.
\ No newline at end of file
diff --git a/docs/resources/docker_basics.md b/docs/resources/docker_basics.md
new file mode 100644
index 0000000..117203b
--- /dev/null
+++ b/docs/resources/docker_basics.md
@@ -0,0 +1,276 @@
+# Docker Basics
+
+## What is Docker?
+
+Docker is a containerization platform that enables you to package your applications along with their dependencies into self-contained units called containers.
+Containers provide a consistent and portable runtime environment, making it easy to develop, test, and deploy applications across different machines.
+
+## Key Concepts
+
+### Images
+A blueprint for a Docker container. Images are read-only and contain all the necessary code, libraries, and configurations for an application.
+
+### Containers
+A running instance of a Docker image. Containers are isolated from each other and the host system.
+
+### Dockerfile
+A text file that defines the instructions needed to build a Docker image.
+
+## Building a jupyterlab Docker Image using GitHub Actions
+
+### Create a Dockerfile
+Create a new directory and Dockerfile within the project docker directory. Since this will be jupyterlab image, we will call the directory jupyterlab.
+```bash
+FROM jupyter/r-notebook:hub-4.0.1 
+
+USER root
+
+# Set up package manager
+RUN apt-get install -y apt-transport-https && \
+    apt-get clean && apt-get update && apt-get install -y software-properties-common && \
+    add-apt-repository multiverse && \
+    apt-get clean && rm -rf /var/lib/apt/lists/*
+
+# Install some base software
+RUN apt-get update --yes && \
+    apt-get install --yes \
+    fonts-dejavu \
+    unixodbc \
+    unixodbc-dev \
+    r-base \
+    r-cran-rodbc && \
+    apt-get clean && rm -rf /var/lib/apt/lists/*
+
+# Add sudo to jovyan user
+RUN apt update && \
+    apt install -y sudo && \
+    apt clean && \
+    rm -rf /var/lib/apt/lists/*
+    
+# This is where we can control which root permissions the jovyan user will have
+ARG PRIV_CMDS='/bin/ch*,/bin/cat,/bin/gunzip,/bin/tar,/bin/mkdir,/bin/ps,/bin/mv,/bin/cp,/usr/bin/apt*,/usr/bin/pip*,/bin/yum,/opt,/opt/conda/bin/*,/usr/bin/*'
+
+RUN usermod -aG sudo jovyan && \
+    echo "$LOCAL_USER ALL=NOPASSWD: $PRIV_CMDS" >> /etc/sudoers
+RUN addgroup jovyan
+RUN usermod -aG jovyan jovyan
+
+# Install RStudio
+RUN apt-get update && apt-get install --yes gdebi-core && \
+    wget https://download2.rstudio.org/server/jammy/amd64/rstudio-server-2023.09.1-494-amd64.deb && \
+    gdebi -n rstudio-server-2023.09.1-494-amd64.deb && \
+    rm rstudio-server-2023.09.1-494-amd64.deb && \
+    apt-get clean && rm -rf /var/lib/apt/lists/*
+
+# Install Geospatial libraries
+RUN apt-get update && \
+    apt install -y \
+    gdal-bin \
+    lbzip2 \
+    libfftw3-dev \
+    libgdal-dev \
+    libgeos-dev \
+    libgsl0-dev \
+    libgl1-mesa-dev \
+    libglu1-mesa-dev \
+    libhdf4-alt-dev \
+    libhdf5-dev \
+    libjq-dev \
+    libpq-dev \
+    libproj-dev \
+    libprotobuf-dev \
+    libnetcdf-dev \
+    libsqlite3-dev \
+    libudunits2-dev \
+    lsb-release \
+    netcdf-bin \
+    postgis \
+    protobuf-compiler \
+    sqlite3 \
+    tk-dev \
+    libfmt-dev \
+    unixodbc-dev && \
+    apt-get clean && rm -rf /var/lib/apt/lists/*
+
+# Fix RStudio / Conda openssl version mismatch
+RUN wget https://www.openssl.org/source/openssl-3.2.0.tar.gz && \
+    tar xfz openssl-3.2.0.tar.gz && \
+    mkdir openssl-build && cd openssl-build && \
+    ../openssl-3.2.0/Configure --libdir=/lib/x86_64-linux-gnu/ && \
+    make && \
+    make install
+
+# Update permissions for /opt/conda
+RUN mkdir /usr/local/bin/start-notebook.d && \
+    chown -R jovyan:users /opt/conda/share /usr/local/share /usr/local/bin/start-notebook.d 
+
+USER jovyan
+
+# Install jupyterlab and rstudio dependencies
+RUN conda install -c conda-forge \ 
+    jupyter_client \ 
+    jupyter_core \ 
+    jupyterlab_server \ 
+    jupyter_server \
+    r-rgl \
+    r-htmlwidgets \
+    r-htmltools && \ 
+    jupyter lab clean
+
+# reinstall R packages. Here is where you add any new R packages you would like to install 
+RUN mamba install --quiet --yes \
+    r-base \
+    r-tidyverse \
+    r-terra \
+    r-future \
+    r-future.apply \
+    r-furrr \
+    && \ 
+    mamba clean --all -f -y
+
+# Install Jupyter Lab Proxy extensions (cards in Launcher)
+RUN pip install jupyter-rsession-proxy jupyter-server-proxy jupyter-shiny-proxy jupyterlab-git 
+
+# Install Mamba Gator package manager
+RUN rm -f ~/.jupyter/lab/workspaces/default* && \
+    mamba install -y -c conda-forge mamba_gator
+
+# Install and configure jupyter lab 
+COPY jupyter_notebook_config.json /opt/conda/etc/jupyter/jupyter_notebook_config.json
+
+# Rebuild the Jupyter Lab with new tools
+RUN jupyter lab build
+
+# Build Conda environment. Any packages you would like to install with conda need to be added to the environment.yml file in this Dockerfiles directory
+RUN conda update -y conda && \
+    conda config --remove channels conda-forge && \
+    conda config --add channels conda-forge
+WORKDIR /home/jovyan
+COPY environment.yml /home/jovyan/ 
+RUN mamba env create -f /home/jovyan/environment.yml
+RUN . /opt/conda/etc/profile.d/conda.sh && conda deactivate && conda activate custom && python -m ipykernel install --name custom && pip install jupyter_contrib_nbextensions
+
+# Install R packages from CRAN and GitHub
+RUN R -e "remotes::install_github('tomroh/ecoregions')"
+RUN R -e "install.packages('mblm', repos='http://cran.rstudio.com/')"
+
+# Set any required environment variables 
+ENV PROJ_LIB=/opt/conda/envs/custom/share/proj
+RUN echo "PROJ_LIB=/opt/conda/envs/custom/share/proj" > /home/jovyan/.Renviron
+```
+There are many things going on in the Dockerfile above. Most of the lines, however, are just Linux commands you would run from a terminal when provisioning a new VM. Each block of code is commented with what it accomplishes.
+
+### Add any necessary files
+The Dockerfile above uses a file called environment.yml to provision the its conda environment and a jupyter_config_notebook.json file to configure the jupyterlab server. Both of these files will need to be added to the docker/jupyterlab directory at the same level as the Dockerfile. You can view the content of these files in this repository.
+
+### Create the GitHub actions workflow file
+Workflow files specify when and how code is executed in a GitHub Actions workflow. Actions can be triggered automatically, such as when a commit is pushed to a repo or a specific file, or they can be triggered manually. The following workflow is defined so that the Action is triggered manually. Actions can also be run on different VM types. The following Action will be run on the latest Ubuntu image. 
+
+```bash
+name: build-and-push-jupyterlab-image
+
+on:
+  workflow_dispatch:  # This allows you to manually trigger the action from GitHub UI.
+
+jobs:
+  
+  build:
+    runs-on: ubuntu-latest
+    
+    steps:
+    
+      - name: Checkout
+        uses: actions/checkout@v3.5.0
+      
+      - name: Set up Docker Buildx
+        id: buildx
+        uses: docker/setup-buildx-action@v2.5.0
+            
+      - name: Login to dockerhub 
+        uses: docker/login-action@v2.1.0
+        with:
+          username: ${{ secrets.DOCKERHUB_USERNAME }}
+          password: ${{ secrets.DOCKERHUB_PASSWORD }}
+
+      - name: Get lowercase repo name (for dynamic tags)
+        id: repo_name  
+        run: |
+          lowercase_name=$(echo ${{ github.event.repository.name }} | tr '[:upper:]' '[:lower:]')
+          echo "::set-output name=repo_name::${lowercase_name}"
+        
+      - name: Build and push latest
+        id: docker_build_jupyterlab
+        uses: docker/build-push-action@v4.0.0
+        with:
+          context: docker/jupyterlab
+          file: docker/jupyterlab/Dockerfile
+          builder: ${{ steps.buildx.outputs.name }}
+          push: true
+          tags: |
+            esiil/${{ steps.repo_name.outputs.repo_name }}_jupyterlab:latest
+     
+      - name: Image digest
+        run: echo ${{ steps.docker_build.outputs.digest }}
+```
+
+The steps section of the file defines what will be run by the Action. An overview of the steps of this file is as follows: Checkout the repository code, setup Docker buildx, login to DockerHub, resolve the name of the current GitHub reposiroy, build and push the Docker Image to DockerHub.
+
+### Running the Action
+From your repositories GitHub page, click on the Actions tab 
+![Actions](../assets/docker_basics/actions.png)
+
+Find the workflow in the Workflow navigation menu and click on it
+![Workflows](../assets/docker_basics/workflows.png)
+
+Click on the run workflow dropdown and click Run Workflow
+![RunWorkflow](../assets/docker_basics/run_workflow.png)
+
+## Deploying the Image on CyVerse
+First go to de.cyverse.org and login. From there go to the Apps dashboard and click on Manage Tools.
+
+![ManageTools](../assets/docker_basics/manage_tools.png)
+
+### Adding the Image as a Tool
+Then click Add Tool.
+
+![AddTool](../assets/docker_basics/add_tool.png)
+
+Give the Tool a descriptive name and set the initial version. The version can be whatever you like but 1.0 makes the most sense.
+
+![ToolName](../assets/docker_basics/tool_name.png)
+
+Set the Image Name to esiil/name_of_your_image and the tag to whichever tag you would like the Tool to use. Most Tools will use the latest tag.
+
+![ImageName](../assets/docker_basics/image_name.png)
+
+You can see all of this information on the ESIIL dockerhub page.
+
+![DockerHub](../assets/docker_basics/dockerhub.png)
+
+Leave the Entrypoint blank, and set the working directory to /home/jovyan/data-store and the UID to 1000. Add container port 8888. This will mount and give you access to the cyverse data store. Because the file explorer GUI will not let you go above the working directory that is set, you will have to use the terminal to go up one directory and copy over any files you included in your container.
+
+![ContainerPort](../assets/docker_basics/container_port.png)
+
+Leave all of the restrictions blank and then save the Tool
+
+![Restrictions](../assets/docker_basics/restrictions.png)
+
+### Associating the Tool with an App
+Go back to the Apps dashboard and click create
+
+![CreateApp](../assets/docker_basics/create_app.png)
+
+Just like for the Tool, give a descriptive name and description
+
+![AppName](../assets/docker_basics/app_name.png)
+
+For "Tool used" click select and then search for the name of the tool that was just added and then click on its row and then select at the bottom.
+
+![ToolSearch](../assets/docker_basics/tool_search.png)
+
+From the app creation screen click Next, and then click next through the next steps until you get to completion. From there click Save and Launch
+
+![SaveandLaunch](../assets/docker_basics/save_and_launch.png)
+
+From there you can go through the deployment of your app like you would deploy any other app on CyVerse and test it out.
+
diff --git a/docs/resources/first_meeting_notes.md b/docs/resources/first_meeting_notes.md
new file mode 100644
index 0000000..b4e16b0
--- /dev/null
+++ b/docs/resources/first_meeting_notes.md
@@ -0,0 +1,89 @@
+# Primary Meeting 1
+
+# Day 1-5: Project Kickoff and Strategy
+
+## Meeting Details
+- **Dates:**
+- **Times:**
+- **Location:**
+- **Facilitator:**
+
+## Attendees
+- List of attendees
+
+## Daily Agenda
+
+### Day 1: Setting the Stage
+
+#### Opening Remarks
+- Welcoming speech and outline of the week's objectives.
+
+#### Project Overview
+- Presentation of the project goals and significance.
+
+#### Theoretical Framework
+- Discussion on the theoretical underpinnings of the project.
+
+#### Data Overview
+- Review available data and any gaps that need addressing.
+
+### Day 2-4: Deep Dives
+
+#### Daily Goals
+- Outline specific goals for each day.
+
+#### Task Assignments
+- Assign tasks and areas of responsibility to team members.
+
+#### Theory and Data Synthesis
+- Host focused discussions on how theory will inform data analysis.
+- Explore different methodological approaches and data integration strategies.
+
+#### Evening Social and Soft Work Sessions
+- Casual gatherings to further discuss ideas and foster team bonding.
+
+### Day 5: Roadmap and Closure
+
+#### Project Roadmap
+- Draft a detailed plan of action for the project going forward.
+
+#### Responsibilities
+- Confirm individual responsibilities and deadlines.
+
+#### Review and Feedback
+- Reflect on the week's discussions and adjust the project plan as needed.
+
+#### Closing Remarks
+- Summarize achievements and express appreciation for the team's efforts.
+
+## Detailed Notes
+
+### Day 1 Notes
+- Summary of discussions, decisions, and key points.
+
+### Day 2 Notes
+- ...
+
+### Day 3 Notes
+- ...
+
+### Day 4 Notes
+- ...
+
+### Day 5 Notes
+- ...
+
+## Action Items
+- [ ] Specific task: Assigned to - Deadline
+- [ ] Specific task: Assigned to - Deadline
+- ...
+
+## Reflections and Comments
+- (Space for any additional thoughts, insights, or personal reflections on the meeting.)
+
+## Next Steps
+- Schedule for follow-up meetings or checkpoints.
+- Outline of expected progress before the next primary meeting.
+
+## Additional Documentation
+- (Include or link to any additional documents, charts, or resources that were created or referenced during the meeting.)
diff --git a/docs/resources/github_basics.md b/docs/resources/github_basics.md
new file mode 100644
index 0000000..146a4b6
--- /dev/null
+++ b/docs/resources/github_basics.md
@@ -0,0 +1,418 @@
+Github essentials
+================
+
+## I. Introduction (2 minutes)
+
+### A. Brief overview of GitHub:
+
+GitHub is a web-based platform that provides version control and
+collaboration features using Git, a distributed version control system.
+It enables developers to work together on projects, track changes to
+code, and efficiently manage different versions of the project. GitHub
+is widely used in the software development industry and is an essential
+tool for collaborative projects and maintaining code quality.
+
+### B. Introduce GitHub Desktop and JupyterHub GitHub widget:
+
+GitHub Desktop is a graphical user interface (GUI) application that
+simplifies working with Git and GitHub by providing a more visual and
+intuitive way to manage repositories, branches, commits, and other Git
+features. JupyterHub GitHub widget, on the other hand, is a built-in
+widget that integrates Git and GitHub functionality directly into
+Jupyter notebooks, allowing users to perform version control and
+collaboration tasks within the Jupyter environment. Both tools help
+streamline the process of working with GitHub and make it more
+accessible to users with varying levels of experience with Git and
+version control.
+
+#### 1. Download GitHub Desktop
+
+##### Step 1: Download GitHub Desktop
+
+Go to the GitHub Desktop download page: https://desktop.github.com/
+
+Click on the “Download for Windows” or “Download for macOS” button,
+depending on your operating system. The download should start
+automatically.
+
+##### Step 2: Install GitHub Desktop
+
+For Windows:
+
+Locate the downloaded installer file (usually in the Downloads folder)
+and double-click on it to run the installer.
+
+Follow the installation instructions that appear on the screen,
+accepting the default settings or customizing them as desired.
+
+Once the installation is complete, GitHub Desktop will launch
+automatically. For macOS:
+
+Locate the downloaded .zip file (usually in the Downloads folder) and
+double-click on it to extract the GitHub Desktop application.
+
+Drag the extracted “GitHub Desktop” application into the “Applications”
+folder.
+
+Open the “Applications” folder and double-click on “GitHub Desktop” to
+launch the application.
+
+##### Step 3: Set up GitHub Desktop
+
+When GitHub Desktop launches for the first time, you will be prompted to
+sign in with your GitHub account. If you don’t have one, you can create
+one at https://github.com/join.
+
+Enter your GitHub username (or email) and password, and click on “Sign
+in.”
+
+You will then be prompted to configure Git. Enter your name and email
+address, which will be used for your commit messages. Click “Continue”
+when you’re done. Choose whether you want to submit usage data to help
+improve GitHub Desktop. Click “Finish” to complete the setup.
+
+Now, you have successfully installed and set up GitHub Desktop. You can
+start using it to clone repositories, make changes, commit, and sync
+with the remote repositories on GitHub.
+
+#### 1. Download GitHub for JupyterHub cloud service
+
+### Step 1: Accessing JupyterHub on the cloud
+
+Visit the JupyterHub cloud service you want to use (e.g., Binder, Google
+Colab, or a custom JupyterHub deployment provided by your organization).
+
+Sign in with your credentials or authenticate using a third-party
+service if required.
+
+### Step 2: Launch a new Jupyter Notebook or open an existing one
+
+Click on the “New” button (usually located in the top right corner) and
+select “Python” to create a new Jupyter Notebook or open an existing one
+from the file browser.
+
+Once the notebook is open, you will see the Jupyter Notebook interface
+with the familiar cells for writing and executing code.
+
+### Step 3: Install and enable the JupyterLab Git extension
+
+In your Jupyter Notebook, create a new code cell and run the following
+command to install the JupyterLab Git extension:
+
+!pip install jupyterlab-git
+
+Restart the Jupyter Notebook server for the changes to take effect.
+
+### Step 4: Using the JupyterHub GitHub widget
+
+In the Jupyter Notebook interface, you should now see a Git icon on the
+left sidebar. Click on it to open the GitHub widget.
+
+To clone a repository, click on the “+” icon in the GitHub widget and
+enter the repository URL. This will clone the repository into your
+JupyterHub workspace. You can now navigate through the cloned
+repository, make changes, and use the GitHub widget to stage, commit,
+and push your changes back to the remote repository.
+
+To create and manage branches, use the branch icon in the GitHub widget.
+You can create new branches, switch between branches, and merge branches
+using this interface.
+
+To sync your local repository with the remote repository, use the “Pull”
+and “Push” buttons in the GitHub widget.
+
+Now, you know how to access and use the JupyterHub GitHub widget running
+on the cloud. This allows you to work with Git and GitHub directly from
+your Jupyter Notebook interface, streamlining your workflow and making
+collaboration easier.
+
+### C. GitHub in Rstudio:
+
+Integrating GitHub with RStudio allows users to manage their Git
+repositories and collaborate on projects directly within the RStudio
+environment. It offers similar functionality to GitHub Desktop but
+caters specifically to R users working within RStudio. By configuring
+RStudio to work with Git, creating or opening RStudio projects, and
+linking projects to GitHub repositories, users can enjoy a seamless
+workflow for version control and collaboration. RStudio’s Git pane
+enables users to stage, commit, and push changes to remote repositories,
+as well as manage branches and sync local repositories with remote ones,
+providing a comprehensive solution for R developers working with GitHub.
+
+#### Step 1: Install Git
+
+Before integrating GitHub with RStudio, you need to have Git installed
+on your computer. Visit the official Git website (https://git-scm.com/)
+to download and install the latest version of Git for your operating
+system.
+
+#### Step 2: Configure RStudio to work with Git
+
+Open RStudio.
+
+Go to “Tools” \> “Global Options” in the top menu. In the “Global
+Options” window, click on the “Git/SVN” tab.
+
+Check that the “Git executable” field is pointing to the correct
+location of the installed Git. If not, click “Browse” and navigate to
+the location of the Git executable file (usually found in the “bin”
+folder of the Git installation directory).
+
+Click “OK” to save the changes.
+
+#### Step 3: Create or open an RStudio project
+
+To create a new RStudio project, go to “File” \> “New Project” in the
+top menu. You can either create a new directory or choose an existing
+one for your project.
+
+To open an existing RStudio project, go to “File” \> “Open Project” and
+navigate to the project’s “.Rproj” file.
+
+#### Step 4: Link your RStudio project to a GitHub repository
+
+In the RStudio project, go to the “Tools” menu and select “Version
+Control” \> “Project Setup.”
+
+In the “Project Setup” window, select “Git” as the version control
+system and click “OK.”
+
+A new “.git” folder will be created in your project directory,
+initializing it as a Git repository. Commit any changes you have made so
+far by clicking on the “Commit” button in the “Git” pane in RStudio.
+
+To link your local repository to a remote GitHub repository, go to your
+GitHub account and create a new repository.
+
+Copy the remote repository’s URL (e.g.,
+“https://github.com/username/repository.git”).
+
+In RStudio, open the “Shell” by going to “Tools” \> “Shell.”
+
+In the shell, run the following command to add the remote repository:
+
+git remote add origin https://github.com/username/repository.git
+
+Replace the URL with the one you copied from your GitHub repository.
+
+Push your changes to the remote repository by running the following
+command in the shell:
+
+git push -u origin master
+
+Now, your RStudio project is linked to a GitHub repository. You can use
+the “Git” pane in RStudio to stage, commit, and push changes to the
+remote repository, as well as manage branches and sync your local
+repository with the remote one.
+
+By integrating GitHub with RStudio, you can streamline your workflow,
+collaborate more effectively with your team, and manage your Git
+repositories directly from the RStudio interface.
+
+## II. GitHub Basics (4 minutes)
+
+### A. Repository:
+
+A repository, often abbreviated as “repo,” is the fundamental building
+block of GitHub. It is a storage space for your project files, including
+the code, documentation, and other related resources. Each repository
+also contains the complete history of all changes made to the project
+files, which is crucial for effective version control. Repositories can
+be public, allowing anyone to access and contribute, or private,
+restricting access to specific collaborators.
+
+### B. Fork and Clone:
+
+Forking and cloning are two essential operations for working with
+repositories on GitHub. Forking creates a personal copy of someone
+else’s repository under your GitHub account, enabling you to make
+changes to the project without affecting the original repo. Cloning, on
+the other hand, is the process of downloading a remote repository to
+your local machine for offline development. In GitHub Desktop, you can
+clone a repository by selecting “Clone a repository from the Internet”
+and entering the repository URL. In JupyterHub GitHub widget, you can
+clone a repository by entering the repo URL in the “Clone Repository”
+section of the widget.
+
+### C. Branches:
+
+Branches are a critical aspect of Git version control, as they allow you
+to create multiple parallel versions of your project within a single
+repository. This is particularly useful when working on new features or
+bug fixes, as it prevents changes from interfering with the main (or
+“master”) branch until they are ready to be merged. Creating a new
+branch in GitHub Desktop can be done by clicking the “Current Branch”
+dropdown and selecting “New Branch.” In JupyterHub GitHub widget, you
+can create a new branch by clicking the “New Branch” button in the
+“Branches” section of the widget.
+
+### D. Replace ‘master’ with ‘main’:
+
+In recent years, there has been a growing awareness of the importance of
+inclusive language in technology. One such example is the use of the
+term “master” in the context of the default branch in a GitHub
+repository. The term “master” has historical connections to the
+“master/slave” file structure, which evokes an unsavory colonial past
+associated with slavery. In light of this, many developers and
+organizations have begun to replace the term “master” with more neutral
+terms, such as “main.” We encourage you to follow this practice and
+change the default branch name in your repositories from “master” to
+“main” or another suitable alternative. This small change can help
+promote a more inclusive and welcoming environment within the technology
+community.
+
+## III. Collaboration and Version Control (5 minutes)
+
+### A. Commits:
+
+Commits are snapshots of your project’s changes at a specific point in
+time, serving as the fundamental building blocks of Git’s version
+control system. Commits make it possible to track changes, revert to
+previous versions, and collaborate with others. In GitHub Desktop, you
+can make a commit by staging the changes you want to include, adding a
+descriptive commit message, and clicking “Commit to \[branch_name\].” In
+JupyterHub GitHub widget, you can create a commit by selecting the files
+with changes, entering a commit message, and clicking the “Commit”
+button.
+
+### B. Push:
+
+In GitHub, “push” is a fundamental operation in the version control
+process that transfers commits from your local repository to a remote
+repository, such as the one hosted on GitHub. When you push changes, you
+synchronize the remote repository with the latest updates made to your
+local repository, making those changes accessible to other collaborators
+working on the same project. This operation ensures that the remote
+repository reflects the most recent state of your work and allows your
+team members to stay up to date with your changes. Pushing is an
+essential step in distributed version control systems like Git, as it
+promotes efficient collaboration among multiple contributors and
+provides a centralized location for tracking the project’s history and
+progress.
+
+In GitHub, the concepts of “commit” and “push” represent two distinct
+steps in the version control process. A “commit” is the action of saving
+changes to your local repository. When you commit changes, you create a
+snapshot of your work, accompanied by a unique identifier and an
+optional descriptive message. Commits allow you to track the progress of
+your work over time and make it easy to revert to a previous state if
+necessary. On the other hand, “push” is the action of transferring your
+local commits to a remote repository, such as the one hosted on GitHub.
+Pushing makes your changes accessible to others collaborating on the
+same project and ensures that the remote repository stays up to date
+with your local repository. In summary, committing saves changes
+locally, while pushing synchronizes those changes with a remote
+repository, allowing for seamless collaboration among multiple
+contributors.
+
+### C. Pull Requests:
+
+Pull requests are a collaboration feature on GitHub that enables
+developers to propose changes to a repository, discuss those changes,
+and ultimately merge them into the main branch. To create a pull
+request, you must first push your changes to a branch on your fork of
+the repository. Then, using either GitHub Desktop or JupyterHub GitHub
+widget, you can navigate to the original repository, click the “Pull
+Request” tab, and create a new pull request. After the pull request is
+reviewed and approved, it can be merged into the main branch.
+
+### D. Merging and Resolving Conflicts:
+
+Merging is the process of combining changes from one branch into
+another. This is typically done when a feature or bugfix has been
+completed and is ready to be integrated into the main branch. Conflicts
+can arise during the merging process if the same lines of code have been
+modified in both branches. To resolve conflicts, you must manually
+review the changes and decide which version to keep. In GitHub Desktop,
+you can merge branches by selecting the target branch and choosing
+“Merge into Current Branch.” Conflicts will be highlighted, and you can
+edit the files to resolve them before committing the changes. In
+JupyterHub GitHub widget, you can merge branches by selecting the target
+branch in the “Branches” section and clicking the “Merge” button. If
+conflicts occur, the widget will prompt you to resolve them before
+completing the merge.
+
+## IV. Additional Features (2 minutes)
+
+### A. Issues and Project Management:
+
+Issues are a powerful feature in GitHub that allows developers to track
+and manage bugs, enhancements, and other tasks within a project. Issues
+can be assigned to collaborators, labeled for easy organization, and
+linked to specific commits or pull requests. They provide a centralized
+location for discussing and addressing project-related concerns,
+fostering collaboration and transparent communication among team
+members. Using issues effectively can significantly improve the overall
+management and organization of your projects.
+
+### B. GitHub Pages:
+
+GitHub Pages is a service offered by GitHub that allows you to host
+static websites directly from a repository. By creating a new branch
+named “gh-pages” in your repository and adding the necessary files
+(HTML, CSS, JavaScript, etc.), GitHub will automatically build and
+deploy your website to a publicly accessible URL. This is particularly
+useful for showcasing project documentation, creating personal
+portfolios, or hosting project demos. With GitHub Pages, you can take
+advantage of the version control and collaboration features of GitHub
+while easily sharing your work with others.
+
+## V. Conclusion (2 minutes)
+
+### A. Recap of the essentials of GitHub:
+
+In this brief introduction, we have covered the essentials of GitHub,
+including the basics of repositories, forking, cloning, branching,
+commits, pull requests, merging, and resolving conflicts. We have also
+discussed additional features like issues for project management and
+GitHub Pages for hosting websites directly from a repository.
+
+### B. Encourage further exploration and learning:
+
+While this introduction provides a solid foundation for understanding
+and using GitHub, there is still much more to learn and explore. As you
+continue to use GitHub in your projects, you will discover new features
+and workflows that can enhance your productivity and collaboration. We
+encourage you to dive deeper into the platform and experiment with
+different tools and techniques.
+
+### C. Share resources for learning more about GitHub:
+
+There are many resources available for learning more about GitHub and
+expanding your skills. Some popular resources include GitHub Guides
+(https://guides.github.com/), which offers a collection of tutorials and
+best practices, the official GitHub documentation
+(https://docs.github.com/), and various online tutorials and courses. By
+engaging with these resources and participating in the GitHub community,
+you can further develop your understanding of the platform and become a
+more proficient user.
+
+## V. Conclusion (2 minutes)
+
+### A. Recap of the essentials of GitHub:
+
+In this brief introduction, we have covered the essentials of GitHub,
+including the basics of repositories, forking, cloning, branching,
+commits, pull requests, merging, and resolving conflicts. We have also
+discussed additional features like issues for project management and
+GitHub Pages for hosting websites directly from a repository.
+
+### B. Encourage further exploration and learning:
+
+While this introduction provides a solid foundation for understanding
+and using GitHub, there is still much more to learn and explore. As you
+continue to use GitHub in your projects, you will discover new features
+and workflows that can enhance your productivity and collaboration. We
+encourage you to dive deeper into the platform and experiment with
+different tools and techniques.
+
+### C. Share resources for learning more about GitHub:
+
+There are many resources available for learning more about GitHub and
+expanding your skills. Some popular resources include GitHub Guides
+(https://guides.github.com/), which offers a collection of tutorials and
+best practices, the official GitHub documentation
+(https://docs.github.com/), and various online tutorials and courses. By
+engaging with these resources and participating in the GitHub community,
+you can further develop your understanding of the platform and become a
+more proficient user.
diff --git a/docs/resources/manuscript.md b/docs/resources/manuscript.md
new file mode 100644
index 0000000..400212e
--- /dev/null
+++ b/docs/resources/manuscript.md
@@ -0,0 +1,58 @@
+# Manuscript Title
+
+## Authors
+
+- Author 1, Affiliation
+- Author 2, Affiliation
+- ...
+
+## Abstract
+
+- A brief summary of the research, its objectives, main findings, and conclusions.
+
+## Introduction
+
+- Background information and context setting for the research.
+- Statement of the problem and research objectives.
+- Overview of the methodology and approach.
+
+## Literature Review
+
+- Discussion of relevant previous work and how this research contributes to the field.
+
+## Methodology
+
+- Detailed description of the research methodology.
+- Explanation of data collection and analysis techniques.
+- Justification for methodological choices.
+
+## Results
+
+- Presentation of the research findings.
+- Use of tables, graphs, and figures to illustrate key points.
+- Analysis and interpretation of the results.
+
+## Discussion
+
+- Discussion of the implications of the findings.
+- Comparison with previous research in the field.
+- Consideration of the limitations of the study.
+
+## Conclusion
+
+- Summary of the main findings.
+- Reflection on the research's significance and potential impact.
+- Suggestions for future research directions.
+
+## Acknowledgements
+
+- Acknowledgement of any assistance, funding, or contributions from others.
+
+## References
+
+- Bibliographic details of the cited works.
+- Use a consistent citation style throughout.
+
+## Appendices
+
+- Additional material that supports the manuscript but is too detailed for the main sections.
diff --git a/docs/resources/markdown_basics.md b/docs/resources/markdown_basics.md
new file mode 100644
index 0000000..fa69ea4
--- /dev/null
+++ b/docs/resources/markdown_basics.md
@@ -0,0 +1,434 @@
+# Markdown for the Modern Researcher at ESIIL
+
+## Introduction
+
+- Overview of Markdown's relevance and utility in modern research.
+- How Markdown streamlines documentation in diverse scientific and coding environments.
+
+## Section 1: Mastering Markdown Syntax
+
+- **Objective:** Equip researchers with a thorough understanding of Markdown syntax and its diverse applications.
+- **Topics Covered:**
+  - Fundamentals of Text Formatting (headings, lists, bold, italics)
+  - Advanced Structures (tables, blockquotes)
+  - Integrating Multimedia (image and video links)
+  - Diagrams with Mermaid (creating flowcharts, mind maps, timelines)
+  - Interactive Elements (hyperlinks, embedding interactive content)
+- **Activities:**
+  - Crafting a Markdown document with various formatting elements.
+  - Developing diagrams using Mermaid for research presentations.
+  - Embedding multimedia elements in a Markdown document for enhanced communication.
+
+## Section 2: Markdown in Research Tools
+
+- **Objective:** Showcase the integration of Markdown in RStudio and Jupyter Notebooks for scientific documentation.
+- **Topics Covered:**
+  - Implementing Markdown in RStudio (R Markdown, knitting to HTML/PDF)
+  - Utilizing Markdown in Jupyter Notebooks (code and Markdown cells)
+  - Best practices for documenting research code
+  - Including code outputs and visualizations in documentation
+- **Activities:**
+  - Creating and sharing an R Markdown document with annotated research data.
+  - Building a comprehensive Jupyter Notebook with integrated Markdown annotations.
+
+## Section 3: Disseminating Research with Markdown and GitHub Pages
+
+- **Objective:** Teach researchers how to publish and manage Markdown-based documentation as web pages.
+- **Topics Covered:**
+  - Setting up a GitHub repository for hosting documentation
+  - Transforming Markdown files into web-friendly formats
+  - Customizing web page layouts and themes
+  - Advanced features using Jekyll
+  - Version control and content management for documentation
+- **Activities:**
+  - Publishing a research project documentation on GitHub Pages.
+  - Applying custom themes and layouts to enhance online documentation.
+
+## Conclusion
+
+- Review of Markdown's role in enhancing research efficiency and clarity.
+- Encouraging the integration of Markdown into daily research activities for improved documentation and dissemination.
+
+## Additional Resources
+
+- Curated list of advanced Markdown tutorials, guides for GitHub Pages, and Jekyll resources for researchers.
+
+
+
+
+## Section 1: Mastering Markdown Syntax
+
+### 1. Fundamentals of Text Formatting
+
+- **Headings**: Use `#` for different levels of headings.
+  - # Heading Level 1
+  - ## Heading Level 2
+  - ### Heading Level 3
+
+- **Lists**: Bulleted lists use asterisks, numbers for ordered lists.
+  - Item 1
+  - Item 2
+    - Subitem 2.1
+    - Subitem 2.2
+  - 1. First item
+  - 2. Second item
+
+- **Bold and Italics**: Use asterisks or underscores.
+  - **Bold Text**
+  - *Italic Text*
+
+### 2. Advanced Structures
+
+- **Tables**: Create tables using dashes and pipes.
+  - | Header 1 | Header 2 | Header 3 |
+    |----------|----------|----------|
+    | Row 1    | Data     | Data     |
+    | Row 2    | Data     | Data     |
+  - Add a ":"" to change text justification. Here the : is added on the left for left justification.
+    | Header 1 | Header 2 | Header 3 |
+    |---------:|--------- |----------|
+    | Row 1    | Data     | Data     |
+    | Row 2    | Data     | Data     |
+
+  - |   |   |   |   |   |   |   |   |   |   |   |   |
+    |---|---|---|---|---|---|---|---|---|---|---|---|
+    | A | N | A | L | Y | T | I | C | S | E | N | R |
+    | E | I | N | V | I | R | O | N | M | E | N | T |
+    | V | E | L | O | P | M | O | C | O | M | U | N |
+    | E | G | A | G | E | L | L | A | H | C | N | E |
+    | R | A | T | A | D | E | V | E | L | O | P | W |
+    | E | I | T | S | I | T | N | E | I | C | S | R |
+    | S | O | I | G | O | L | O | I | B | H | T | L |
+    | A | H | T | L | A | E | W | E | G | N | E | L |
+    | T | I | T | S | I | T | N | E | I | C | S | N |
+    | I | E | E | S | R | E | H | T | O | E | N | I |
+    | C | S | L | L | A | H | C | E | G | L | A | N |
+    | E | G | A | L | L | E | H | C | N | E | I | C |
+
+  - If you hit the boundaries of Markdown's capabilities, you can start to add html directly. Remember, this entire exercisse is to translate to html. 
+
+**Sudoku Puzzle**
+Fill in the blank cells with numbers from 1 to 9, such that each row, column, and 3x3 subgrid contains all the numbers from 1 to 9 without repetition.
+
+|   |   |   |   |   |   |   |   |   |
+|---|---|---|---|---|---|---|---|---|
+| 5 | 3 |   |   | 7 |   |   |   |   |
+| 6 |   |   | 1 | 9 | 5 |   |   |   |
+|   | 9 | 8 |   |   |   |   | 6 |   |
+| 8 |   |   |   | 6 |   |   |   | 3 |
+| 4 |   |   | 8 |   | 3 |   |   | 1 |
+| 7 |   |   |   | 2 |   |   |   | 6 |
+|   | 6 |   |   |   |   | 2 | 8 |   |
+|   |   |   | 4 | 1 | 9 |   |   | 5 |
+|   |   |   |   | 8 |   |   | 7 | 9 |
+
+
+
+
+<table>
+  <tr><td style="color: blue;">5</td><td style="color: blue;">3</td><td style="color: grey;">4</td><td style="color: grey;">6</td><td style="color: blue;">7</td><td style="color: grey;">8</td><td style="color: grey;">9</td><td style="color: grey;">1</td><td style="color: grey;">2</td></tr>
+  <tr><td style="color: blue;">6</td><td style="color: grey;">7</td><td style="color: grey;">2</td><td style="color: blue;">1</td><td style="color: blue;">9</td><td style="color: blue;">5</td><td style="color: grey;">3</td><td style="color: grey;">4</td><td style="color: grey;">8</td></tr>
+  <tr><td style="color: grey;">1</td><td style="color: blue;">9</td><td style="color: blue;">8</td><td style="color: grey;">3</td><td style="color: grey;">4</td><td style="color: grey;">2</td><td style="color: grey;">5</td><td style="color: blue;">6</td><td style="color: grey;">7</td></tr>
+  <tr><td style="color: blue;">8</td><td style="color: grey;">5</td><td style="color: grey;">9</td><td style="color: grey;">7</td><td style="color: blue;">6</td><td style="color: grey;">1</td><td style="color: grey;">4</td><td style="color: grey;">2</td><td style="color: blue;">3</td></tr>
+  <tr><td style="color: blue;">4</td><td style="color: grey;">2</td><td style="color: grey;">6</td><td style="color: blue;">8</td><td style="color: grey;">5</td><td style="color: blue;">3</td><td style="color: grey;">7</td><td style="color: grey;">9</td><td style="color: blue;">1</td></tr>
+  <tr><td style="color: blue;">7</td><td style="color: grey;">1</td><td style="color: grey;">3</td><td style="color: grey;">9</td><td style="color: blue;">2</td><td style="color: grey;">4</td><td style="color: grey;">8</td><td style="color: grey;">5</td><td style="color: blue;">6</td></tr>
+  <tr><td style="color: grey;">9</td><td style="color: blue;">6</td><td style="color: grey;">1</td><td style="color: grey;">5</td><td style="color: grey;">3</td><td style="color: grey;">7</td><td style="color: blue;">2</td><td style="color: blue;">8</td><td style="color: grey;">4</td></tr>
+  <tr><td style="color: grey;">2</td><td style="color: grey;">8</td><td style="color: grey;">7</td><td style="color: blue;">4</td><td style="color: blue;">1</td><td style="color: blue;">9</td><td style="color: grey;">6</td><td style="color: grey;">3</td><td style="color: blue;">5</td></tr>
+  <tr><td style="color: grey;">3</td><td style="color: grey;">4</td><td style="color: grey;">5</td><td style="color: grey;">2</td><td style="color: blue;">8</td><td style="color: grey;">6</td><td style="color: grey;">1</td><td style="color: grey;">7</td><td style="color: blue;">9</td></tr>
+</table>
+
+
+
+
+
+- **Blockquotes**: Use `>` for blockquotes.
+  - > This is a blockquote.
+  - > It can span multiple lines.
+
+### 3. Integrating Multimedia
+
+- **Images**: Add images using the format `![alt text](image_url)`.
+  - ![Markdown Logo](https://example.com/markdown-logo.png)
+
+- **Videos**: Embed videos using HTML in Markdown.
+  - `<iframe width="560" height="315" src="https://www.youtube.com/embed/dQw4w9WgXcQ" frameborder="0" allowfullscreen></iframe>`
+
+### 4. Diagrams with Mermaid
+
+- **Flowcharts**:
+
+```mermaid
+    graph TD
+    A[Start] --> B[Analyze Data]
+    B --> C{Is Data Large?}
+    C -->|Yes| D[Apply Big Data Solutions]
+    C -->|No| E[Use Traditional Methods]
+    D --> F[Machine Learning]
+    E --> G[Statistical Analysis]
+    F --> H{Model Accurate?}
+    G --> I[Report Results]
+    H -->|Yes| J[Deploy Model]
+    H -->|No| K[Refine Model]
+    J --> L[Monitor Performance]
+    K --> F
+    L --> M[End: Success]
+    I --> N[End: Report Generated]
+    style A fill:#f9f,stroke:#333,stroke-width:2px
+    style M fill:#9f9,stroke:#333,stroke-width:2px
+    style N fill:#9f9,stroke:#333,stroke-width:2px
+```
+
+- **Mind Maps**:
+```mermaid
+    mindmap
+  root((ESIIL))
+    section Data Sources
+      Satellite Imagery
+        ::icon(fa fa-satellite)
+      Remote Sensing Data
+        Drones
+        Aircraft
+      On-ground Sensors
+        Weather Stations
+        IoT Devices
+      Open Environmental Data
+        Public Datasets
+        ::icon(fa fa-database)
+    section Research Focus
+      Climate Change Analysis
+        Ice Melt Patterns
+        Sea Level Rise
+      Biodiversity Monitoring
+        Species Distribution
+        Habitat Fragmentation
+      Geospatial Analysis Techniques
+        Machine Learning Models
+        Predictive Analytics
+    section Applications
+      Conservation Strategies
+        ::icon(fa fa-leaf)
+      Urban Planning
+        Green Spaces
+      Disaster Response
+        Flood Mapping
+        Wildfire Tracking
+    section Tools and Technologies
+      GIS Software
+        QGIS
+        ArcGIS
+      Programming Languages
+        Python
+        R
+      Cloud Computing Platforms
+        AWS
+        Google Earth Engine
+      Data Visualization
+        D3.js
+        Tableau
+```
+
+- **Timelines**:
+
+```mermaid
+gantt
+    title ESIIL Year 2 Project Schedule
+    dateFormat  YYYY-MM-DD
+    section CI
+    Sovereign OASIS via private jupiterhubs :2024-08-01, 2024-10-30
+    OASIS documentation                    :2024-09-15, 70d
+    Data cube OASIS via cyverse account    :2024-09-15, 100d
+    Integrate with ESIIL User Management system :2024-08-01, 2024-11-30
+    Build badges to deploy DE from mkdoc   :2024-09-01, 2024-12-15
+    Streamline Github ssh key management   :2024-10-01, 2024-12-31
+    Cyverse support (R proxy link)         :2024-11-01, 2024-12-31
+    Cyverse use summary and statistics     :2024-08-01, 2024-12-15
+    
+    section CI Consultation and Education
+    Conferences/Invited talks              :2024-08-01, 2024-12-31
+    Office hours                           :2024-08-15, 2024-12-15
+    Proposals                              :2024-09-01, 2024-11-15
+    Private lessons                        :2024-09-15, 2024-11-30
+    Pre-event trainings                    :2024-10-01, 2024-12-15
+    Textbook development w/ education team :2024-08-01, 2024-12-15
+    Train the trainers / group lessons     :2024-08-15, 2024-11-30
+    Tribal engagement                      :2024-09-01, 2024-12-15
+    Ethical Space training                 :2024-09-15, 2024-12-31
+    
+    section CI Design and Build
+    Data library (repository)              :2024-08-01, 2024-10-30
+    Analytics library (repository)         :2024-08-15, 2024-11-15
+    Containers (repository)                :2024-09-01, 2024-11-30
+    Cloud infrastructure templates (repository) :2024-09-15, 2024-12-15
+    Tribal resilience Data Cube            :2024-10-01, 2024-12-31
+```
+
+```mermaid
+
+%%{init: { 'logLevel': 'debug', 'theme': 'base', 'gitGraph': {'rotateCommitLabel': true}} }%%
+gitGraph
+  commit id: "Start from template"
+  branch c1
+  commit id: "Set up SSH key pair"
+  commit id: "Modify _config.yml for GitHub Pages"
+  commit id: "Initial website structure"
+  commit id: "Add new markdown pages"
+  commit id: "Update navigation tree"
+  commit id: "Edit existing pages"
+  commit id: "Delete old markdown pages"
+  commit id: "Finalize website updates"
+  commit id: "Add new markdown pages"
+  commit id: "Update navigation tree"
+checkout c1
+   
+  branch b1
+  
+  commit
+  commit
+  checkout c1
+  merge b1
+```
+
+```mermaid
+%%{init: {"quadrantChart": {"chartWidth": 400, "chartHeight": 400}, "themeVariables": {"quadrant1TextFill": "#ff0000"} }}%%
+quadrantChart
+  x-axis Urgent --> Not Urgent
+  y-axis Not Important --> "Important ❤"
+  quadrant-1 Plan
+  quadrant-2 Do
+  quadrant-3 Delegate
+  quadrant-4 Delete
+```
+
+
+```mermaid
+timeline
+    title Major Events in Environmental Science and Data Science
+    section Environmental Science
+        19th century : Foundations in Ecology and Conservation
+        1962 : Publication of 'Silent Spring' by Rachel Carson
+        1970 : First Earth Day
+        1987 : Brundtland Report introduces Sustainable Development
+        1992 : Rio Earth Summit
+        2015 : Paris Agreement on Climate Change
+    section Data Science
+        1960s-1970s : Development of Database Management Systems
+        1980s : Emergence of Data Warehousing
+        1990s : Growth of the World Wide Web and Data Mining
+        2000s : Big Data and Predictive Analytics
+        2010s : AI and Machine Learning Revolution
+        2020s : Integration of AI in Environmental Research
+```
+
+
+
+
+```mermaid
+erDiagram
+    CAR ||--o{ NAMED-DRIVER : allows
+    CAR {
+        string registrationNumber
+        string make
+        string model
+    }
+    PERSON ||--o{ NAMED-DRIVER : is
+    PERSON {
+        string firstName
+        string lastName
+        int age
+    }
+```
+
+```mermaid
+---
+config:
+  sankey:
+    showValues: false
+---
+sankey-beta
+
+NASA Data,Big Data Harmonization,100
+    Satellite Imagery,Big Data Harmonization,80
+    Open Environmental Data,Big Data Harmonization,70
+    Remote Sensing Data,Big Data Harmonization,90
+    Big Data Harmonization, Data Analysis and Integration,340
+    Data Analysis and Integration,Climate Change Research,100
+    Data Analysis and Integration,Biodiversity Monitoring,80
+    Data Analysis and Integration,Geospatial Mapping,60
+    Data Analysis and Integration,Urban Planning,50
+    Data Analysis and Integration,Disaster Response,50
+```
+
+
+### 5. Interactive Elements
+
+- **Hyperlinks**: Use the format `[link text](URL)`.
+  - [Google](https://www.google.com)
+  - [Play Tetris](https://tetris.com/play-tetris)
+
+- **Embedding Interactive Content**: Use HTML tags or specific platform embed codes.
+  - `<iframe src="https://example.com/interactive-content" width="600" height="400"></iframe>`
+
+
+
+
+### 6. Math Notation
+
+Markdown can be combined with LaTeX for mathematical notation, useful in environmental data science for expressing statistical distributions, coordinate systems, and more. This requires a Markdown renderer with LaTeX support (like MathJax or KaTeX).
+
+- **Inline Math**: Use single dollar signs for inline math expressions. Representing the normal distribution.
+
+  Example: The probability density function of the normal distribution is given by $f(x|\mu,\sigma) = \frac{1}{\sigma\sqrt{2\pi}}e^{-\frac{1}{2}\left(\frac{x-\mu}{\sigma}\right)^2}$.`
+
+- **Display Math**: Use double dollar signs for standalone equations.
+
+  Example:
+  $$
+  f(x|\mu,\sigma) = \frac{1}{\sigma\sqrt{2\pi}}e^{-\frac{1}{2}\left(\frac{x-\mu}{\sigma}\right)^2}
+  $$
+  
+
+- **Common LaTeX Elements for Environmental Data Science**:
+  - **Statistical Distributions**:
+    - Normal Distribution: `\frac{1}{\sigma\sqrt{2\pi}}e^{-\frac{1}{2}\left(\frac{x-\mu}{\sigma}\right)^2}` for $\frac{1}{\sigma\sqrt{2\pi}}e^{-\frac{1}{2}\left(\frac{x-\mu}{\sigma}\right)^2}$
+    - Poisson Distribution: `P(k; \lambda) = \frac{\lambda^k e^{-\lambda}}{k!}` for $P(k; \lambda) = \frac{\lambda^k e^{-\lambda}}{k!}$
+  - **Coordinate Systems**:
+    - Spherical Coordinates: `(r, \theta, \phi)` for $(r, \theta, \phi)$
+    - Cartesian Coordinates: `(x, y, z)` for $(x, y, z)$
+  - **Geospatial Equations**:
+    - Haversine Formula for Distance: `a = \sin^2\left(\frac{\Delta\phi}{2}\right) + \cos(\phi_1)\cos(\phi_2)\sin^2\left(\frac{\Delta\lambda}{2}\right)` for $a = \sin^2\left(\frac{\Delta\phi}{2}\right) + \cos(\phi_1)\cos(\phi_2)\sin^2\left(\frac{\Delta\lambda}{2}\right)$
+
+Note: The rendering of these equations as formatted math will depend on your Markdown viewer's LaTeX capabilities.
+
+
+
+### 7. Effective Citations in Markdown
+
+## Inline Citations
+
+- **Objective:** Learn how to use inline citations in Markdown.
+- **Example Usage:**
+  - Inline citation of a single work: 
+    - Some text with an inline citation. [@jones:envstudy:2020]
+  - Inline citation with specific page or section: 
+    - More text with a specific section cited. [See @jones:envstudy:2020, §4.2]
+  - Contrasting views: 
+    - Discussion of a topic with a contrasting view. [Contra @smith:climatechange:2019, p. 78]
+
+## Footnote Citations
+
+- **Objective:** Understand how to use footnote citations in Markdown.
+- **Example Usage:**
+  - Citing with a footnote: 
+    - Some statement in the text.[^1]
+  - Multiple references to the same footnote: 
+    - Another statement referring to the same source.[^1]
+  - A different citation: 
+    - Additional comment with a new citation.[^2]
+
+## Creating Footnotes
+
+- **Example Syntax:**
+  - [^1]: First reference details. Example: Emma Jones, "Environmental Study," Nature Journal, May 2020, https://nature-journal.com/envstudy2020.
+  - [^2]: Second reference details. Example: David Smith, "Climate Change Controversies," Science Daily, August 2019, https://sciencedaily.com/climatechange2019.
+
+
diff --git a/docs/resources/notes_from_readings.md b/docs/resources/notes_from_readings.md
new file mode 100644
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+# Literature Reading Notes
+
+## Reference Information
+
+- **Title:** 
+- **Authors:** 
+- **Publication Year:** 
+- **Journal/Source:** 
+- **DOI/URL:** 
+
+## Summary
+
+- Brief summary of the main objective, research question, or thesis of the literature.
+
+## Key Findings
+
+- Major findings or conclusions:
+  - Finding 1
+  - Finding 2
+  - ...
+
+## Methodology
+
+- Description of research methodology, techniques, or approaches.
+- Notable tools, datasets, or analytical methods used.
+
+## Theoretical Framework
+
+- Theoretical models or frameworks underpinning the research.
+- Positioning within the broader field.
+
+## Critical Analysis
+
+- **Strengths:** Well-executed aspects or convincing arguments.
+- **Limitations:** Weaknesses, gaps, or biases.
+- **Insights:** New understandings or perspectives gained.
+
+## Connections to Other Work
+
+- Similarities or differences with other readings.
+- Complementarity to other studies.
+
+## Quotations and Notes
+
+- Significant quotes:
+  - "Quote here." - Author Name, page number
+- Additional notes or comments.
+
+## Personal Reflections
+
+- Influence on understanding or perspective.
+- Potential impact on future research or studies.
+
+## Action Items
+
+- Follow-up actions such as readings, discussions, or research activities:
+  - [ ] Action item 1
+  - [ ] Action item 2
+  - ...
diff --git a/docs/resources/participant_agreement.md b/docs/resources/participant_agreement.md
new file mode 100644
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+++ b/docs/resources/participant_agreement.md
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+# Participant Agreement
+
+This Participant Agreement (“Agreement”) is a contract between you (“You/Your” or “Participant”) and THE REGENTS OF THE UNIVERSITY OF COLORADO, a body corporate, acting on behalf of the University of Colorado Boulder, a public institution of higher education created under the Constitution and the Law of the State of Colorado (the “University”), having offices located at 3100 Marine Street, Boulder, CO 80309.
+
+In consideration of Your participation in the Forest Carbon Codefest (the “Codefest”), the sufficiency of which is hereby acknowledged, You agree as follows:
+
+Environmental Data Science Innovation & Inclusion Lab (“ESIIL”) is a National Science Foundation (“NSF”) funded data synthesis center led by the University. Earth Lab is part of the Cooperative Institute for Research in Environmental Sciences (CIRES) specializing in data-intensive open, reproducible environmental science. Earth Lab and ESIIL will co-host the Codefest in person from March 12 through March 14, 2023.
+
+## Codefest Description
+
+The Codefest aims to use big data to understand aboveground forest carbon dynamics. It brings together environmental scientists, data analysts, and forest experts from academia, non-profits, and the private sector under one roof to collaborate and provide solutions to on-the-ground needs in a respectful and inclusive environment. The Codefest provides resources to address environmental challenges, such as participation in training on Environmental Data Science and cyberinfrastructure. You will work on a cloud-based, highly secure platform that allows for the seamless integration of data sets and analytical tools. The Codefest encourages individuals participating to create a solution in the form of a research project, computer code, and models (individually and/or collectively, a “Solution”).
+
+## How to Participate
+
+You will join a team of environmental scientists, data experts, and coders to explore curated data, consider the objectivity of the data, propose a scientific question that can be addressed with all or some of the data sets, and analyze the data in an attempt to answer your scientific question by the end of the event. You will present your Solution to the event community. Earth Lab and ESIIL will provide environmental data, cyberinfrastructure, cyberinfrastructure and data analytics training, and technical support. The team members of the winning Solution will receive a small monetary award. Details regarding how the winning Solution will be chosen and how the prize will be managed are outlined in the Official Rules for the Codefest (“Official Rules”).
+
+## Representations and Warranties
+
+By and through Your participation in the Codefest, You represent and warrant the following:
+
+- You have read, understand, and agree to abide by the Code of Conduct and Respectful Inclusive Collaboration Guidelines for the Forest Carbon Codefest (“Code of Conduct”) and the Official Rules.
+- Any decisions concerning the Code of Conduct, Official Rules, or any other matter relating to this Codefest by the University is final and binding on all Participants.
+
+# Codefest Assets
+
+## 5.1 Access and Use
+By participating in the Codefest, You may receive access to certain datasets, webinars, and/or other copyrighted materials (collectively, the “Codefest Assets”). You agree to follow all licenses, restrictions, and other instructions provided to You with the Codefest Assets.
+
+## 5.2 Disclaimer
+The Codefest Assets are provided “as is” without warranty of any kind, either express or implied, including, without limitation, any implied warranties of merchantability and fitness for a particular purpose. Without limiting the foregoing, the University does not warrant that the Materials will be suitable for Your Solution or that the operation or supply of the Codefest Assets will be uninterrupted or error free.
+
+## 5.3 Restrictions
+You agree not to access or use the Codefest Assets in a manner that may interfere with any other participants’ or users’ use of such assets, unless provided with express written consent by the University. Your access to and use of the Codefest Assets may be limited, throttled, or terminated at any time at the sole discretion of the University.
+
+# Intellectual Property
+
+For purposes of this Agreement, “Intellectual Property” includes all copyright, patent, trademark, trade secret and other intellectual property rights.
+
+## 6.1 Solution Publication
+You agree to make Your Solution publicly available in GitHub under the MIT open-source license within five (5) months from the end of the Codefest.
+
+## 6.2 Government Rights
+In consideration of the funding provided by NSF for the Codefest, You hereby grant and agree to grant to the U.S. Government (i) a nonexclusive, non-transferable, irrevocable, royalty-free license to exercise or have exercised for or on behalf of the U.S. throughout the world all the exclusive rights provided by copyright in any copyrightable intellectual property that You create during the Codefest and (ii) a nonexclusive, non-transferable, irrevocable, paid-up license to practice, or have practiced for or on its behalf, any invention created by You during the Codefest throughout the world.
+
+## 6.3 NSF Agreement and Invention Ownership
+You acknowledge that the Codefest is subject to NSF’s Cooperative Agreement Terms and Conditions effective May 12, 2023. As such, the U.S. Government may be entitled to own any invention that You create during the Codefest as further outlined within 37 CFR 401 and the NSF Proposal & Award Policies and Procedures Guide. In such event, You agree to assign any invention created by You during the Codefest to the U.S. Government and to reasonably cooperate with the University and NSF to accomplish the same.
+
+## 6.4 Representations and Warranties
+You represent and warrant that You are legally entitled to grant the above licenses and other intellectual property rights as outlined in Sections 6.1, 6.2, and 6.3. If You are an individual, and if Your employer(s) and/or another third party has rights to Intellectual Property that You create that includes Your Solution, You represent that You have received permission to participate in the Codefest on behalf of that employer or third party and that Your employer or the third party has waived such rights for Your contributions.
+
+## 6.5 Originality and Third-Party Materials
+You represent that Your Solution is Your original creation. If you obtain permission under Section 6.5 to include third-party materials, You represent that Your Solution includes complete details of any third-party license or other restriction (including, but not limited to, related patents and trademarks) of which You are aware and which are associated with any part of Your Solution. You represent and warrant that You will not submit any materials to the University that You know or believe to have components that are malicious or harmful. You represent that You will perform a reasonable amount of due diligence in order to be properly informed of third-party licenses, infringing materials, or harmful content associated with any part of Your Solution.
+
+## 6.6 Submission of External Work
+Should You wish to submit work that is not Your original creation during the Codefest (and that is not a Codefest Asset), You may ask for permission from the University to incorporate such work into Your Solution. To request such permission, identify the complete details of the materials you wish to use, including any licenses or other restrictions (including, but not limited to, related patents, trademarks, and license agreements) of which You are personally aware. Request for permission to add materials created outside of the Codefest must be submitted in advance of the Codefest to: Tyler McIntosh; [tyler.l.mcintosh@colorado.edu](mailto:tyler.l.mcintosh@colorado.edu).
+
+## 6.7 Notification of Changes
+You agree to notify the University of any facts or circumstances of which You become aware that would make these representations inaccurate in any respect. You agree to notify the University of any administrative or court proceeding which involve Your Solution.
+
+# Limitation of Liability
+
+TO THE EXTENT ALLOWED BY LAW, IN NO EVENT SHALL THE UNIVERSITY, ITS PARTNERS, LICENSORS, SERVICE PROVIDERS, OR ANY OF THEIR RESPECTIVE OFFICERS, DIRECTORS, AGENTS, EMPLOYEES OR REPRESENTATIVES, BE LIABLE FOR DIRECT, INCIDENTAL, CONSEQUENTIAL, EXEMPLARY OR PUNITIVE DAMAGES ARISING OUT OF OR IN CONNECTION WITH THE HACKATHON OR THIS AGREEMENT (HOWEVER ARISING, INCLUDING NEGLIGENCE). IF YOU HAVE A DISPUTE WITH ANY PARTICIPANT OR ANY OTHER THIRD PARTY, YOU RELEASE THE UNIVERSITY, ITS, PARTNERS, LICENSORS, AND SERVICE PROVIDERS, AND EACH OF THEIR RESPECTIVE OFFICERS, DIRECTORS, AGENTS, EMPLOYEES AND REPRESENTATIVES FROM ANY AND ALL CLAIMS, DEMANDS AND DAMAGES (ACTUAL AND CONSEQUENTIAL) OF EVERY KIND AND NATURE ARISING OUT OF OR IN ANY WAY CONNECTED WITH SUCH DISPUTES. YOU AGREE THAT ANY CLAIMS AGAINST UNIVERSITY ARISING OUT OF THE HACKATHON OR THIS AGREEMENT MUST BE FILED WITHIN ONE YEAR AFTER SUCH CLAIM AROSE; OTHERWISE, YOUR CLAIM IS PERMANENTLY BARRED.
+
+# Not an Offer or Contract of Employment
+
+Under no circumstances will Your participation in the Codefest or anything in this Agreement be construed as an offer or contract of employment with the University.
+
+# Additional Terms
+
+- You must be at least eighteen (18) years of age to participate in the Codefest. The Codefest is subject to applicable federal, state, and local laws.
+- The University reserves the right to permanently disqualify any person from the Codefest that it reasonably believes has violated this Agreement, the Code of Conduct, and/or the Official Rules.
+- Any attempt to deliberately damage the Codefest or the operation thereof is unlawful and subject to legal action by the University, which may seek damages to the fullest extent permitted by law.
+- The University assumes no responsibility for any injury or damage to Your or any other person’s computer relating to or resulting from entering or downloading materials or software in connection with the Codefest. 
+- The University is not responsible for telecommunications, network, electronic, technical, or computer failures of any kind; for inaccurate transcription of entry information; for any human or electronic error; or for Solutions that are stolen, misdirected, garbled, delayed, lost, late, damaged, or returned.
+- The University reserves the right to cancel, modify, or suspend the Codefest or any element thereof (including, without limitation, this Agreement) without notice in any manner and for any reason (including, without limitation, in the event of any unanticipated occurrence that is not fully addressed in this Agreement).
+- The University may prohibit any person from participating in the Codefest, if such person shows a disregard for this Agreement; acts with an intent to annoy, abuse, threaten, or harass any other entrant or any agents or representatives of the University (or any associated, partners, licensors, or service providers for the University); or behaves in any other disruptive manner (as determined by the University in its sole discretion).
+- Nothing contained in this Agreement shall be construed as an express or implied waiver by University of its governmental immunity or of the governmental immunity of the State of Colorado.
+- Your Solutions shall not contain any item(s) that are either export-controlled under the International Traffic in Arms Regulations, or that appear on the Commerce Control List (except as EAR99) of the Export Administration Regulations.
+
+# Dispute Resolution
+
+This Agreement and the Codefest shall be governed and construed in accordance with and governed by the laws of the state of Colorado without giving effect to conflict of law provisions.
+
+# Entire Agreement
+
+This Agreement, along with the Official Rules, and the Event Code of Conduct, constitutes the entire agreement between the University and You with respect to the Codefest and supersedes all previous or contemporaneous oral or written agreements concerning the Codefest. In the event of a conflict between this Agreement, the Official Rules and/or the Event Code of Conduct, the conflict shall be resolved with the following order of precedence:
+
+1. This Agreement
+2. The Official Rules
+3. The Event Code of Conduct
+
+# Severability
+
+The invalidity, illegality, or unenforceability of any one or more phrases, sentences, clauses, or sections in this Agreement does not affect the remaining portions of this Agreement.
+
+If you have questions about the Codefest, please contact Tyler McIntosh at [tyler.l.mcintosh@colorado.edu](mailto:tyler.l.mcintosh@colorado.edu).
diff --git a/docs/resources/post_meeting_notes.md b/docs/resources/post_meeting_notes.md
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+# Post-Meeting Notes Template
+
+## Meeting Details
+- **Date:**
+- **Time:**
+- **Location:**
+- **Facilitator:**
+
+## Attendees
+- List of attendees
+
+## Agenda
+
+### 1. Review of Meeting Goals
+- Recap the primary objectives and if they were met.
+
+### 2. Manuscript Development
+- Discuss the status of current manuscript drafts.
+- Assign writing and editing tasks for different sections of the manuscript.
+- Set deadlines for draft completion and review.
+
+### 3. Research Highlights
+- Identify key findings and outcomes that should be emphasized in the publications.
+- Discuss any new research insights that emerged from the meeting.
+
+### 4. Publication Strategy
+- Decide on target journals or conferences for publication submission.
+- Discuss authorship order and contributions.
+- Plan for any additional data or research needed to strengthen the manuscript.
+
+### 5. Editing and Review Process
+- Establish a peer-review process within the group for initial feedback.
+- Assign members to focus on specific aspects of editing, such as clarity, grammar, and technical accuracy.
+- Agree on a schedule for review rounds to ensure timely submission.
+
+### 6. Responsibilities and Expectations
+- Clearly define what is expected from each member before the next meeting.
+- Discuss communication methods for progress updates and questions.
+
+### 7. Closing Remarks
+- Summarize the discussion and confirm the action plan.
+- Reiterate the importance of meeting the set deadlines and maintaining communication.
+
+## Action Items
+- [ ] Draft introduction section: Responsible person(s) - Deadline
+- [ ] Compile and analyze additional data: Responsible person(s) - Deadline
+- [ ] Draft methodology section: Responsible person(s) - Deadline
+- ...
+- [ ] Coordinate manuscript peer review: Responsible person(s) - Deadline
+
+## Next Steps
+- Define the timeline for the submission process.
+- Schedule follow-up meetings or check-ins to monitor progress.
+
+## Notes
+- (Additional notes, comments, or observations made during the meeting.)
+
diff --git a/docs/resources/pre_meeting_notes.md b/docs/resources/pre_meeting_notes.md
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+# Pre-Meeting Notes
+
+## Meeting Details
+- **Date:** 
+- **Time:**
+- **Location:**
+- **Facilitator:**
+
+## Attendees
+- List of attendees
+
+## Agenda
+
+### 1. Opening Remarks
+- Brief welcome and overview of the meeting's objectives.
+
+### 2. Introductions
+- Roundtable introductions for all attendees.
+- Share a personal note or interesting fact to foster camaraderie.
+
+### 3. Planning
+- Discuss the agenda for the primary meetings.
+- Outline the key topics and issues to address.
+- Assign roles for note-taking, timekeeping, and facilitation in primary meetings.
+
+### 4. Goal Setting
+- Establish clear, actionable goals for the upcoming period.
+- Identify specific outcomes desired from the primary meetings.
+- Agree on metrics or indicators of success for these goals.
+
+### 5. Camaraderie Building
+- Icebreaker activity or team-building exercise.
+- Share expectations and aspirations for the group's progress.
+- Highlight the importance of collaboration and mutual support.
+
+### 6. Open Discussion
+- Allow for any additional topics, concerns, or ideas to be brought forward.
+
+### 7. Closing Remarks
+- Summarize the discussions and confirm the next steps.
+- Confirm dates and times for primary meetings.
+- Express appreciation for participation.
+
+## Action Items
+- [ ] Action item 1: Responsible person(s) - Deadline
+- [ ] Action item 2: Responsible person(s) - Deadline
+- ...
+
+## Notes
+- (Any additional notes or comments about the meeting.)
+
diff --git a/docs/resources/stac_mount_save.md b/docs/resources/stac_mount_save.md
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+The art of making a data cube
+================
+Ty Tuff, ESIIL Data Scientist
+2023-10-27
+
+``` r
+
+#library(Rcpp)
+library(sf)
+library(gdalcubes)
+library(rstac)
+library(gdalUtils)
+library(terra)
+library(rgdal)
+library(reshape2)
+library(osmdata)
+library(terra)
+library(dplyr)
+library(stars)
+library(ggplot2)
+library(colorspace)
+library(geos)
+library(osmdata)
+library(ggthemes)
+library(tidyr)
+gdalcubes_options(parallel = 8)
+
+sf::sf_extSoftVersion()
+##           GEOS           GDAL         proj.4 GDAL_with_GEOS     USE_PROJ_H 
+##       "3.11.0"        "3.5.3"        "9.1.0"         "true"         "true" 
+##           PROJ 
+##        "9.1.0"
+gdalcubes_gdal_has_geos()
+## [1] TRUE
+
+library(osmdata)
+library(dplyr)
+library(sf)
+library(terra)
+library(tidyterra)
+library(glue)
+library(ggplot2)
+library(ggthemes)
+library(stars)
+library(magrittr)
+library(landsat)
+```
+
+# The philosophy of moving data in the cloud
+
+The philosophy of moving data in the cloud represents a paradigm shift
+in how we approach data within our analytical processes. Instead of the
+traditional method of transferring entire datasets to our local
+environments, the cloud encourages a more efficient model: bring your
+analysis to the data. This approach minimizes data movement and
+leverages the cloud’s computational power and scalability. By utilizing
+cloud-native tools and services, we can run our analyses directly on the
+data where it resides, selectively accessing and processing only what is
+necessary. This not only streamlines workflows but also significantly
+reduces overheads related to data transfer and storage management. In
+essence, the focus is on diverting computational resources to the data
+rather than the cumbersome and resource-intensive practice of moving
+large datasets to and fro.
+
+## ‘To Make’ or ‘To Take’ a photo
+
+The distinction between making and taking a photograph lies in the
+approach and intent behind the camera. Taking a photo is often a
+reactive process, where the photographer captures moments as they
+naturally unfold, seizing the spontaneity of life without alteration.
+It’s a passive form of photography where the emphasis is on the right
+timing and the natural interplay of elements within the frame. On the
+other hand, making a photo is a proactive and deliberate act. It is akin
+to craftsmanship, where a professional photographer starts with a
+concept and utilizes a variety of tools and techniques to stage and
+construct the desired scene. They actively manipulate lighting,
+composition, and subjects to create a photograph that aligns with their
+pre-visualized artistic vision. While both methods use a camera to
+produce a photograph, making a photo involves a creation process,
+whereas taking a photo is about finding the scene.
+
+David Yarrow is a famous photographer who ‘makes’ his photographs.
+![](../assets/esiil_content/stac_mount_save/David-Yarrow-sorrel-sky-gallery-Photographic-Print-Cindys-Shotgun-Wedding.png)
+![](../assets/esiil_content/stac_mount_save/bison.png)
+
+## What does it mean to ‘make’ a data cube?
+
+The artistry of Ansel Adams’ photography serves as a compelling analogy
+for the meticulous craft of building a data cube from cloud data sources
+using tools like STAC and GDAL VSI. Just as Adams would survey the
+vastness of a landscape, discerning the interplay of light and shadow
+upon the mountains before him, a data architect surveys the expanse of
+available data. In this analogy, the raw data are the majestic mountains
+and sweeping landscapes waiting to be captured. The STAC collection acts
+as the photographer’s deliberate choice of scene, pointing the camera
+lens—our data tools—towards the most telling and coherent dataset.
+
+![](../assets/stac_mount_save/Ansel_Adams_datacube.png) Just as Adams’
+photographs are more than mere records of a landscape, but rather a
+confluence of his vision, technique, and the scene’s natural beauty, so
+too is the data cube more than the sum of its parts. It is the artful
+synthesis of information, crafted and composed with the skill and intent
+of an artist, producing not just a tool for analysis but a harmonized,
+data-driven portrait of the world it represents. The builder of the data
+cube is, indeed, an artist, and the data cube their masterpiece,
+revealing not just data, but a story, a perspective, a landscape sewn
+from the raw material of cloud-sourced information.
+
+As Adams would adjust his viewfinder, setting the boundaries of his
+photographic frame, the data builder sets the view window, filtering and
+transferring relevant data to their own medium, akin to Adams’ film.
+This is where the raw data is transformed, organized into the structured
+form of a data frame or data cube, a process not unlike the careful
+development of a photograph in a darkroom. Here, the data cube creator,
+much like Adams with his careful dodging and burning, harmonizes
+disparate elements into a cohesive whole, each decision reflecting an
+intention and vision for the final product.
+
+## 1) The Rat through the Snake Problem: Scalability with Cloud Computing
+
+Just like a snake that swallows a rat, traditional computing systems
+often struggle to process the large volumes of environmental data —
+they’re constrained by their static hardware limitations. Cloud
+computing introduces a python-esque capability: massive scalability. By
+migrating to the cloud, we essentially make the snake bigger, allowing
+it to handle larger “prey.” Scalable computers in the cloud can grow
+with the demand, providing the necessary computational power to process
+extensive datasets, which is vital in a field where data volumes are
+increasing exponentially.
+
+![Raster through a snake](../assets/esiil_content/stac_mount_save/mouseinsnake.png)
+
+## 2) The Antelope through the Python Problem: Streamlining with GDAL VSI
+
+As we scale up, we encounter a new challenge: trying to pass an antelope
+through a python — a metaphor for the next level of complexity in data
+processing. The sheer size and complexity of the data can become
+overwhelming. This is where GDAL’s Virtual File System (VSI) becomes our
+ecological adaptation. VSI allows us to access remote data transparently
+and more efficiently. Instead of ingesting the entire “antelope,” VSI
+enables the “python” to dynamically access and process only the parts of
+the data it needs, when it needs them, much like constriction before
+digestion. This selective access minimizes the need for local storage
+and expedites the data handling process.
+
+![Antelope through a Python](../assets/esiil_content/stac_mount_save/antelopeinpython.png)
+
+## 3) Drinking from a Fire Hose: Accelerated Inference with AI and ML
+
+Once we’ve enabled the flow of large amounts of digestible data, we
+encounter the metaphorical challenge of drinking from a fire hose. The
+data, now flowing and accessible, is immense and rapid — posing a
+challenge not just to store and process, but to understand and derive
+meaning from in real-time. This is where artificial intelligence (AI)
+and machine learning (ML) step in. These technologies act as a
+sophisticated filtration system, enabling us to drink safely and
+beneficially from the torrent. AI and ML can analyze patterns, make
+predictions, and infer insights at a pace that keeps up with the fast
+stream of data, turning raw information into actionable knowledge.
+
+![Inference through a firehose](../assets/esiil_content/stac_mount_save/drink-firehose.png)
+
+By addressing these three pivotal challenges with cloud computing, GDAL
+VSI, and AI/ML, we not only manage to consume the data effectively but
+also transform our capabilities in environmental data science. We can
+move from mere data ingestion to meaningful data interpretation, all at
+a scale and speed necessary for impactful environmental analysis.
+
+### Mounting data
+
+A void-filled Digital Elevation Model (DEM) is a comprehensive
+topographical representation where any missing data points, known as
+voids, have been filled in. These voids can occur due to various
+reasons, such as clouds or technical errors during data collection. In a
+void-filled DEM, these gaps are interpolated or estimated using the
+surrounding data to create a continuous, seamless surface model. This
+process enhances the utility and accuracy of the DEM for hydrological
+modeling, terrain analysis, and other geographical applications. The
+HydroSHEDS website
+(https://www.hydrosheds.org/hydrosheds-core-downloads) provides access
+to high-quality, void-filled DEM datasets like the
+DEM_continuous_CONUS_15s, which users can download and easily integrate
+into spatial analysis workflows using tools such as ‘terra’ in R,
+allowing for sophisticated environmental and geographical research and
+planning.
+
+``` r
+# Record start time
+a <- Sys.time()  
+
+# Create a string with the file path using glue, then download and read the DEM file as a raster object
+
+DEM_continuous_CONUS_15s <- glue(
+  "/vsizip/vsicurl/", #magic remote connection 
+  "https://data.hydrosheds.org/file/hydrosheds-v1-dem/hyd_na_dem_15s.zip", #copied link to download location
+  "/hyd_na_dem_15s.tif") %>% #path inside zip file
+  terra::rast()  
+
+# The 'glue' function constructs the file path string, which is then passed to 'terra::rast()' to read the DEM file into R as a raster layer. '/vsizip/vsicurl/' is a special GDAL virtual file system syntax that allows reading directly from a zipped file on a remote server.
+
+# Record end time and calculate the time difference
+b <- Sys.time()  
+difftime(b, a) 
+## Time difference of 4.603666 secs
+
+# The resulting raster object is stored in 'DEM_continuous_CONUS_15s', which now contains the void-filled DEM data ready for use
+
+DEM_continuous_CONUS_15s  # Prints out the details of the 'DEM_continuous_CONUS_15s' raster object
+## class       : SpatRaster 
+## dimensions  : 13920, 20640, 1  (nrow, ncol, nlyr)
+## resolution  : 0.004166667, 0.004166667  (x, y)
+## extent      : -138, -52, 5, 63  (xmin, xmax, ymin, ymax)
+## coord. ref. : lon/lat WGS 84 (EPSG:4326) 
+## source      : hyd_na_dem_15s.tif 
+## name        : Band_1
+
+# output is a SpatRaster, which is the object type associated with the 'terra' package. 
+```
+
+Continuous DEM for North America
+
+``` r
+# Record start time
+a <- Sys.time()
+
+ggplot() +
+  geom_spatraster(data=DEM_continuous_CONUS_15s) +
+  theme_tufte()
+```
+
+![](stac_mount_save_files/figure-gfm/DEM_plot-1.png)
+
+``` r
+
+b <- Sys.time()
+difftime(b, a)
+## Time difference of 52.49061 secs
+```
+
+Calculate Slope from that DEM
+
+``` r
+SLOPE_continuous_CONUS_15s <-  terra::terrain(DEM_continuous_CONUS_15s, "slope") 
+
+SLOPE_continuous_CONUS_15s
+## class       : SpatRaster 
+## dimensions  : 13920, 20640, 1  (nrow, ncol, nlyr)
+## resolution  : 0.004166667, 0.004166667  (x, y)
+## extent      : -138, -52, 5, 63  (xmin, xmax, ymin, ymax)
+## coord. ref. : lon/lat WGS 84 (EPSG:4326) 
+## source(s)   : memory
+## name        :    slope 
+## min value   :  0.00000 
+## max value   : 56.98691
+```
+
+``` r
+# Record start time
+a <- Sys.time()
+
+ggplot() +
+  geom_spatraster(data=SLOPE_continuous_CONUS_15s) +
+  theme_tufte()
+```
+
+![](stac_mount_save_files/figure-gfm/SLOPE_plot-1.png)
+
+``` r
+
+b <- Sys.time()
+difftime(b, a)
+## Time difference of 3.859545 secs
+```
+
+Calculate aspect from DEM
+
+``` r
+ASPECT_continuous_CONUS_15s <-  terra::terrain(DEM_continuous_CONUS_15s, "aspect") 
+ASPECT_continuous_CONUS_15s
+## class       : SpatRaster 
+## dimensions  : 13920, 20640, 1  (nrow, ncol, nlyr)
+## resolution  : 0.004166667, 0.004166667  (x, y)
+## extent      : -138, -52, 5, 63  (xmin, xmax, ymin, ymax)
+## coord. ref. : lon/lat WGS 84 (EPSG:4326) 
+## source(s)   : memory
+## name        : aspect 
+## min value   :      0 
+## max value   :    360
+```
+
+``` r
+# Record start time
+a <- Sys.time()
+
+ggplot() +
+  geom_spatraster(data=ASPECT_continuous_CONUS_15s) +
+  theme_tufte()
+```
+
+![](stac_mount_save_files/figure-gfm/ASPECT_plot-1.png)
+
+``` r
+
+b <- Sys.time()
+difftime(b, a)
+## Time difference of 3.650267 secs
+```
+
+Create a cube from those layers!
+
+``` r
+mini_stack <- c(DEM_continuous_CONUS_15s, SLOPE_continuous_CONUS_15s,ASPECT_continuous_CONUS_15s)
+mini_stack
+## class       : SpatRaster 
+## dimensions  : 13920, 20640, 3  (nrow, ncol, nlyr)
+## resolution  : 0.004166667, 0.004166667  (x, y)
+## extent      : -138, -52, 5, 63  (xmin, xmax, ymin, ymax)
+## coord. ref. : lon/lat WGS 84 (EPSG:4326) 
+## sources     : hyd_na_dem_15s.tif  
+##               memory  
+##               memory  
+## names       : Band_1,    slope, aspect 
+## min values  :     ? ,  0.00000,      0 
+## max values  :     ? , 56.98691,    360
+```
+
+Reproject and return the bounding box coordinates for our Area of
+Interest
+
+``` r
+# Transform the filtered geometry to EPSG:4326 and store its bounding box
+# Record start time
+a <- Sys.time()
+
+DEM_continuous_CONUS_15s |>
+stars::st_as_stars() |> 
+  st_transform("EPSG:4326") |>
+  st_bbox() -> bbox_4326
+
+
+DEM_continuous_CONUS_15s |>
+stars::st_as_stars() |> 
+  st_transform("EPSG:32618") |>
+  st_bbox() -> bbox_32618
+
+b <- Sys.time()
+difftime(b, a)
+## Time difference of 3.7653 mins
+```
+
+Get a polygon for Boulder County, reproject, and return bounding box.
+This is so I can make a smaller search in the stac catalog.
+
+``` r
+boulder_county <- getbb("boulder, co", format_out="sf_polygon")
+
+boulder_county$multipolygon |> 
+  st_transform(crs =4326 ) |>
+  st_bbox() -> bbox_4326_boulder
+
+boulder_county$multipolygon |> 
+  st_transform(crs =32720 ) |>
+  st_bbox() -> bbox_32720_boulder
+```
+
+Get a polygon for the United States and crop it to be the same size as
+the DEM above.
+
+``` r
+aoi <- getbb("United States", format_out="sf_polygon")
+
+conus <- aoi$multipolygon |>
+  st_crop(bbox_4326)
+
+
+ggplot(data=conus) +
+  geom_sf()
+```
+
+![](stac_mount_save_files/figure-gfm/conus_bounding_box-1.png)
+
+Search the Stac catalog.
+
+STAC, or SpatioTemporal Asset Catalog, is an open-source specification
+designed to standardize the way geospatial data is indexed and
+discovered. Developed by Element 84 among others, it facilitates better
+interoperability and sharing of geospatial assets by providing a common
+language for describing them. STAC’s flexible design allows for easy
+cataloging of data, making it simpler for individuals and systems to
+search and retrieve geospatial information. By effectively organizing
+data about the Earth’s spatial and temporal characteristics, STAC
+enables users to harness the full power of the cloud and modern data
+processing technologies, optimizing the way we access and analyze
+environmental data on a global scale.
+
+``` r
+ stac("https://earth-search.aws.element84.com/v1") |>
+       get_request()
+## ###STACCatalog
+## - id: earth-search-aws
+## - description: A STAC API of public datasets on AWS
+## - field(s): stac_version, type, id, title, description, links, conformsTo
+```
+
+Element 84’s Earth Search is a STAC compliant search and discovery API
+that offers users access to a vast collection of geospatial open
+datasets hosted on AWS. It serves as a centralized search catalog
+providing standardized metadata for these open datasets, designed to be
+freely used and integrated into various applications. Alongside the API,
+Element 84 also provides a web application named Earth Search Console,
+which is map-centric and allows users to explore and visualize the data
+contained within the Earth Search API’s catalog. This suite of tools is
+part of Element 84’s initiative to make geospatial data more accessible
+and actionable for a wide range of users and applications.
+
+``` r
+collection_formats()
+##    CHIRPS_v2_0_daily_p05_tif | Image collection format for CHIRPS v 2.0 daily
+##                              | global precipitation dataset (0.05 degrees
+##                              | resolution) from GeoTIFFs, expects list of .tif
+##                              | or .tif.gz files as input. [TAGS: CHIRPS,
+##                              | precipitation]
+##  CHIRPS_v2_0_monthly_p05_tif | Image collection format for CHIRPS v 2.0 monthly
+##                              | global precipitation dataset (0.05 degrees
+##                              | resolution) from GeoTIFFs, expects list of .tif
+##                              | or .tif.gz files as input. [TAGS: CHIRPS,
+##                              | precipitation]
+##            ESA_CCI_SM_ACTIVE | Collection format for ESA CCI soil moisture
+##                              | active product (version 4.7) [TAGS: Soil
+##                              | Moisture, ESA, CCI]
+##           ESA_CCI_SM_PASSIVE | Collection format for ESA CCI soil moisture
+##                              | passive product (version 4.7) [TAGS: Soil
+##                              | Moisture, ESA, CCI]
+##    GPM_IMERG_3B_DAY_GIS_V06A | Collection format for daily
+##                              | IMERG_3B_DAY_GIS_V06A data [TAGS: Precipitation,
+##                              | GPM, IMERG]
+##                      L8_L1TP | Collection format for Landsat 8 Level 1 TP
+##                              | product [TAGS: Landsat, USGS, Level 1, NASA]
+##                        L8_SR | Collection format for Landsat 8 surface
+##                              | reflectance product [TAGS: Landsat, USGS, Level
+##                              | 2, NASA, surface reflectance]
+##                        MAXAR | Preliminary collection format for MAXAR open
+##                              | data, visual only (under development) [TAGS: ]
+##                      MxD09GA | Collection format for selected bands from the
+##                              | MODIS MxD09GA (Aqua and Terra) product [TAGS:
+##                              | MODIS, surface reflectance]
+##                      MxD10A2 | Collection format for selected bands from the
+##                              | MODIS MxD10A2 (Aqua and Terra) v006 Snow Cover
+##                              | product [TAGS: MODIS, Snow Cover]
+##                      MxD11A1 | Collection format for selected bands from the
+##                              | MODIS MxD11A2 (Aqua and Terra) v006 Land Surface
+##                              | Temperature product [TAGS: MODIS, LST]
+##                      MxD11A2 | Collection format for selected bands from the
+##                              | MODIS MxD11A2 (Aqua and Terra) v006 Land Surface
+##                              | Temperature product [TAGS: MODIS, LST]
+##                      MxD13A2 | Collection format for selected bands from the
+##                              | MODIS MxD13A2 (Aqua and Terra) product [TAGS:
+##                              | MODIS, VI, NDVI, EVI]
+##                      MxD13A3 | Collection format for selected bands from the
+##                              | MODIS MxD13A3 (Aqua and Terra) product [TAGS:
+##                              | MODIS, VI, NDVI, EVI]
+##                      MxD13Q1 | Collection format for selected bands from the
+##                              | MODIS MxD13Q1 (Aqua and Terra) product [TAGS:
+##                              | MODIS, VI, NDVI, EVI]
+##                      MxD14A2 | Collection format for the MODIS MxD14A2 (Aqua
+##                              | and Terra) product [TAGS: MODIS, Fire]
+## PlanetScope_3B_AnalyticMS_SR | Image collection format for PlanetScope 4-band
+##                              | scenes [TAGS: PlanetScope, BOA, Surface
+##                              | Reflectance]
+##                Sentinel2_L1C | Image collection format for Sentinel 2 Level 1C
+##                              | data as downloaded from the Copernicus Open
+##                              | Access Hub, expects a list of file paths as
+##                              | input. The format works on original ZIP
+##                              | compressed as well as uncompressed imagery.
+##                              | [TAGS: Sentinel, Copernicus, ESA, TOA]
+##            Sentinel2_L1C_AWS | Image collection format for Sentinel 2 Level 1C
+##                              | data in AWS [TAGS: Sentinel, Copernicus, ESA,
+##                              | TOA]
+##                Sentinel2_L2A | Image collection format for Sentinel 2 Level 2A
+##                              | data as downloaded from the Copernicus Open
+##                              | Access Hub, expects a list of file paths as
+##                              | input. The format should work on original ZIP
+##                              | compressed as well as uncompressed imagery.
+##                              | [TAGS: Sentinel, Copernicus, ESA, BOA, Surface
+##                              | Reflectance]
+##          Sentinel2_L2A_THEIA | Image collection format for Sentinel 2 Level 2A
+##                              | data as downloaded from Theia. [TAGS: Sentinel,
+##                              | ESA, Flat Reflectance, Theia]
+```
+
+Building a stac collection by aiming your camera at the landscape
+
+Creating a STAC collection is akin to a photographer framing a shot; the
+landscape is rich with diverse data, mirroring a scene bustling with
+potential subjects, colors, and light. Just as a photographer selects a
+portion of the vista to capture, focusing on elements that will compose
+a compelling image, a data scientist must similarly navigate the vast
+data terrain. They must ‘point their camera’ judiciously, ensuring that
+the ‘frame’ encapsulates the precise data needed. This careful selection
+is crucial, as it determines the relevance and quality of the data
+collection, much like the photographer’s choice dictates the story a
+photograph will tell.
+
+![](../assets/esiil_content/stac_mount_save/Ansel_adams_Jackson_hole.png)
+
+``` r
+# Record start time
+a <- Sys.time()
+
+# Initialize STAC connection
+s = stac("https://earth-search.aws.element84.com/v0")
+
+
+# Search for Sentinel-2 images within specified bounding box and date range
+#22 Million items
+items = s |>
+    stac_search(collections = "sentinel-s2-l2a-cogs",
+                bbox = c(bbox_4326_boulder["xmin"], 
+                         bbox_4326_boulder["ymin"],
+                         bbox_4326_boulder["xmax"], 
+                         bbox_4326_boulder["ymax"]), 
+                datetime = "2021-05-15/2021-05-16") |>
+    post_request() |>
+    items_fetch(progress = FALSE)
+
+# Print number of found items
+length(items$features)
+## [1] 1
+
+# Prepare the assets for analysis
+library(gdalcubes)
+assets = c("B01", "B02", "B03", "B04", "B05", "B06", 
+           "B07", 
+           "B08", "B8A", "B09", "B11", "B12", "SCL")
+s2_collection = stac_image_collection(items$features, asset_names = assets,
+property_filter = function(x) {x[["eo:cloud_cover"]] < 20}) #all images with less than 20% clouds
+
+b <- Sys.time()
+difftime(b, a)
+## Time difference of 0.4706092 secs
+
+# Display the image collection
+s2_collection
+## Image collection object, referencing 1 images with 13 bands
+## Images:
+##                       name      left      top   bottom     right
+## 1 S2B_13TDE_20210516_0_L2A -106.1832 40.65079 39.65576 -104.8846
+##              datetime        srs
+## 1 2021-05-16T18:02:54 EPSG:32613
+## 
+## Bands:
+##    name offset scale unit nodata image_count
+## 1   B01      0     1                       1
+## 2   B02      0     1                       1
+## 3   B03      0     1                       1
+## 4   B04      0     1                       1
+## 5   B05      0     1                       1
+## 6   B06      0     1                       1
+## 7   B07      0     1                       1
+## 8   B08      0     1                       1
+## 9   B09      0     1                       1
+## 10  B11      0     1                       1
+## 11  B12      0     1                       1
+## 12  B8A      0     1                       1
+## 13  SCL      0     1                       1
+```
+
+Setting up your camera and film
+
+The camera through which the data scientist frames the shot is
+multifaceted, akin to the tools and processes they employ. The camera’s
+film, analogous to the data cube, defines the resolution and dimensions
+of the captured data, shaping how the final dataset will be utilized.
+The lens and its settings—focus, aperture, and exposure—determine the
+clarity, depth, and breadth of the captured information, much like the
+algorithms and parameters set by the data scientist dictate the
+granularity and scope of the data cube. The flash, like data enhancement
+techniques, can illuminate hidden details, ensuring that the data cube,
+the final product, is as informative and accurate as the landscape it
+represents.
+
+![](../assets/esiil_content/stac_mount_save/View_Ansel-Adams_Camera.png)
+
+``` r
+# Record start time
+a <- Sys.time()
+
+# Define a specific view on the satellite image collection
+v = cube_view(
+    srs = "EPSG:32720", #this is harder than expected. 
+    dx = 100, 
+    dy = 100, 
+    dt = "P1M", 
+    aggregation = "median", 
+    resampling = "near",
+    extent = list(
+        t0 = "2021-05-15", 
+        t1 = "2021-05-16",
+        left = bbox_32720_boulder[1], 
+        right = bbox_32720_boulder[2],
+        top = bbox_32720_boulder[4], 
+        bottom = bbox_32720_boulder[3]
+    )
+)
+
+b <- Sys.time()
+difftime(b, a)
+## Time difference of 0.002738953 secs
+
+# Display the defined view
+v
+## A data cube view object
+## 
+## Dimensions:
+##                 low             high  count pixel_size
+## t        2021-05-01       2021-05-31      1        P1M
+## y -3103099.52398788 15434400.4760121 185375        100
+## x -3178878.98542359 15369521.0145764 185484        100
+## 
+## SRS: "EPSG:32720"
+## Temporal aggregation method: "median"
+## Spatial resampling method: "near"
+```
+
+Take a picture!
+
+Raster style
+
+``` r
+# Record start time
+a <- Sys.time()
+
+s2_collection |>
+    raster_cube(v) |>
+    select_bands(c( "B04", "B05"))  |>
+  apply_pixel(c("(B05-B04)/(B05+B04)"), names="NDVI") |>
+  write_tif() |>
+  raster::stack() -> x
+x
+## class      : RasterStack 
+## dimensions : 185375, 185484, 34384096500, 1  (nrow, ncol, ncell, nlayers)
+## resolution : 100, 100  (x, y)
+## extent     : -3178879, 15369521, -3103100, 15434400  (xmin, xmax, ymin, ymax)
+## crs        : +proj=utm +zone=20 +south +datum=WGS84 +units=m +no_defs 
+## names      : NDVI
+
+b <- Sys.time()
+difftime(b, a)
+## Time difference of 4.132932 mins
+```
+
+STARS style
+
+``` r
+# Record start time
+a <- Sys.time()
+
+s2_collection |>
+    raster_cube(v) |>
+    select_bands(c("B04","B05"))  |>
+  apply_pixel(c("(B05-B04)/(B05+B04)"), names="NDVI") |>
+  stars::st_as_stars() -> y
+
+b <- Sys.time()
+difftime(b, a)
+## Time difference of 1.459866 mins
+
+y
+## stars_proxy object with 1 attribute in 1 file(s):
+## $NDVI
+## [1] "[...]/filec5982c38536c.nc:NDVI"
+## 
+## dimension(s):
+##      from     to   offset delta                refsys point
+## x       1 185484 -3178879   100 WGS 84 / UTM zone 20S    NA
+## y       1 185375 15434400  -100 WGS 84 / UTM zone 20S    NA
+## time    1      1       NA    NA               POSIXct FALSE
+##                       values x/y
+## x                       NULL [x]
+## y                       NULL [y]
+## time [2021-05-01,2021-06-01)
+```
+
+Extract data
+
+``` r
+# Record start time
+a <- Sys.time()
+
+
+x <- s2_collection |>
+    raster_cube(v) |>
+    select_bands(c("B01", "B02", "B03", "B04", 
+                   "B05", "B06", "B07", "B08", 
+                   "B8A", "B09", "B11", "B12")) |>
+    extract_geom(boulder_county$multipolygon) |>
+    rename(
+        "time" = "time",
+        "443" = "B01",
+        "490" = "B02",
+        "560" = "B03",
+        "665" = "B04",
+        "705" = "B05",
+        "740" = "B06",
+        "783" = "B07",
+        "842" = "B08",
+        "865" = "B8A",
+        "940" = "B09",
+        "1610" = "B11",
+        "2190" = "B12"
+    )
+
+b <- Sys.time()
+difftime(b, a)
+## Time difference of 1.699016 mins
+
+head(x)
+##   FID       time   443   490   560   665   705   740   783   842  865  940 1610
+## 1   1 2021-05-01 11096 10929 10224  9893  9956  9706  9715  9641 9511 8459 5682
+## 2   1 2021-05-01 11631 11282 10550 10234 10288 10031 10032  9988 9828 9153 5802
+## 3   1 2021-05-01 11900 11393 10666 10337 10398 10142 10138 10093 9927 9461 5754
+## 4   1 2021-05-01 11406 10597  9928  9626  9694  9481  9516  9338 9336 8959 5726
+## 5   1 2021-05-01 11399 10939 10237  9905  9978  9738  9746  9633 9555 8925 5831
+## 6   1 2021-05-01 11600 11174 10462 10147 10209  9952  9960  9890 9760 9153 5773
+##   2190
+## 1 3917
+## 2 3981
+## 3 3937
+## 4 4054
+## 5 4097
+## 6 3990
+```
+
+Make a timeseries
+
+``` r
+
+# Record start time
+a <- Sys.time()
+
+items <- s |>
+    stac_search(collections = "sentinel-s2-l2a-cogs",
+                bbox = c(-105.694362,   39.912886,  -105.052774,    40.262785),
+                datetime = "2020-01-01/2022-12-31",
+                limit = 500) %>% 
+    post_request() 
+
+S2.mask = image_mask("SCL", values=c(3,8,9))
+
+col = stac_image_collection(items$features, asset_names = assets, 
+                            property_filter = function(x) {x[["eo:cloud_cover"]] < 30})
+
+v = cube_view(srs = "EPSG:4326",  extent = list(t0 = "2020-01-01", t1 = "2022-12-31",
+              left = -105.694362, right = -105.052774,  top = 40.262785, bottom = 39.912886),
+              dx = 0.001, dy = 0.001, dt = "P1M", aggregation = "median", resampling = "bilinear")
+
+library(colorspace)
+ndvi.col = function(n) {
+  rev(sequential_hcl(n, "Green-Yellow"))
+}
+library(gdalcubes)
+raster_cube(col, v, mask = S2.mask) |>
+    select_bands(c("B04", "B08")) |>
+    apply_pixel("(B08-B04)/(B08+B04)", "NDVI") |>
+    gdalcubes::animate(col = ndvi.col, zlim=c(-0.2,1), key.pos = 1, save_as = "anim.gif", fps = 4)
+## [1] "/Users/ty/Documents/Github/hackathon2023_datacube/docs/code_for_building_cube/anim.gif"
+
+b <- Sys.time()
+difftime(b, a)
+## Time difference of 4.716672 mins
+
+y
+## stars_proxy object with 1 attribute in 1 file(s):
+## $NDVI
+## [1] "[...]/filec5982c38536c.nc:NDVI"
+## 
+## dimension(s):
+##      from     to   offset delta                refsys point
+## x       1 185484 -3178879   100 WGS 84 / UTM zone 20S    NA
+## y       1 185375 15434400  -100 WGS 84 / UTM zone 20S    NA
+## time    1      1       NA    NA               POSIXct FALSE
+##                       values x/y
+## x                       NULL [x]
+## y                       NULL [y]
+## time [2021-05-01,2021-06-01)
+```
+
+![](../assets/esiil_content/stac_mount_save/anim.gif)
+
+Saving Data Cubes to Local Storage There are occasions when we need to
+manipulate data cubes using other software. For such purposes, we can
+save data cubes to our local disk as individual netCDF files or as a
+series of GeoTIFF files. In the case of the latter, each temporal
+segment of the cube is saved as a separate (multiband) GeoTIFF file.
+
+Both netCDF and GeoTIFF formats allow for file size reduction through
+compression and data packing. This process involves transforming double
+precision numbers into smaller integer values using a scale and offset,
+which can be particularly useful for managing disk space (for more
+details, refer to the ?write_ncdf and ?write_tif documentation).
+
+``` r
+gdalcubes_options(ncdf_compression_level = 1)
+write_ncdf(cube, file.path("~/Desktop", basename(tempfile(fileext = ".nc"))))
+gdalcubes_options(ncdf_compression_level = 0)
+```
+
+write_tif() and write_ncdf() both return the path(s) to created file(s)
+as a character vector.
+
+``` r
+items_2020 <- s |>
+    stac_search(collections = "sentinel-s2-l2a-cogs",
+                bbox = c(-105.694362,   39.912886,  -105.052774,    40.262785),
+                datetime = "2020-05-01/2020-06-30") |> 
+    post_request() 
+
+items_2021 <- s |>
+    stac_search(collections = "sentinel-s2-l2a-cogs",
+                bbox = c(-105.694362,   39.912886,  -105.052774,    40.262785),
+                datetime = "2021-05-01/2021-06-30") |> 
+    post_request() 
+
+
+col_2020 = stac_image_collection(items_2020$features, asset_names = assets)
+col_2021 = stac_image_collection(items_2021$features, asset_names = assets)
+
+v_2020 = cube_view(srs = "EPSG:32720",  extent = list(t0 = "2020-05-01", t1 = "2020-06-30",
+              left = bbox_32720_boulder["xmin"], right = bbox_32720_boulder["xmax"],  top = bbox_32720_boulder["ymax"], bottom = bbox_32720_boulder["ymin"]),
+              dx = 100, dy = 100, dt = "P1D", aggregation = "median", resampling = "bilinear")
+
+v_2021 = cube_view(v_2020, extent = list(t0 = "2021-05-01", t1 = "2021-06-30"))
+
+
+max_ndvi_mosaic <- function(col, v) {
+    raster_cube(col, v) |>
+    select_bands(c("B04", "B08")) |>
+    apply_pixel(c("(B08-B04)/(B08+B04)"), names="NDVI") |>
+    reduce_time("max(NDVI)")
+}
+
+suppressPackageStartupMessages(library(stars))
+max_ndvi_mosaic(col_2020, v_2020) -> maxndvi_2020
+
+max_ndvi_mosaic(col_2021, v_2021)  -> maxndvi_2021
+
+maxndvi_2021
+maxndvi_2020
+
+difference = maxndvi_2021 - maxndvi_2020
+difference[difference > -0.15] = NA
+names(difference) <- "Difference of max NDVI (2020 - 2019)"
+```
+
+``` r
+flood_polygon_data3 <- glue("/vsizip/vsicurl/https://data.hydrosheds.org/file/hydrosheds-associated/gloric/GloRiC_v10_shapefile.zip/GloRiC_v10_shapefile/GloRiC_v10.shp") |>
+  st_read() |>
+  st_as_sf(coords = c("lon","lat"))
+
+flood_polygon_data3
+```
+
+``` r
+#st_read("/Users/ty/Downloads/GloRiC_v10_geodatabase/GloRiC_v10.gdb")
+
+flood_polygon_data3 <- glue("/vsizip/vsicurl/https://data.hydrosheds.org/file/hydrosheds-associated/gloric/GloRiC_v10_geodatabase.zip/GloRiC_v10_geodatabase/GloRiC_v10.gdb") |>
+  st_read() |>
+  st_as_sf(coords = c("lon","lat"))
+
+flood_polygon_data3
+```
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diff --git a/docs/resources/stac_mount_save_files/libs/bootstrap/bootstrap-icons.woff b/docs/resources/stac_mount_save_files/libs/bootstrap/bootstrap-icons.woff
new file mode 100644
index 0000000..b26ccd1
Binary files /dev/null and b/docs/resources/stac_mount_save_files/libs/bootstrap/bootstrap-icons.woff differ
diff --git a/docs/resources/stac_mount_save_files/libs/bootstrap/bootstrap.min.css b/docs/resources/stac_mount_save_files/libs/bootstrap/bootstrap.min.css
new file mode 100644
index 0000000..2b6003a
--- /dev/null
+++ b/docs/resources/stac_mount_save_files/libs/bootstrap/bootstrap.min.css
@@ -0,0 +1,10 @@
+/*!
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+ * Copyright 2011-2021 The Bootstrap Authors
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+*
+*/.ansi-black-fg{color:#3e424d}.ansi-black-bg{background-color:#3e424d}.ansi-black-intense-fg{color:#282c36}.ansi-black-intense-bg{background-color:#282c36}.ansi-red-fg{color:#e75c58}.ansi-red-bg{background-color:#e75c58}.ansi-red-intense-fg{color:#b22b31}.ansi-red-intense-bg{background-color:#b22b31}.ansi-green-fg{color:#00a250}.ansi-green-bg{background-color:#00a250}.ansi-green-intense-fg{color:#007427}.ansi-green-intense-bg{background-color:#007427}.ansi-yellow-fg{color:#ddb62b}.ansi-yellow-bg{background-color:#ddb62b}.ansi-yellow-intense-fg{color:#b27d12}.ansi-yellow-intense-bg{background-color:#b27d12}.ansi-blue-fg{color:#208ffb}.ansi-blue-bg{background-color:#208ffb}.ansi-blue-intense-fg{color:#0065ca}.ansi-blue-intense-bg{background-color:#0065ca}.ansi-magenta-fg{color:#d160c4}.ansi-magenta-bg{background-color:#d160c4}.ansi-magenta-intense-fg{color:#a03196}.ansi-magenta-intense-bg{background-color:#a03196}.ansi-cyan-fg{color:#60c6c8}.ansi-cyan-bg{background-color:#60c6c8}.ansi-cyan-intense-fg{color:#258f8f}.ansi-cyan-intense-bg{background-color:#258f8f}.ansi-white-fg{color:#c5c1b4}.ansi-white-bg{background-color:#c5c1b4}.ansi-white-intense-fg{color:#a1a6b2}.ansi-white-intense-bg{background-color:#a1a6b2}.ansi-default-inverse-fg{color:#fff}.ansi-default-inverse-bg{background-color:#000}.ansi-bold{font-weight:bold}.ansi-underline{text-decoration:underline}:root{--quarto-body-bg: #ffffff;--quarto-body-color: #212529;--quarto-text-muted: #6c757d;--quarto-border-color: #dee2e6;--quarto-border-width: 1px;--quarto-border-radius: 0.25rem}.code-copy-button{position:absolute;top:0;right:0;border:0;margin-top:5px;margin-right:5px;background-color:transparent}.code-copy-button:focus{outline:none}pre.sourceCode:hover>.code-copy-button>.bi::before{display:inline-block;height:1rem;width:1rem;content:"";vertical-align:-0.125em;background-image:url('data:image/svg+xml,<svg xmlns="http://www.w3.org/2000/svg" width="16" height="16" fill="rgb(108, 117, 125)" viewBox="0 0 16 16"><path d="M4 1.5H3a2 2 0 0 0-2 2V14a2 2 0 0 0 2 2h10a2 2 0 0 0 2-2V3.5a2 2 0 0 0-2-2h-1v1h1a1 1 0 0 1 1 1V14a1 1 0 0 1-1 1H3a1 1 0 0 1-1-1V3.5a1 1 0 0 1 1-1h1v-1z"/><path d="M9.5 1a.5.5 0 0 1 .5.5v1a.5.5 0 0 1-.5.5h-3a.5.5 0 0 1-.5-.5v-1a.5.5 0 0 1 .5-.5h3zm-3-1A1.5 1.5 0 0 0 5 1.5v1A1.5 1.5 0 0 0 6.5 4h3A1.5 1.5 0 0 0 11 2.5v-1A1.5 1.5 0 0 0 9.5 0h-3z"/></svg>');background-repeat:no-repeat;background-size:1rem 1rem}pre.sourceCode:hover>.code-copy-button-checked>.bi::before{background-image:url('data:image/svg+xml,<svg xmlns="http://www.w3.org/2000/svg" width="16" height="16" fill="rgb(108, 117, 125)" viewBox="0 0 16 16"><path d="M13.854 3.646a.5.5 0 0 1 0 .708l-7 7a.5.5 0 0 1-.708 0l-3.5-3.5a.5.5 0 1 1 .708-.708L6.5 10.293l6.646-6.647a.5.5 0 0 1 .708 0z"/></svg>')}pre.sourceCode:hover>.code-copy-button:hover>.bi::before{background-image:url('data:image/svg+xml,<svg xmlns="http://www.w3.org/2000/svg" width="16" height="16" fill="rgb(13, 110, 253)" viewBox="0 0 16 16"><path d="M4 1.5H3a2 2 0 0 0-2 2V14a2 2 0 0 0 2 2h10a2 2 0 0 0 2-2V3.5a2 2 0 0 0-2-2h-1v1h1a1 1 0 0 1 1 1V14a1 1 0 0 1-1 1H3a1 1 0 0 1-1-1V3.5a1 1 0 0 1 1-1h1v-1z"/><path d="M9.5 1a.5.5 0 0 1 .5.5v1a.5.5 0 0 1-.5.5h-3a.5.5 0 0 1-.5-.5v-1a.5.5 0 0 1 .5-.5h3zm-3-1A1.5 1.5 0 0 0 5 1.5v1A1.5 1.5 0 0 0 6.5 4h3A1.5 1.5 0 0 0 11 2.5v-1A1.5 1.5 0 0 0 9.5 0h-3z"/></svg>')}pre.sourceCode:hover>.code-copy-button-checked:hover>.bi::before{background-image:url('data:image/svg+xml,<svg xmlns="http://www.w3.org/2000/svg" width="16" height="16" fill="rgb(13, 110, 253)"  viewBox="0 0 16 16"><path d="M13.854 3.646a.5.5 0 0 1 0 .708l-7 7a.5.5 0 0 1-.708 0l-3.5-3.5a.5.5 0 1 1 .708-.708L6.5 10.293l6.646-6.647a.5.5 0 0 1 .708 0z"/></svg>')}main ol ol,main ul ul,main ol ul,main ul ol{margin-bottom:1em}body{margin:0}main.page-columns>header>h1.title,main.page-columns>header>.title.h1{margin-bottom:0}@media(min-width: 992px){body .page-columns{display:grid;gap:0;grid-template-columns:[screen-start] 1.5em [screen-start-inset] 5fr [page-start page-start-inset] 35px [body-start-outset] 35px [body-start] 1.5em [body-content-start] minmax(500px, calc(850px - 3em)) [body-content-end] 1.5em [body-end] 35px [body-end-outset] minmax(75px, 145px) [page-end-inset] 35px [page-end] 5fr [screen-end-inset] 1.5em [screen-end]}body.fullcontent:not(.floating):not(.docked) .page-columns{display:grid;gap:0;grid-template-columns:[screen-start] 1.5em [screen-start-inset] 5fr [page-start page-start-inset] 35px [body-start-outset] 35px [body-start] 1.5em [body-content-start] minmax(500px, calc(850px - 3em)) [body-content-end] 1.5em [body-end] 35px [body-end-outset] 35px [page-end-inset page-end] 5fr [screen-end-inset] 1.5em [screen-end]}body.slimcontent:not(.floating):not(.docked) .page-columns{display:grid;gap:0;grid-template-columns:[screen-start] 1.5em [screen-start-inset] 5fr [page-start page-start-inset] 35px [body-start-outset] 35px [body-start] 1.5em [body-content-start] minmax(500px, calc(750px - 3em)) [body-content-end] 1.5em [body-end] 50px [body-end-outset] minmax(0px, 200px) [page-end-inset] 50px [page-end] 5fr [screen-end-inset] 1.5em [screen-end]}body.listing:not(.floating):not(.docked) .page-columns{display:grid;gap:0;grid-template-columns:[screen-start] 1.5em [screen-start-inset 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[body-start] 1.5em [body-content-start] minmax(450px, calc(750px - 3em)) [body-content-end] 1.5em [body-end] 50px [body-end-outset] minmax(0px, 200px) [page-end-inset] 50px [page-end] 5fr [screen-end-inset] 1.5em [screen-end]}body.floating .page-columns{display:grid;gap:0;grid-template-columns:[screen-start] 1.5em [screen-start-inset] 5fr [page-start] minmax(25px, 50px) [page-start-inset] minmax(50px, 150px) [body-start-outset] minmax(25px, 50px) [body-start] 1.5em [body-content-start] minmax(500px, calc(800px - 3em)) [body-content-end] 1.5em [body-end] minmax(25px, 50px) [body-end-outset] minmax(50px, 150px) [page-end-inset] minmax(25px, 50px) [page-end] 5fr [screen-end-inset] 1.5em [screen-end]}body.docked .page-columns{display:grid;gap:0;grid-template-columns:[screen-start] 1.5em [screen-start-inset page-start] minmax(50px, 100px) [page-start-inset] 50px [body-start-outset] 50px [body-start] 1.5em [body-content-start] minmax(500px, calc( 1000px - 3em )) [body-content-end] 1.5em [body-end] 50px [body-end-outset] minmax(0px, 100px) [page-end-inset] 50px [page-end] 5fr [screen-end-inset] 1.5em [screen-end]}body.docked.fullcontent .page-columns{display:grid;gap:0;grid-template-columns:[screen-start] 1.5em [screen-start-inset page-start] minmax(50px, 100px) [page-start-inset] 50px [body-start-outset] 50px [body-start] 1.5em [body-content-start] minmax(500px, calc( 1000px - 3em )) [body-content-end] 1.5em [body-end body-end-outset page-end-inset page-end] 5fr [screen-end-inset] 1.5em [screen-end]}body.floating.fullcontent .page-columns{display:grid;gap:0;grid-template-columns:[screen-start] 1.5em [screen-start-inset] 5fr [page-start] 50px [page-start-inset] minmax(50px, 150px) [body-start-outset] 50px [body-start] 1.5em [body-content-start] minmax(500px, calc(800px - 3em)) [body-content-end] 1.5em [body-end body-end-outset page-end-inset page-end] 5fr [screen-end-inset] 1.5em [screen-end]}body.docked.slimcontent .page-columns{display:grid;gap:0;grid-template-columns:[screen-start] 1.5em [screen-start-inset page-start] minmax(50px, 100px) [page-start-inset] 50px [body-start-outset] 50px [body-start] 1.5em [body-content-start] minmax(450px, calc(750px - 3em)) [body-content-end] 1.5em [body-end] 50px [body-end-outset] minmax(0px, 200px) [page-end-inset] 50px [page-end] 5fr [screen-end-inset] 1.5em [screen-end]}body.docked.listing .page-columns{display:grid;gap:0;grid-template-columns:[screen-start] 1.5em [screen-start-inset page-start] minmax(50px, 100px) [page-start-inset] 50px [body-start-outset] 50px [body-start] 1.5em [body-content-start] minmax(500px, calc( 1000px - 3em )) [body-content-end] 1.5em [body-end] 50px [body-end-outset] minmax(0px, 100px) [page-end-inset] 50px [page-end] 5fr [screen-end-inset] 1.5em [screen-end]}body.floating.slimcontent .page-columns{display:grid;gap:0;grid-template-columns:[screen-start] 1.5em [screen-start-inset] 5fr [page-start] 50px [page-start-inset] minmax(50px, 150px) [body-start-outset] 50px [body-start] 1.5em [body-content-start] minmax(450px, calc(750px - 3em)) [body-content-end] 1.5em [body-end] 50px [body-end-outset] minmax(50px, 150px) [page-end-inset] 50px [page-end] 5fr [screen-end-inset] 1.5em [screen-end]}body.floating.listing .page-columns{display:grid;gap:0;grid-template-columns:[screen-start] 1.5em [screen-start-inset] 5fr [page-start] minmax(25px, 50px) [page-start-inset] minmax(50px, 150px) [body-start-outset] minmax(25px, 50px) [body-start] 1.5em [body-content-start] minmax(500px, calc(800px - 3em)) [body-content-end] 1.5em [body-end] minmax(25px, 50px) [body-end-outset] minmax(50px, 150px) [page-end-inset] minmax(25px, 50px) [page-end] 5fr [screen-end-inset] 1.5em [screen-end]}}@media(max-width: 991.98px){body .page-columns{display:grid;gap:0;grid-template-columns:[screen-start] 1.5em [screen-start-inset page-start page-start-inset body-start-outset] 5fr [body-start] 1.5em [body-content-start] minmax(500px, calc(750px - 3em)) [body-content-end] 1.5em [body-end] 35px [body-end-outset] minmax(75px, 145px) [page-end-inset] 35px [page-end] 5fr [screen-end-inset] 1.5em [screen-end]}body.fullcontent:not(.floating):not(.docked) .page-columns{display:grid;gap:0;grid-template-columns:[screen-start] 1.5em [screen-start-inset page-start page-start-inset body-start-outset] 5fr [body-start] 1.5em [body-content-start] minmax(500px, calc(750px - 3em)) [body-content-end] 1.5em [body-end body-end-outset page-end-inset page-end] 5fr [screen-end-inset] 1.5em [screen-end]}body.slimcontent:not(.floating):not(.docked) .page-columns{display:grid;gap:0;grid-template-columns:[screen-start] 1.5em [screen-start-inset page-start page-start-inset body-start-outset] 5fr [body-start] 1.5em [body-content-start] minmax(500px, calc(750px - 3em)) [body-content-end] 1.5em [body-end] 35px [body-end-outset] minmax(75px, 145px) [page-end-inset] 35px [page-end] 5fr [screen-end-inset] 1.5em [screen-end]}body.listing:not(.floating):not(.docked) .page-columns{display:grid;gap:0;grid-template-columns:[screen-start] 1.5em [screen-start-inset page-start page-start-inset body-start-outset] 5fr [body-start] 1.5em [body-content-start] minmax(500px, calc(1200px - 3em)) [body-content-end body-end body-end-outset page-end-inset page-end] 5fr [screen-end-inset] 1.5em [screen-end]}body:not(.floating):not(.docked) .page-columns.toc-left{display:grid;gap:0;grid-template-columns:[screen-start] 1.5em [screen-start-inset] 5fr [page-start] 35px [page-start-inset] minmax(0px, 145px) [body-start-outset] 35px [body-start] 1.5em [body-content-start] minmax(450px, calc(750px - 3em)) [body-content-end] 1.5em [body-end body-end-outset page-end-inset page-end] 5fr [screen-end-inset] 1.5em [screen-end]}body:not(.floating):not(.docked) .page-columns.toc-left .page-columns{display:grid;gap:0;grid-template-columns:[screen-start] 1.5em [screen-start-inset] 5fr [page-start] 35px [page-start-inset] minmax(0px, 145px) [body-start-outset] 35px [body-start] 1.5em [body-content-start] minmax(450px, calc(750px - 3em)) [body-content-end] 1.5em [body-end body-end-outset page-end-inset page-end] 5fr [screen-end-inset] 1.5em [screen-end]}body.floating .page-columns{display:grid;gap:0;grid-template-columns:[screen-start] 1.5em [screen-start-inset] 5fr [page-start page-start-inset body-start-outset body-start] 1em [body-content-start] minmax(500px, calc(750px - 3em)) [body-content-end] 1.5em [body-end] 50px [body-end-outset] minmax(75px, 150px) [page-end-inset] 25px [page-end] 5fr [screen-end-inset] 1.5em [screen-end]}body.docked .page-columns{display:grid;gap:0;grid-template-columns:[screen-start] 1.5em [screen-start-inset page-start page-start-inset body-start-outset body-start body-content-start] minmax(500px, calc(750px - 3em)) [body-content-end] 1.5em [body-end] 50px [body-end-outset] minmax(25px, 50px) [page-end-inset] 50px [page-end] 5fr [screen-end-inset] 1.5em [screen-end]}body.docked.fullcontent .page-columns{display:grid;gap:0;grid-template-columns:[screen-start] 1.5em [screen-start-inset page-start page-start-inset body-start-outset body-start body-content-start] minmax(500px, calc( 1000px - 3em )) [body-content-end] 1.5em [body-end body-end-outset page-end-inset page-end] 5fr [screen-end-inset] 1.5em [screen-end]}body.floating.fullcontent .page-columns{display:grid;gap:0;grid-template-columns:[screen-start] 1.5em [screen-start-inset] 5fr [page-start page-start-inset body-start-outset body-start] 1em [body-content-start] minmax(500px, calc(800px - 3em)) [body-content-end] 1.5em [body-end body-end-outset page-end-inset page-end] 5fr [screen-end-inset] 1.5em [screen-end]}body.docked.slimcontent .page-columns{display:grid;gap:0;grid-template-columns:[screen-start] 1.5em [screen-start-inset page-start page-start-inset body-start-outset body-start body-content-start] minmax(500px, calc(750px - 3em)) [body-content-end] 1.5em [body-end] 35px [body-end-outset] minmax(75px, 145px) [page-end-inset] 35px [page-end] 5fr [screen-end-inset] 1.5em [screen-end]}body.docked.listing .page-columns{display:grid;gap:0;grid-template-columns:[screen-start] 1.5em [screen-start-inset page-start page-start-inset body-start-outset body-start body-content-start] minmax(500px, calc(750px - 3em)) [body-content-end] 1.5em [body-end] 50px [body-end-outset] minmax(25px, 50px) [page-end-inset] 50px [page-end] 5fr [screen-end-inset] 1.5em [screen-end]}body.floating.slimcontent .page-columns{display:grid;gap:0;grid-template-columns:[screen-start] 1.5em [screen-start-inset] 5fr [page-start page-start-inset body-start-outset body-start] 1em [body-content-start] minmax(500px, calc(750px - 3em)) [body-content-end] 1.5em [body-end] 35px [body-end-outset] minmax(75px, 145px) [page-end-inset] 35px [page-end] 4fr [screen-end-inset] 1.5em [screen-end]}body.floating.listing .page-columns{display:grid;gap:0;grid-template-columns:[screen-start] 1.5em [screen-start-inset] 5fr [page-start page-start-inset body-start-outset body-start] 1em [body-content-start] minmax(500px, calc(750px - 3em)) [body-content-end] 1.5em [body-end] 50px [body-end-outset] minmax(75px, 150px) [page-end-inset] 25px [page-end] 5fr [screen-end-inset] 1.5em [screen-end]}}@media(max-width: 767.98px){body .page-columns,body.fullcontent:not(.floating):not(.docked) .page-columns,body.slimcontent:not(.floating):not(.docked) .page-columns,body.docked .page-columns,body.docked.slimcontent .page-columns,body.docked.fullcontent .page-columns,body.floating .page-columns,body.floating.slimcontent .page-columns,body.floating.fullcontent .page-columns{display:grid;gap:0;grid-template-columns:[screen-start] 1.5em [screen-start-inset page-start page-start-inset body-start-outset body-start body-content-start] minmax(0px, 1fr) [body-content-end body-end body-end-outset page-end-inset page-end screen-end-inset] 1.5em [screen-end]}body:not(.floating):not(.docked) .page-columns.toc-left{display:grid;gap:0;grid-template-columns:[screen-start] 1.5em [screen-start-inset page-start page-start-inset body-start-outset body-start body-content-start] minmax(0px, 1fr) [body-content-end body-end body-end-outset page-end-inset page-end screen-end-inset] 1.5em [screen-end]}body:not(.floating):not(.docked) .page-columns.toc-left .page-columns{display:grid;gap:0;grid-template-columns:[screen-start] 1.5em [screen-start-inset page-start page-start-inset body-start-outset body-start body-content-start] minmax(0px, 1fr) [body-content-end body-end body-end-outset page-end-inset page-end screen-end-inset] 1.5em [screen-end]}nav[role=doc-toc]{display:none}}body,.page-row-navigation{grid-template-rows:[page-top] max-content [contents-top] max-content [contents-bottom] max-content [page-bottom]}.page-rows-contents{grid-template-rows:[content-top] minmax(max-content, 1fr) [content-bottom] minmax(60px, max-content) [page-bottom]}.page-full{grid-column:screen-start/screen-end !important}.page-columns>*{grid-column:body-content-start/body-content-end}.page-columns.column-page>*{grid-column:page-start/page-end}.page-columns.column-page-left>*{grid-column:page-start/body-content-end}.page-columns.column-page-right>*{grid-column:body-content-start/page-end}.page-rows{grid-auto-rows:auto}.header{grid-column:screen-start/screen-end;grid-row:page-top/contents-top}#quarto-content{padding:0;grid-column:screen-start/screen-end;grid-row:contents-top/contents-bottom}body.floating .sidebar.sidebar-navigation{grid-column:page-start/body-start;grid-row:content-top/page-bottom}body.docked .sidebar.sidebar-navigation{grid-column:screen-start/body-start;grid-row:content-top/page-bottom}.sidebar.toc-left{grid-column:page-start/body-start;grid-row:content-top/page-bottom}.sidebar.margin-sidebar{grid-column:body-end/page-end;grid-row:content-top/page-bottom}.page-columns 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Q="x"===y?mt:bt,G="x"===y?gt:_t,Z=E[w],J=Z+g[Q],tt=Z-g[G],et=oe(f?ne(J,K):J,Z,f?ie(tt,X):tt);E[w]=et,C[w]=et-Z}}e.modifiersData[n]=C}},requiresIfExists:["offset"]};function Me(t,e,i){void 0===i&&(i=!1);var n=zt(e);zt(e)&&function(t){var e=t.getBoundingClientRect();e.width,t.offsetWidth,e.height,t.offsetHeight}(e);var s,o,r=Gt(e),a=Vt(t),l={scrollLeft:0,scrollTop:0},c={x:0,y:0};return(n||!n&&!i)&&(("body"!==Rt(e)||we(r))&&(l=(s=e)!==Wt(s)&&zt(s)?{scrollLeft:(o=s).scrollLeft,scrollTop:o.scrollTop}:ve(s)),zt(e)?((c=Vt(e)).x+=e.clientLeft,c.y+=e.clientTop):r&&(c.x=ye(r))),{x:a.left+l.scrollLeft-c.x,y:a.top+l.scrollTop-c.y,width:a.width,height:a.height}}function He(t){var e=new Map,i=new Set,n=[];function s(t){i.add(t.name),[].concat(t.requires||[],t.requiresIfExists||[]).forEach((function(t){if(!i.has(t)){var n=e.get(t);n&&s(n)}})),n.push(t)}return t.forEach((function(t){e.set(t.name,t)})),t.forEach((function(t){i.has(t.name)||s(t)})),n}var Be={placement:"bottom",modifiers:[],strategy:"absolute"};function Re(){for(var t=arguments.length,e=new Array(t),i=0;i<t;i++)e[i]=arguments[i];return!e.some((function(t){return!(t&&"function"==typeof t.getBoundingClientRect)}))}function We(t){void 0===t&&(t={});var e=t,i=e.defaultModifiers,n=void 0===i?[]:i,s=e.defaultOptions,o=void 0===s?Be:s;return function(t,e,i){void 0===i&&(i=o);var s,r,a={placement:"bottom",orderedModifiers:[],options:Object.assign({},Be,o),modifiersData:{},elements:{reference:t,popper:e},attributes:{},styles:{}},l=[],c=!1,h={state:a,setOptions:function(i){var s="function"==typeof i?i(a.options):i;d(),a.options=Object.assign({},o,a.options,s),a.scrollParents={reference:$t(t)?Ae(t):t.contextElement?Ae(t.contextElement):[],popper:Ae(e)};var r,c,u=function(t){var e=He(t);return Bt.reduce((function(t,i){return t.concat(e.filter((function(t){return t.phase===i})))}),[])}((r=[].concat(n,a.options.modifiers),c=r.reduce((function(t,e){var i=t[e.name];return t[e.name]=i?Object.assign({},i,e,{options:Object.assign({},i.options,e.options),data:Object.assign({},i.data,e.data)}):e,t}),{}),Object.keys(c).map((function(t){return c[t]}))));return a.orderedModifiers=u.filter((function(t){return t.enabled})),a.orderedModifiers.forEach((function(t){var e=t.name,i=t.options,n=void 0===i?{}:i,s=t.effect;if("function"==typeof s){var o=s({state:a,name:e,instance:h,options:n});l.push(o||function(){})}})),h.update()},forceUpdate:function(){if(!c){var t=a.elements,e=t.reference,i=t.popper;if(Re(e,i)){a.rects={reference:Me(e,te(i),"fixed"===a.options.strategy),popper:Kt(i)},a.reset=!1,a.placement=a.options.placement,a.orderedModifiers.forEach((function(t){return a.modifiersData[t.name]=Object.assign({},t.data)}));for(var n=0;n<a.orderedModifiers.length;n++)if(!0!==a.reset){var s=a.orderedModifiers[n],o=s.fn,r=s.options,l=void 0===r?{}:r,d=s.name;"function"==typeof o&&(a=o({state:a,options:l,name:d,instance:h})||a)}else a.reset=!1,n=-1}}},update:(s=function(){return new Promise((function(t){h.forceUpdate(),t(a)}))},function(){return r||(r=new Promise((function(t){Promise.resolve().then((function(){r=void 0,t(s())}))}))),r}),destroy:function(){d(),c=!0}};if(!Re(t,e))return h;function d(){l.forEach((function(t){return t()})),l=[]}return h.setOptions(i).then((function(t){!c&&i.onFirstUpdate&&i.onFirstUpdate(t)})),h}}var $e=We(),ze=We({defaultModifiers:[pe,Pe,ue,Ft]}),qe=We({defaultModifiers:[pe,Pe,ue,Ft,Ie,xe,je,le,Ne]});const Fe=Object.freeze({__proto__:null,popperGenerator:We,detectOverflow:ke,createPopperBase:$e,createPopper:qe,createPopperLite:ze,top:mt,bottom:gt,right:_t,left:bt,auto:vt,basePlacements:yt,start:wt,end:Et,clippingParents:At,viewport:Tt,popper:Ot,reference:Ct,variationPlacements:kt,placements:Lt,beforeRead:xt,read:Dt,afterRead:St,beforeMain:Nt,main:It,afterMain:Pt,beforeWrite:jt,write:Mt,afterWrite:Ht,modifierPhases:Bt,applyStyles:Ft,arrow:le,computeStyles:ue,eventListeners:pe,flip:xe,hide:Ne,offset:Ie,popperOffsets:Pe,preventOverflow:je}),Ue="dropdown",Ve="Escape",Ke="Space",Xe="ArrowUp",Ye="ArrowDown",Qe=new RegExp("ArrowUp|ArrowDown|Escape"),Ge="click.bs.dropdown.data-api",Ze="keydown.bs.dropdown.data-api",Je="show",ti='[data-bs-toggle="dropdown"]',ei=".dropdown-menu",ii=m()?"top-end":"top-start",ni=m()?"top-start":"top-end",si=m()?"bottom-end":"bottom-start",oi=m()?"bottom-start":"bottom-end",ri=m()?"left-start":"right-start",ai=m()?"right-start":"left-start",li={offset:[0,2],boundary:"clippingParents",reference:"toggle",display:"dynamic",popperConfig:null,autoClose:!0},ci={offset:"(array|string|function)",boundary:"(string|element)",reference:"(string|element|object)",display:"string",popperConfig:"(null|object|function)",autoClose:"(boolean|string)"};class hi extends B{constructor(t,e){super(t),this._popper=null,this._config=this._getConfig(e),this._menu=this._getMenuElement(),this._inNavbar=this._detectNavbar()}static get Default(){return li}static get DefaultType(){return ci}static get NAME(){return Ue}toggle(){return this._isShown()?this.hide():this.show()}show(){if(c(this._element)||this._isShown(this._menu))return;const t={relatedTarget:this._element};if(j.trigger(this._element,"show.bs.dropdown",t).defaultPrevented)return;const e=hi.getParentFromElement(this._element);this._inNavbar?U.setDataAttribute(this._menu,"popper","none"):this._createPopper(e),"ontouchstart"in document.documentElement&&!e.closest(".navbar-nav")&&[].concat(...document.body.children).forEach((t=>j.on(t,"mouseover",d))),this._element.focus(),this._element.setAttribute("aria-expanded",!0),this._menu.classList.add(Je),this._element.classList.add(Je),j.trigger(this._element,"shown.bs.dropdown",t)}hide(){if(c(this._element)||!this._isShown(this._menu))return;const t={relatedTarget:this._element};this._completeHide(t)}dispose(){this._popper&&this._popper.destroy(),super.dispose()}update(){this._inNavbar=this._detectNavbar(),this._popper&&this._popper.update()}_completeHide(t){j.trigger(this._element,"hide.bs.dropdown",t).defaultPrevented||("ontouchstart"in document.documentElement&&[].concat(...document.body.children).forEach((t=>j.off(t,"mouseover",d))),this._popper&&this._popper.destroy(),this._menu.classList.remove(Je),this._element.classList.remove(Je),this._element.setAttribute("aria-expanded","false"),U.removeDataAttribute(this._menu,"popper"),j.trigger(this._element,"hidden.bs.dropdown",t))}_getConfig(t){if(t={...this.constructor.Default,...U.getDataAttributes(this._element),...t},a(Ue,t,this.constructor.DefaultType),"object"==typeof t.reference&&!o(t.reference)&&"function"!=typeof t.reference.getBoundingClientRect)throw new TypeError(`${Ue.toUpperCase()}: Option "reference" provided type "object" without a required "getBoundingClientRect" method.`);return t}_createPopper(t){if(void 0===Fe)throw new TypeError("Bootstrap's dropdowns require Popper (https://popper.js.org)");let e=this._element;"parent"===this._config.reference?e=t:o(this._config.reference)?e=r(this._config.reference):"object"==typeof this._config.reference&&(e=this._config.reference);const i=this._getPopperConfig(),n=i.modifiers.find((t=>"applyStyles"===t.name&&!1===t.enabled));this._popper=qe(e,this._menu,i),n&&U.setDataAttribute(this._menu,"popper","static")}_isShown(t=this._element){return t.classList.contains(Je)}_getMenuElement(){return V.next(this._element,ei)[0]}_getPlacement(){const t=this._element.parentNode;if(t.classList.contains("dropend"))return ri;if(t.classList.contains("dropstart"))return ai;const e="end"===getComputedStyle(this._menu).getPropertyValue("--bs-position").trim();return t.classList.contains("dropup")?e?ni:ii:e?oi:si}_detectNavbar(){return null!==this._element.closest(".navbar")}_getOffset(){const{offset:t}=this._config;return"string"==typeof t?t.split(",").map((t=>Number.parseInt(t,10))):"function"==typeof t?e=>t(e,this._element):t}_getPopperConfig(){const t={placement:this._getPlacement(),modifiers:[{name:"preventOverflow",options:{boundary:this._config.boundary}},{name:"offset",options:{offset:this._getOffset()}}]};return"static"===this._config.display&&(t.modifiers=[{name:"applyStyles",enabled:!1}]),{...t,..."function"==typeof this._config.popperConfig?this._config.popperConfig(t):this._config.popperConfig}}_selectMenuItem({key:t,target:e}){const i=V.find(".dropdown-menu .dropdown-item:not(.disabled):not(:disabled)",this._menu).filter(l);i.length&&v(i,e,t===Ye,!i.includes(e)).focus()}static jQueryInterface(t){return this.each((function(){const e=hi.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t])throw new TypeError(`No method named "${t}"`);e[t]()}}))}static clearMenus(t){if(t&&(2===t.button||"keyup"===t.type&&"Tab"!==t.key))return;const e=V.find(ti);for(let i=0,n=e.length;i<n;i++){const n=hi.getInstance(e[i]);if(!n||!1===n._config.autoClose)continue;if(!n._isShown())continue;const s={relatedTarget:n._element};if(t){const e=t.composedPath(),i=e.includes(n._menu);if(e.includes(n._element)||"inside"===n._config.autoClose&&!i||"outside"===n._config.autoClose&&i)continue;if(n._menu.contains(t.target)&&("keyup"===t.type&&"Tab"===t.key||/input|select|option|textarea|form/i.test(t.target.tagName)))continue;"click"===t.type&&(s.clickEvent=t)}n._completeHide(s)}}static getParentFromElement(t){return n(t)||t.parentNode}static dataApiKeydownHandler(t){if(/input|textarea/i.test(t.target.tagName)?t.key===Ke||t.key!==Ve&&(t.key!==Ye&&t.key!==Xe||t.target.closest(ei)):!Qe.test(t.key))return;const e=this.classList.contains(Je);if(!e&&t.key===Ve)return;if(t.preventDefault(),t.stopPropagation(),c(this))return;const i=this.matches(ti)?this:V.prev(this,ti)[0],n=hi.getOrCreateInstance(i);if(t.key!==Ve)return t.key===Xe||t.key===Ye?(e||n.show(),void n._selectMenuItem(t)):void(e&&t.key!==Ke||hi.clearMenus());n.hide()}}j.on(document,Ze,ti,hi.dataApiKeydownHandler),j.on(document,Ze,ei,hi.dataApiKeydownHandler),j.on(document,Ge,hi.clearMenus),j.on(document,"keyup.bs.dropdown.data-api",hi.clearMenus),j.on(document,Ge,ti,(function(t){t.preventDefault(),hi.getOrCreateInstance(this).toggle()})),g(hi);const di=".fixed-top, .fixed-bottom, .is-fixed, .sticky-top",ui=".sticky-top";class fi{constructor(){this._element=document.body}getWidth(){const t=document.documentElement.clientWidth;return Math.abs(window.innerWidth-t)}hide(){const t=this.getWidth();this._disableOverFlow(),this._setElementAttributes(this._element,"paddingRight",(e=>e+t)),this._setElementAttributes(di,"paddingRight",(e=>e+t)),this._setElementAttributes(ui,"marginRight",(e=>e-t))}_disableOverFlow(){this._saveInitialAttribute(this._element,"overflow"),this._element.style.overflow="hidden"}_setElementAttributes(t,e,i){const n=this.getWidth();this._applyManipulationCallback(t,(t=>{if(t!==this._element&&window.innerWidth>t.clientWidth+n)return;this._saveInitialAttribute(t,e);const s=window.getComputedStyle(t)[e];t.style[e]=`${i(Number.parseFloat(s))}px`}))}reset(){this._resetElementAttributes(this._element,"overflow"),this._resetElementAttributes(this._element,"paddingRight"),this._resetElementAttributes(di,"paddingRight"),this._resetElementAttributes(ui,"marginRight")}_saveInitialAttribute(t,e){const i=t.style[e];i&&U.setDataAttribute(t,e,i)}_resetElementAttributes(t,e){this._applyManipulationCallback(t,(t=>{const i=U.getDataAttribute(t,e);void 0===i?t.style.removeProperty(e):(U.removeDataAttribute(t,e),t.style[e]=i)}))}_applyManipulationCallback(t,e){o(t)?e(t):V.find(t,this._element).forEach(e)}isOverflowing(){return this.getWidth()>0}}const pi={className:"modal-backdrop",isVisible:!0,isAnimated:!1,rootElement:"body",clickCallback:null},mi={className:"string",isVisible:"boolean",isAnimated:"boolean",rootElement:"(element|string)",clickCallback:"(function|null)"},gi="show",_i="mousedown.bs.backdrop";class bi{constructor(t){this._config=this._getConfig(t),this._isAppended=!1,this._element=null}show(t){this._config.isVisible?(this._append(),this._config.isAnimated&&u(this._getElement()),this._getElement().classList.add(gi),this._emulateAnimation((()=>{_(t)}))):_(t)}hide(t){this._config.isVisible?(this._getElement().classList.remove(gi),this._emulateAnimation((()=>{this.dispose(),_(t)}))):_(t)}_getElement(){if(!this._element){const t=document.createElement("div");t.className=this._config.className,this._config.isAnimated&&t.classList.add("fade"),this._element=t}return this._element}_getConfig(t){return(t={...pi,..."object"==typeof t?t:{}}).rootElement=r(t.rootElement),a("backdrop",t,mi),t}_append(){this._isAppended||(this._config.rootElement.append(this._getElement()),j.on(this._getElement(),_i,(()=>{_(this._config.clickCallback)})),this._isAppended=!0)}dispose(){this._isAppended&&(j.off(this._element,_i),this._element.remove(),this._isAppended=!1)}_emulateAnimation(t){b(t,this._getElement(),this._config.isAnimated)}}const vi={trapElement:null,autofocus:!0},yi={trapElement:"element",autofocus:"boolean"},wi=".bs.focustrap",Ei="backward";class Ai{constructor(t){this._config=this._getConfig(t),this._isActive=!1,this._lastTabNavDirection=null}activate(){const{trapElement:t,autofocus:e}=this._config;this._isActive||(e&&t.focus(),j.off(document,wi),j.on(document,"focusin.bs.focustrap",(t=>this._handleFocusin(t))),j.on(document,"keydown.tab.bs.focustrap",(t=>this._handleKeydown(t))),this._isActive=!0)}deactivate(){this._isActive&&(this._isActive=!1,j.off(document,wi))}_handleFocusin(t){const{target:e}=t,{trapElement:i}=this._config;if(e===document||e===i||i.contains(e))return;const n=V.focusableChildren(i);0===n.length?i.focus():this._lastTabNavDirection===Ei?n[n.length-1].focus():n[0].focus()}_handleKeydown(t){"Tab"===t.key&&(this._lastTabNavDirection=t.shiftKey?Ei:"forward")}_getConfig(t){return t={...vi,..."object"==typeof t?t:{}},a("focustrap",t,yi),t}}const Ti="modal",Oi="Escape",Ci={backdrop:!0,keyboard:!0,focus:!0},ki={backdrop:"(boolean|string)",keyboard:"boolean",focus:"boolean"},Li="hidden.bs.modal",xi="show.bs.modal",Di="resize.bs.modal",Si="click.dismiss.bs.modal",Ni="keydown.dismiss.bs.modal",Ii="mousedown.dismiss.bs.modal",Pi="modal-open",ji="show",Mi="modal-static";class Hi extends B{constructor(t,e){super(t),this._config=this._getConfig(e),this._dialog=V.findOne(".modal-dialog",this._element),this._backdrop=this._initializeBackDrop(),this._focustrap=this._initializeFocusTrap(),this._isShown=!1,this._ignoreBackdropClick=!1,this._isTransitioning=!1,this._scrollBar=new fi}static get Default(){return Ci}static get NAME(){return Ti}toggle(t){return this._isShown?this.hide():this.show(t)}show(t){this._isShown||this._isTransitioning||j.trigger(this._element,xi,{relatedTarget:t}).defaultPrevented||(this._isShown=!0,this._isAnimated()&&(this._isTransitioning=!0),this._scrollBar.hide(),document.body.classList.add(Pi),this._adjustDialog(),this._setEscapeEvent(),this._setResizeEvent(),j.on(this._dialog,Ii,(()=>{j.one(this._element,"mouseup.dismiss.bs.modal",(t=>{t.target===this._element&&(this._ignoreBackdropClick=!0)}))})),this._showBackdrop((()=>this._showElement(t))))}hide(){if(!this._isShown||this._isTransitioning)return;if(j.trigger(this._element,"hide.bs.modal").defaultPrevented)return;this._isShown=!1;const t=this._isAnimated();t&&(this._isTransitioning=!0),this._setEscapeEvent(),this._setResizeEvent(),this._focustrap.deactivate(),this._element.classList.remove(ji),j.off(this._element,Si),j.off(this._dialog,Ii),this._queueCallback((()=>this._hideModal()),this._element,t)}dispose(){[window,this._dialog].forEach((t=>j.off(t,".bs.modal"))),this._backdrop.dispose(),this._focustrap.deactivate(),super.dispose()}handleUpdate(){this._adjustDialog()}_initializeBackDrop(){return new bi({isVisible:Boolean(this._config.backdrop),isAnimated:this._isAnimated()})}_initializeFocusTrap(){return new Ai({trapElement:this._element})}_getConfig(t){return t={...Ci,...U.getDataAttributes(this._element),..."object"==typeof t?t:{}},a(Ti,t,ki),t}_showElement(t){const e=this._isAnimated(),i=V.findOne(".modal-body",this._dialog);this._element.parentNode&&this._element.parentNode.nodeType===Node.ELEMENT_NODE||document.body.append(this._element),this._element.style.display="block",this._element.removeAttribute("aria-hidden"),this._element.setAttribute("aria-modal",!0),this._element.setAttribute("role","dialog"),this._element.scrollTop=0,i&&(i.scrollTop=0),e&&u(this._element),this._element.classList.add(ji),this._queueCallback((()=>{this._config.focus&&this._focustrap.activate(),this._isTransitioning=!1,j.trigger(this._element,"shown.bs.modal",{relatedTarget:t})}),this._dialog,e)}_setEscapeEvent(){this._isShown?j.on(this._element,Ni,(t=>{this._config.keyboard&&t.key===Oi?(t.preventDefault(),this.hide()):this._config.keyboard||t.key!==Oi||this._triggerBackdropTransition()})):j.off(this._element,Ni)}_setResizeEvent(){this._isShown?j.on(window,Di,(()=>this._adjustDialog())):j.off(window,Di)}_hideModal(){this._element.style.display="none",this._element.setAttribute("aria-hidden",!0),this._element.removeAttribute("aria-modal"),this._element.removeAttribute("role"),this._isTransitioning=!1,this._backdrop.hide((()=>{document.body.classList.remove(Pi),this._resetAdjustments(),this._scrollBar.reset(),j.trigger(this._element,Li)}))}_showBackdrop(t){j.on(this._element,Si,(t=>{this._ignoreBackdropClick?this._ignoreBackdropClick=!1:t.target===t.currentTarget&&(!0===this._config.backdrop?this.hide():"static"===this._config.backdrop&&this._triggerBackdropTransition())})),this._backdrop.show(t)}_isAnimated(){return this._element.classList.contains("fade")}_triggerBackdropTransition(){if(j.trigger(this._element,"hidePrevented.bs.modal").defaultPrevented)return;const{classList:t,scrollHeight:e,style:i}=this._element,n=e>document.documentElement.clientHeight;!n&&"hidden"===i.overflowY||t.contains(Mi)||(n||(i.overflowY="hidden"),t.add(Mi),this._queueCallback((()=>{t.remove(Mi),n||this._queueCallback((()=>{i.overflowY=""}),this._dialog)}),this._dialog),this._element.focus())}_adjustDialog(){const t=this._element.scrollHeight>document.documentElement.clientHeight,e=this._scrollBar.getWidth(),i=e>0;(!i&&t&&!m()||i&&!t&&m())&&(this._element.style.paddingLeft=`${e}px`),(i&&!t&&!m()||!i&&t&&m())&&(this._element.style.paddingRight=`${e}px`)}_resetAdjustments(){this._element.style.paddingLeft="",this._element.style.paddingRight=""}static jQueryInterface(t,e){return this.each((function(){const i=Hi.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===i[t])throw new TypeError(`No method named "${t}"`);i[t](e)}}))}}j.on(document,"click.bs.modal.data-api",'[data-bs-toggle="modal"]',(function(t){const e=n(this);["A","AREA"].includes(this.tagName)&&t.preventDefault(),j.one(e,xi,(t=>{t.defaultPrevented||j.one(e,Li,(()=>{l(this)&&this.focus()}))}));const i=V.findOne(".modal.show");i&&Hi.getInstance(i).hide(),Hi.getOrCreateInstance(e).toggle(this)})),R(Hi),g(Hi);const Bi="offcanvas",Ri={backdrop:!0,keyboard:!0,scroll:!1},Wi={backdrop:"boolean",keyboard:"boolean",scroll:"boolean"},$i="show",zi=".offcanvas.show",qi="hidden.bs.offcanvas";class Fi extends B{constructor(t,e){super(t),this._config=this._getConfig(e),this._isShown=!1,this._backdrop=this._initializeBackDrop(),this._focustrap=this._initializeFocusTrap(),this._addEventListeners()}static get NAME(){return Bi}static get Default(){return Ri}toggle(t){return this._isShown?this.hide():this.show(t)}show(t){this._isShown||j.trigger(this._element,"show.bs.offcanvas",{relatedTarget:t}).defaultPrevented||(this._isShown=!0,this._element.style.visibility="visible",this._backdrop.show(),this._config.scroll||(new fi).hide(),this._element.removeAttribute("aria-hidden"),this._element.setAttribute("aria-modal",!0),this._element.setAttribute("role","dialog"),this._element.classList.add($i),this._queueCallback((()=>{this._config.scroll||this._focustrap.activate(),j.trigger(this._element,"shown.bs.offcanvas",{relatedTarget:t})}),this._element,!0))}hide(){this._isShown&&(j.trigger(this._element,"hide.bs.offcanvas").defaultPrevented||(this._focustrap.deactivate(),this._element.blur(),this._isShown=!1,this._element.classList.remove($i),this._backdrop.hide(),this._queueCallback((()=>{this._element.setAttribute("aria-hidden",!0),this._element.removeAttribute("aria-modal"),this._element.removeAttribute("role"),this._element.style.visibility="hidden",this._config.scroll||(new fi).reset(),j.trigger(this._element,qi)}),this._element,!0)))}dispose(){this._backdrop.dispose(),this._focustrap.deactivate(),super.dispose()}_getConfig(t){return t={...Ri,...U.getDataAttributes(this._element),..."object"==typeof t?t:{}},a(Bi,t,Wi),t}_initializeBackDrop(){return new bi({className:"offcanvas-backdrop",isVisible:this._config.backdrop,isAnimated:!0,rootElement:this._element.parentNode,clickCallback:()=>this.hide()})}_initializeFocusTrap(){return new Ai({trapElement:this._element})}_addEventListeners(){j.on(this._element,"keydown.dismiss.bs.offcanvas",(t=>{this._config.keyboard&&"Escape"===t.key&&this.hide()}))}static jQueryInterface(t){return this.each((function(){const e=Fi.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t]||t.startsWith("_")||"constructor"===t)throw new TypeError(`No method named "${t}"`);e[t](this)}}))}}j.on(document,"click.bs.offcanvas.data-api",'[data-bs-toggle="offcanvas"]',(function(t){const e=n(this);if(["A","AREA"].includes(this.tagName)&&t.preventDefault(),c(this))return;j.one(e,qi,(()=>{l(this)&&this.focus()}));const i=V.findOne(zi);i&&i!==e&&Fi.getInstance(i).hide(),Fi.getOrCreateInstance(e).toggle(this)})),j.on(window,"load.bs.offcanvas.data-api",(()=>V.find(zi).forEach((t=>Fi.getOrCreateInstance(t).show())))),R(Fi),g(Fi);const Ui=new Set(["background","cite","href","itemtype","longdesc","poster","src","xlink:href"]),Vi=/^(?:(?:https?|mailto|ftp|tel|file|sms):|[^#&/:?]*(?:[#/?]|$))/i,Ki=/^data:(?:image\/(?:bmp|gif|jpeg|jpg|png|tiff|webp)|video\/(?:mpeg|mp4|ogg|webm)|audio\/(?:mp3|oga|ogg|opus));base64,[\d+/a-z]+=*$/i,Xi=(t,e)=>{const i=t.nodeName.toLowerCase();if(e.includes(i))return!Ui.has(i)||Boolean(Vi.test(t.nodeValue)||Ki.test(t.nodeValue));const n=e.filter((t=>t instanceof RegExp));for(let t=0,e=n.length;t<e;t++)if(n[t].test(i))return!0;return!1};function Yi(t,e,i){if(!t.length)return t;if(i&&"function"==typeof i)return i(t);const n=(new window.DOMParser).parseFromString(t,"text/html"),s=[].concat(...n.body.querySelectorAll("*"));for(let t=0,i=s.length;t<i;t++){const i=s[t],n=i.nodeName.toLowerCase();if(!Object.keys(e).includes(n)){i.remove();continue}const o=[].concat(...i.attributes),r=[].concat(e["*"]||[],e[n]||[]);o.forEach((t=>{Xi(t,r)||i.removeAttribute(t.nodeName)}))}return n.body.innerHTML}const Qi="tooltip",Gi=new Set(["sanitize","allowList","sanitizeFn"]),Zi={animation:"boolean",template:"string",title:"(string|element|function)",trigger:"string",delay:"(number|object)",html:"boolean",selector:"(string|boolean)",placement:"(string|function)",offset:"(array|string|function)",container:"(string|element|boolean)",fallbackPlacements:"array",boundary:"(string|element)",customClass:"(string|function)",sanitize:"boolean",sanitizeFn:"(null|function)",allowList:"object",popperConfig:"(null|object|function)"},Ji={AUTO:"auto",TOP:"top",RIGHT:m()?"left":"right",BOTTOM:"bottom",LEFT:m()?"right":"left"},tn={animation:!0,template:'<div class="tooltip" role="tooltip"><div class="tooltip-arrow"></div><div class="tooltip-inner"></div></div>',trigger:"hover focus",title:"",delay:0,html:!1,selector:!1,placement:"top",offset:[0,0],container:!1,fallbackPlacements:["top","right","bottom","left"],boundary:"clippingParents",customClass:"",sanitize:!0,sanitizeFn:null,allowList:{"*":["class","dir","id","lang","role",/^aria-[\w-]*$/i],a:["target","href","title","rel"],area:[],b:[],br:[],col:[],code:[],div:[],em:[],hr:[],h1:[],h2:[],h3:[],h4:[],h5:[],h6:[],i:[],img:["src","srcset","alt","title","width","height"],li:[],ol:[],p:[],pre:[],s:[],small:[],span:[],sub:[],sup:[],strong:[],u:[],ul:[]},popperConfig:null},en={HIDE:"hide.bs.tooltip",HIDDEN:"hidden.bs.tooltip",SHOW:"show.bs.tooltip",SHOWN:"shown.bs.tooltip",INSERTED:"inserted.bs.tooltip",CLICK:"click.bs.tooltip",FOCUSIN:"focusin.bs.tooltip",FOCUSOUT:"focusout.bs.tooltip",MOUSEENTER:"mouseenter.bs.tooltip",MOUSELEAVE:"mouseleave.bs.tooltip"},nn="fade",sn="show",on="show",rn="out",an=".tooltip-inner",ln=".modal",cn="hide.bs.modal",hn="hover",dn="focus";class un extends B{constructor(t,e){if(void 0===Fe)throw new TypeError("Bootstrap's tooltips require Popper (https://popper.js.org)");super(t),this._isEnabled=!0,this._timeout=0,this._hoverState="",this._activeTrigger={},this._popper=null,this._config=this._getConfig(e),this.tip=null,this._setListeners()}static get Default(){return tn}static get NAME(){return Qi}static get Event(){return en}static get DefaultType(){return Zi}enable(){this._isEnabled=!0}disable(){this._isEnabled=!1}toggleEnabled(){this._isEnabled=!this._isEnabled}toggle(t){if(this._isEnabled)if(t){const e=this._initializeOnDelegatedTarget(t);e._activeTrigger.click=!e._activeTrigger.click,e._isWithActiveTrigger()?e._enter(null,e):e._leave(null,e)}else{if(this.getTipElement().classList.contains(sn))return void this._leave(null,this);this._enter(null,this)}}dispose(){clearTimeout(this._timeout),j.off(this._element.closest(ln),cn,this._hideModalHandler),this.tip&&this.tip.remove(),this._disposePopper(),super.dispose()}show(){if("none"===this._element.style.display)throw new Error("Please use show on visible elements");if(!this.isWithContent()||!this._isEnabled)return;const t=j.trigger(this._element,this.constructor.Event.SHOW),e=h(this._element),i=null===e?this._element.ownerDocument.documentElement.contains(this._element):e.contains(this._element);if(t.defaultPrevented||!i)return;"tooltip"===this.constructor.NAME&&this.tip&&this.getTitle()!==this.tip.querySelector(an).innerHTML&&(this._disposePopper(),this.tip.remove(),this.tip=null);const n=this.getTipElement(),s=(t=>{do{t+=Math.floor(1e6*Math.random())}while(document.getElementById(t));return t})(this.constructor.NAME);n.setAttribute("id",s),this._element.setAttribute("aria-describedby",s),this._config.animation&&n.classList.add(nn);const o="function"==typeof this._config.placement?this._config.placement.call(this,n,this._element):this._config.placement,r=this._getAttachment(o);this._addAttachmentClass(r);const{container:a}=this._config;H.set(n,this.constructor.DATA_KEY,this),this._element.ownerDocument.documentElement.contains(this.tip)||(a.append(n),j.trigger(this._element,this.constructor.Event.INSERTED)),this._popper?this._popper.update():this._popper=qe(this._element,n,this._getPopperConfig(r)),n.classList.add(sn);const l=this._resolvePossibleFunction(this._config.customClass);l&&n.classList.add(...l.split(" ")),"ontouchstart"in document.documentElement&&[].concat(...document.body.children).forEach((t=>{j.on(t,"mouseover",d)}));const c=this.tip.classList.contains(nn);this._queueCallback((()=>{const t=this._hoverState;this._hoverState=null,j.trigger(this._element,this.constructor.Event.SHOWN),t===rn&&this._leave(null,this)}),this.tip,c)}hide(){if(!this._popper)return;const t=this.getTipElement();if(j.trigger(this._element,this.constructor.Event.HIDE).defaultPrevented)return;t.classList.remove(sn),"ontouchstart"in document.documentElement&&[].concat(...document.body.children).forEach((t=>j.off(t,"mouseover",d))),this._activeTrigger.click=!1,this._activeTrigger.focus=!1,this._activeTrigger.hover=!1;const e=this.tip.classList.contains(nn);this._queueCallback((()=>{this._isWithActiveTrigger()||(this._hoverState!==on&&t.remove(),this._cleanTipClass(),this._element.removeAttribute("aria-describedby"),j.trigger(this._element,this.constructor.Event.HIDDEN),this._disposePopper())}),this.tip,e),this._hoverState=""}update(){null!==this._popper&&this._popper.update()}isWithContent(){return Boolean(this.getTitle())}getTipElement(){if(this.tip)return this.tip;const t=document.createElement("div");t.innerHTML=this._config.template;const e=t.children[0];return this.setContent(e),e.classList.remove(nn,sn),this.tip=e,this.tip}setContent(t){this._sanitizeAndSetContent(t,this.getTitle(),an)}_sanitizeAndSetContent(t,e,i){const n=V.findOne(i,t);e||!n?this.setElementContent(n,e):n.remove()}setElementContent(t,e){if(null!==t)return o(e)?(e=r(e),void(this._config.html?e.parentNode!==t&&(t.innerHTML="",t.append(e)):t.textContent=e.textContent)):void(this._config.html?(this._config.sanitize&&(e=Yi(e,this._config.allowList,this._config.sanitizeFn)),t.innerHTML=e):t.textContent=e)}getTitle(){const t=this._element.getAttribute("data-bs-original-title")||this._config.title;return this._resolvePossibleFunction(t)}updateAttachment(t){return"right"===t?"end":"left"===t?"start":t}_initializeOnDelegatedTarget(t,e){return e||this.constructor.getOrCreateInstance(t.delegateTarget,this._getDelegateConfig())}_getOffset(){const{offset:t}=this._config;return"string"==typeof t?t.split(",").map((t=>Number.parseInt(t,10))):"function"==typeof t?e=>t(e,this._element):t}_resolvePossibleFunction(t){return"function"==typeof t?t.call(this._element):t}_getPopperConfig(t){const e={placement:t,modifiers:[{name:"flip",options:{fallbackPlacements:this._config.fallbackPlacements}},{name:"offset",options:{offset:this._getOffset()}},{name:"preventOverflow",options:{boundary:this._config.boundary}},{name:"arrow",options:{element:`.${this.constructor.NAME}-arrow`}},{name:"onChange",enabled:!0,phase:"afterWrite",fn:t=>this._handlePopperPlacementChange(t)}],onFirstUpdate:t=>{t.options.placement!==t.placement&&this._handlePopperPlacementChange(t)}};return{...e,..."function"==typeof this._config.popperConfig?this._config.popperConfig(e):this._config.popperConfig}}_addAttachmentClass(t){this.getTipElement().classList.add(`${this._getBasicClassPrefix()}-${this.updateAttachment(t)}`)}_getAttachment(t){return Ji[t.toUpperCase()]}_setListeners(){this._config.trigger.split(" ").forEach((t=>{if("click"===t)j.on(this._element,this.constructor.Event.CLICK,this._config.selector,(t=>this.toggle(t)));else if("manual"!==t){const e=t===hn?this.constructor.Event.MOUSEENTER:this.constructor.Event.FOCUSIN,i=t===hn?this.constructor.Event.MOUSELEAVE:this.constructor.Event.FOCUSOUT;j.on(this._element,e,this._config.selector,(t=>this._enter(t))),j.on(this._element,i,this._config.selector,(t=>this._leave(t)))}})),this._hideModalHandler=()=>{this._element&&this.hide()},j.on(this._element.closest(ln),cn,this._hideModalHandler),this._config.selector?this._config={...this._config,trigger:"manual",selector:""}:this._fixTitle()}_fixTitle(){const t=this._element.getAttribute("title"),e=typeof this._element.getAttribute("data-bs-original-title");(t||"string"!==e)&&(this._element.setAttribute("data-bs-original-title",t||""),!t||this._element.getAttribute("aria-label")||this._element.textContent||this._element.setAttribute("aria-label",t),this._element.setAttribute("title",""))}_enter(t,e){e=this._initializeOnDelegatedTarget(t,e),t&&(e._activeTrigger["focusin"===t.type?dn:hn]=!0),e.getTipElement().classList.contains(sn)||e._hoverState===on?e._hoverState=on:(clearTimeout(e._timeout),e._hoverState=on,e._config.delay&&e._config.delay.show?e._timeout=setTimeout((()=>{e._hoverState===on&&e.show()}),e._config.delay.show):e.show())}_leave(t,e){e=this._initializeOnDelegatedTarget(t,e),t&&(e._activeTrigger["focusout"===t.type?dn:hn]=e._element.contains(t.relatedTarget)),e._isWithActiveTrigger()||(clearTimeout(e._timeout),e._hoverState=rn,e._config.delay&&e._config.delay.hide?e._timeout=setTimeout((()=>{e._hoverState===rn&&e.hide()}),e._config.delay.hide):e.hide())}_isWithActiveTrigger(){for(const t in this._activeTrigger)if(this._activeTrigger[t])return!0;return!1}_getConfig(t){const e=U.getDataAttributes(this._element);return Object.keys(e).forEach((t=>{Gi.has(t)&&delete e[t]})),(t={...this.constructor.Default,...e,..."object"==typeof t&&t?t:{}}).container=!1===t.container?document.body:r(t.container),"number"==typeof t.delay&&(t.delay={show:t.delay,hide:t.delay}),"number"==typeof t.title&&(t.title=t.title.toString()),"number"==typeof t.content&&(t.content=t.content.toString()),a(Qi,t,this.constructor.DefaultType),t.sanitize&&(t.template=Yi(t.template,t.allowList,t.sanitizeFn)),t}_getDelegateConfig(){const t={};for(const e in this._config)this.constructor.Default[e]!==this._config[e]&&(t[e]=this._config[e]);return t}_cleanTipClass(){const t=this.getTipElement(),e=new RegExp(`(^|\\s)${this._getBasicClassPrefix()}\\S+`,"g"),i=t.getAttribute("class").match(e);null!==i&&i.length>0&&i.map((t=>t.trim())).forEach((e=>t.classList.remove(e)))}_getBasicClassPrefix(){return"bs-tooltip"}_handlePopperPlacementChange(t){const{state:e}=t;e&&(this.tip=e.elements.popper,this._cleanTipClass(),this._addAttachmentClass(this._getAttachment(e.placement)))}_disposePopper(){this._popper&&(this._popper.destroy(),this._popper=null)}static jQueryInterface(t){return this.each((function(){const e=un.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t])throw new TypeError(`No method named "${t}"`);e[t]()}}))}}g(un);const fn={...un.Default,placement:"right",offset:[0,8],trigger:"click",content:"",template:'<div class="popover" role="tooltip"><div class="popover-arrow"></div><h3 class="popover-header"></h3><div class="popover-body"></div></div>'},pn={...un.DefaultType,content:"(string|element|function)"},mn={HIDE:"hide.bs.popover",HIDDEN:"hidden.bs.popover",SHOW:"show.bs.popover",SHOWN:"shown.bs.popover",INSERTED:"inserted.bs.popover",CLICK:"click.bs.popover",FOCUSIN:"focusin.bs.popover",FOCUSOUT:"focusout.bs.popover",MOUSEENTER:"mouseenter.bs.popover",MOUSELEAVE:"mouseleave.bs.popover"};class gn extends un{static get Default(){return fn}static get NAME(){return"popover"}static get Event(){return mn}static get DefaultType(){return pn}isWithContent(){return this.getTitle()||this._getContent()}setContent(t){this._sanitizeAndSetContent(t,this.getTitle(),".popover-header"),this._sanitizeAndSetContent(t,this._getContent(),".popover-body")}_getContent(){return this._resolvePossibleFunction(this._config.content)}_getBasicClassPrefix(){return"bs-popover"}static jQueryInterface(t){return this.each((function(){const e=gn.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t])throw new TypeError(`No method named "${t}"`);e[t]()}}))}}g(gn);const _n="scrollspy",bn={offset:10,method:"auto",target:""},vn={offset:"number",method:"string",target:"(string|element)"},yn="active",wn=".nav-link, .list-group-item, .dropdown-item",En="position";class An extends B{constructor(t,e){super(t),this._scrollElement="BODY"===this._element.tagName?window:this._element,this._config=this._getConfig(e),this._offsets=[],this._targets=[],this._activeTarget=null,this._scrollHeight=0,j.on(this._scrollElement,"scroll.bs.scrollspy",(()=>this._process())),this.refresh(),this._process()}static get Default(){return bn}static get NAME(){return _n}refresh(){const t=this._scrollElement===this._scrollElement.window?"offset":En,e="auto"===this._config.method?t:this._config.method,n=e===En?this._getScrollTop():0;this._offsets=[],this._targets=[],this._scrollHeight=this._getScrollHeight(),V.find(wn,this._config.target).map((t=>{const s=i(t),o=s?V.findOne(s):null;if(o){const t=o.getBoundingClientRect();if(t.width||t.height)return[U[e](o).top+n,s]}return null})).filter((t=>t)).sort(((t,e)=>t[0]-e[0])).forEach((t=>{this._offsets.push(t[0]),this._targets.push(t[1])}))}dispose(){j.off(this._scrollElement,".bs.scrollspy"),super.dispose()}_getConfig(t){return(t={...bn,...U.getDataAttributes(this._element),..."object"==typeof t&&t?t:{}}).target=r(t.target)||document.documentElement,a(_n,t,vn),t}_getScrollTop(){return this._scrollElement===window?this._scrollElement.pageYOffset:this._scrollElement.scrollTop}_getScrollHeight(){return this._scrollElement.scrollHeight||Math.max(document.body.scrollHeight,document.documentElement.scrollHeight)}_getOffsetHeight(){return this._scrollElement===window?window.innerHeight:this._scrollElement.getBoundingClientRect().height}_process(){const t=this._getScrollTop()+this._config.offset,e=this._getScrollHeight(),i=this._config.offset+e-this._getOffsetHeight();if(this._scrollHeight!==e&&this.refresh(),t>=i){const t=this._targets[this._targets.length-1];this._activeTarget!==t&&this._activate(t)}else{if(this._activeTarget&&t<this._offsets[0]&&this._offsets[0]>0)return this._activeTarget=null,void this._clear();for(let e=this._offsets.length;e--;)this._activeTarget!==this._targets[e]&&t>=this._offsets[e]&&(void 0===this._offsets[e+1]||t<this._offsets[e+1])&&this._activate(this._targets[e])}}_activate(t){this._activeTarget=t,this._clear();const e=wn.split(",").map((e=>`${e}[data-bs-target="${t}"],${e}[href="${t}"]`)),i=V.findOne(e.join(","),this._config.target);i.classList.add(yn),i.classList.contains("dropdown-item")?V.findOne(".dropdown-toggle",i.closest(".dropdown")).classList.add(yn):V.parents(i,".nav, .list-group").forEach((t=>{V.prev(t,".nav-link, .list-group-item").forEach((t=>t.classList.add(yn))),V.prev(t,".nav-item").forEach((t=>{V.children(t,".nav-link").forEach((t=>t.classList.add(yn)))}))})),j.trigger(this._scrollElement,"activate.bs.scrollspy",{relatedTarget:t})}_clear(){V.find(wn,this._config.target).filter((t=>t.classList.contains(yn))).forEach((t=>t.classList.remove(yn)))}static jQueryInterface(t){return this.each((function(){const e=An.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t])throw new TypeError(`No method named "${t}"`);e[t]()}}))}}j.on(window,"load.bs.scrollspy.data-api",(()=>{V.find('[data-bs-spy="scroll"]').forEach((t=>new An(t)))})),g(An);const Tn="active",On="fade",Cn="show",kn=".active",Ln=":scope > li > .active";class xn extends B{static get NAME(){return"tab"}show(){if(this._element.parentNode&&this._element.parentNode.nodeType===Node.ELEMENT_NODE&&this._element.classList.contains(Tn))return;let t;const e=n(this._element),i=this._element.closest(".nav, .list-group");if(i){const e="UL"===i.nodeName||"OL"===i.nodeName?Ln:kn;t=V.find(e,i),t=t[t.length-1]}const s=t?j.trigger(t,"hide.bs.tab",{relatedTarget:this._element}):null;if(j.trigger(this._element,"show.bs.tab",{relatedTarget:t}).defaultPrevented||null!==s&&s.defaultPrevented)return;this._activate(this._element,i);const o=()=>{j.trigger(t,"hidden.bs.tab",{relatedTarget:this._element}),j.trigger(this._element,"shown.bs.tab",{relatedTarget:t})};e?this._activate(e,e.parentNode,o):o()}_activate(t,e,i){const n=(!e||"UL"!==e.nodeName&&"OL"!==e.nodeName?V.children(e,kn):V.find(Ln,e))[0],s=i&&n&&n.classList.contains(On),o=()=>this._transitionComplete(t,n,i);n&&s?(n.classList.remove(Cn),this._queueCallback(o,t,!0)):o()}_transitionComplete(t,e,i){if(e){e.classList.remove(Tn);const t=V.findOne(":scope > .dropdown-menu .active",e.parentNode);t&&t.classList.remove(Tn),"tab"===e.getAttribute("role")&&e.setAttribute("aria-selected",!1)}t.classList.add(Tn),"tab"===t.getAttribute("role")&&t.setAttribute("aria-selected",!0),u(t),t.classList.contains(On)&&t.classList.add(Cn);let n=t.parentNode;if(n&&"LI"===n.nodeName&&(n=n.parentNode),n&&n.classList.contains("dropdown-menu")){const e=t.closest(".dropdown");e&&V.find(".dropdown-toggle",e).forEach((t=>t.classList.add(Tn))),t.setAttribute("aria-expanded",!0)}i&&i()}static jQueryInterface(t){return this.each((function(){const e=xn.getOrCreateInstance(this);if("string"==typeof t){if(void 0===e[t])throw new TypeError(`No method named "${t}"`);e[t]()}}))}}j.on(document,"click.bs.tab.data-api",'[data-bs-toggle="tab"], [data-bs-toggle="pill"], [data-bs-toggle="list"]',(function(t){["A","AREA"].includes(this.tagName)&&t.preventDefault(),c(this)||xn.getOrCreateInstance(this).show()})),g(xn);const Dn="toast",Sn="hide",Nn="show",In="showing",Pn={animation:"boolean",autohide:"boolean",delay:"number"},jn={animation:!0,autohide:!0,delay:5e3};class Mn extends B{constructor(t,e){super(t),this._config=this._getConfig(e),this._timeout=null,this._hasMouseInteraction=!1,this._hasKeyboardInteraction=!1,this._setListeners()}static get DefaultType(){return Pn}static get Default(){return jn}static get NAME(){return Dn}show(){j.trigger(this._element,"show.bs.toast").defaultPrevented||(this._clearTimeout(),this._config.animation&&this._element.classList.add("fade"),this._element.classList.remove(Sn),u(this._element),this._element.classList.add(Nn),this._element.classList.add(In),this._queueCallback((()=>{this._element.classList.remove(In),j.trigger(this._element,"shown.bs.toast"),this._maybeScheduleHide()}),this._element,this._config.animation))}hide(){this._element.classList.contains(Nn)&&(j.trigger(this._element,"hide.bs.toast").defaultPrevented||(this._element.classList.add(In),this._queueCallback((()=>{this._element.classList.add(Sn),this._element.classList.remove(In),this._element.classList.remove(Nn),j.trigger(this._element,"hidden.bs.toast")}),this._element,this._config.animation)))}dispose(){this._clearTimeout(),this._element.classList.contains(Nn)&&this._element.classList.remove(Nn),super.dispose()}_getConfig(t){return t={...jn,...U.getDataAttributes(this._element),..."object"==typeof t&&t?t:{}},a(Dn,t,this.constructor.DefaultType),t}_maybeScheduleHide(){this._config.autohide&&(this._hasMouseInteraction||this._hasKeyboardInteraction||(this._timeout=setTimeout((()=>{this.hide()}),this._config.delay)))}_onInteraction(t,e){switch(t.type){case"mouseover":case"mouseout":this._hasMouseInteraction=e;break;case"focusin":case"focusout":this._hasKeyboardInteraction=e}if(e)return void this._clearTimeout();const i=t.relatedTarget;this._element===i||this._element.contains(i)||this._maybeScheduleHide()}_setListeners(){j.on(this._element,"mouseover.bs.toast",(t=>this._onInteraction(t,!0))),j.on(this._element,"mouseout.bs.toast",(t=>this._onInteraction(t,!1))),j.on(this._element,"focusin.bs.toast",(t=>this._onInteraction(t,!0))),j.on(this._element,"focusout.bs.toast",(t=>this._onInteraction(t,!1)))}_clearTimeout(){clearTimeout(this._timeout),this._timeout=null}static jQueryInterface(t){return this.each((function(){const e=Mn.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t])throw new TypeError(`No method named "${t}"`);e[t](this)}}))}}return R(Mn),g(Mn),{Alert:W,Button:z,Carousel:st,Collapse:pt,Dropdown:hi,Modal:Hi,Offcanvas:Fi,Popover:gn,ScrollSpy:An,Tab:xn,Toast:Mn,Tooltip:un}}));
+//# sourceMappingURL=bootstrap.bundle.min.js.map
\ No newline at end of file
diff --git a/docs/resources/stac_mount_save_files/libs/clipboard/clipboard.min.js b/docs/resources/stac_mount_save_files/libs/clipboard/clipboard.min.js
new file mode 100644
index 0000000..41c6a0f
--- /dev/null
+++ b/docs/resources/stac_mount_save_files/libs/clipboard/clipboard.min.js
@@ -0,0 +1,7 @@
+/*!
+ * clipboard.js v2.0.10
+ * https://clipboardjs.com/
+ *
+ * Licensed MIT © Zeno Rocha
+ */
+!function(t,e){"object"==typeof exports&&"object"==typeof module?module.exports=e():"function"==typeof define&&define.amd?define([],e):"object"==typeof exports?exports.ClipboardJS=e():t.ClipboardJS=e()}(this,function(){return n={686:function(t,e,n){"use strict";n.d(e,{default:function(){return o}});var e=n(279),i=n.n(e),e=n(370),u=n.n(e),e=n(817),c=n.n(e);function a(t){try{return document.execCommand(t)}catch(t){return}}var f=function(t){t=c()(t);return a("cut"),t};var l=function(t){var e,n,o,r=1<arguments.length&&void 0!==arguments[1]?arguments[1]:{container:document.body},i="";return"string"==typeof t?(e=t,n="rtl"===document.documentElement.getAttribute("dir"),(o=document.createElement("textarea")).style.fontSize="12pt",o.style.border="0",o.style.padding="0",o.style.margin="0",o.style.position="absolute",o.style[n?"right":"left"]="-9999px",n=window.pageYOffset||document.documentElement.scrollTop,o.style.top="".concat(n,"px"),o.setAttribute("readonly",""),o.value=e,o=o,r.container.appendChild(o),i=c()(o),a("copy"),o.remove()):(i=c()(t),a("copy")),i};function r(t){return(r="function"==typeof Symbol&&"symbol"==typeof Symbol.iterator?function(t){return typeof t}:function(t){return t&&"function"==typeof Symbol&&t.constructor===Symbol&&t!==Symbol.prototype?"symbol":typeof t})(t)}var s=function(){var t=0<arguments.length&&void 0!==arguments[0]?arguments[0]:{},e=t.action,n=void 0===e?"copy":e,o=t.container,e=t.target,t=t.text;if("copy"!==n&&"cut"!==n)throw new Error('Invalid "action" value, use either "copy" or "cut"');if(void 0!==e){if(!e||"object"!==r(e)||1!==e.nodeType)throw new Error('Invalid "target" value, use a valid Element');if("copy"===n&&e.hasAttribute("disabled"))throw new Error('Invalid "target" attribute. 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\ No newline at end of file
diff --git a/docs/resources/stac_mount_save_files/libs/quarto-html/anchor.min.js b/docs/resources/stac_mount_save_files/libs/quarto-html/anchor.min.js
new file mode 100644
index 0000000..1c2b86f
--- /dev/null
+++ b/docs/resources/stac_mount_save_files/libs/quarto-html/anchor.min.js
@@ -0,0 +1,9 @@
+// @license magnet:?xt=urn:btih:d3d9a9a6595521f9666a5e94cc830dab83b65699&dn=expat.txt Expat
+//
+// AnchorJS - v4.3.1 - 2021-04-17
+// https://www.bryanbraun.com/anchorjs/
+// Copyright (c) 2021 Bryan Braun; Licensed MIT
+//
+// @license magnet:?xt=urn:btih:d3d9a9a6595521f9666a5e94cc830dab83b65699&dn=expat.txt Expat
+!function(A,e){"use strict";"function"==typeof define&&define.amd?define([],e):"object"==typeof module&&module.exports?module.exports=e():(A.AnchorJS=e(),A.anchors=new A.AnchorJS)}(this,function(){"use strict";return function(A){function d(A){A.icon=Object.prototype.hasOwnProperty.call(A,"icon")?A.icon:"",A.visible=Object.prototype.hasOwnProperty.call(A,"visible")?A.visible:"hover",A.placement=Object.prototype.hasOwnProperty.call(A,"placement")?A.placement:"right",A.ariaLabel=Object.prototype.hasOwnProperty.call(A,"ariaLabel")?A.ariaLabel:"Anchor",A.class=Object.prototype.hasOwnProperty.call(A,"class")?A.class:"",A.base=Object.prototype.hasOwnProperty.call(A,"base")?A.base:"",A.truncate=Object.prototype.hasOwnProperty.call(A,"truncate")?Math.floor(A.truncate):64,A.titleText=Object.prototype.hasOwnProperty.call(A,"titleText")?A.titleText:""}function w(A){var e;if("string"==typeof A||A instanceof String)e=[].slice.call(document.querySelectorAll(A));else{if(!(Array.isArray(A)||A instanceof NodeList))throw new TypeError("The selector provided to AnchorJS was invalid.");e=[].slice.call(A)}return e}this.options=A||{},this.elements=[],d(this.options),this.isTouchDevice=function(){return Boolean("ontouchstart"in window||window.TouchEvent||window.DocumentTouch&&document instanceof DocumentTouch)},this.add=function(A){var e,t,o,i,n,s,a,c,r,l,h,u,p=[];if(d(this.options),"touch"===(l=this.options.visible)&&(l=this.isTouchDevice()?"always":"hover"),0===(e=w(A=A||"h2, h3, h4, h5, h6")).length)return this;for(null===document.head.querySelector("style.anchorjs")&&((u=document.createElement("style")).className="anchorjs",u.appendChild(document.createTextNode("")),void 0===(A=document.head.querySelector('[rel="stylesheet"],style'))?document.head.appendChild(u):document.head.insertBefore(u,A),u.sheet.insertRule(".anchorjs-link{opacity:0;text-decoration:none;-webkit-font-smoothing:antialiased;-moz-osx-font-smoothing:grayscale}",u.sheet.cssRules.length),u.sheet.insertRule(":hover>.anchorjs-link,.anchorjs-link:focus{opacity:1}",u.sheet.cssRules.length),u.sheet.insertRule("[data-anchorjs-icon]::after{content:attr(data-anchorjs-icon)}",u.sheet.cssRules.length),u.sheet.insertRule('@font-face{font-family:anchorjs-icons;src:url(data:n/a;base64,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) format("truetype")}',u.sheet.cssRules.length)),u=document.querySelectorAll("[id]"),t=[].map.call(u,function(A){return A.id}),i=0;i<e.length;i++)if(this.hasAnchorJSLink(e[i]))p.push(i);else{if(e[i].hasAttribute("id"))o=e[i].getAttribute("id");else if(e[i].hasAttribute("data-anchor-id"))o=e[i].getAttribute("data-anchor-id");else{for(c=a=this.urlify(e[i].textContent),s=0;n=t.indexOf(c=void 0!==n?a+"-"+s:c),s+=1,-1!==n;);n=void 0,t.push(c),e[i].setAttribute("id",c),o=c}(r=document.createElement("a")).className="anchorjs-link "+this.options.class,r.setAttribute("aria-label",this.options.ariaLabel),r.setAttribute("data-anchorjs-icon",this.options.icon),this.options.titleText&&(r.title=this.options.titleText),h=document.querySelector("base")?window.location.pathname+window.location.search:"",h=this.options.base||h,r.href=h+"#"+o,"always"===l&&(r.style.opacity="1"),""===this.options.icon&&(r.style.font="1em/1 anchorjs-icons","left"===this.options.placement&&(r.style.lineHeight="inherit")),"left"===this.options.placement?(r.style.position="absolute",r.style.marginLeft="-1em",r.style.paddingRight=".5em",e[i].insertBefore(r,e[i].firstChild)):(r.style.paddingLeft=".375em",e[i].appendChild(r))}for(i=0;i<p.length;i++)e.splice(p[i]-i,1);return this.elements=this.elements.concat(e),this},this.remove=function(A){for(var e,t,o=w(A),i=0;i<o.length;i++)(t=o[i].querySelector(".anchorjs-link"))&&(-1!==(e=this.elements.indexOf(o[i]))&&this.elements.splice(e,1),o[i].removeChild(t));return this},this.removeAll=function(){this.remove(this.elements)},this.urlify=function(A){var e=document.createElement("textarea");return e.innerHTML=A,A=e.value,this.options.truncate||d(this.options),A.trim().replace(/'/gi,"").replace(/[& +$,:;=?@"#{}|^~[`%!'<>\]./()*\\\n\t\b\v\u00A0]/g,"-").replace(/-{2,}/g,"-").substring(0,this.options.truncate).replace(/^-+|-+$/gm,"").toLowerCase()},this.hasAnchorJSLink=function(A){var 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+// @license-end
\ No newline at end of file
diff --git a/docs/resources/stac_mount_save_files/libs/quarto-html/popper.min.js b/docs/resources/stac_mount_save_files/libs/quarto-html/popper.min.js
new file mode 100644
index 0000000..2269d66
--- /dev/null
+++ b/docs/resources/stac_mount_save_files/libs/quarto-html/popper.min.js
@@ -0,0 +1,6 @@
+/**
+ * @popperjs/core v2.11.4 - MIT License
+ */
+
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+
diff --git a/docs/resources/stac_mount_save_files/libs/quarto-html/quarto-syntax-highlighting.css b/docs/resources/stac_mount_save_files/libs/quarto-html/quarto-syntax-highlighting.css
new file mode 100644
index 0000000..36cb328
--- /dev/null
+++ b/docs/resources/stac_mount_save_files/libs/quarto-html/quarto-syntax-highlighting.css
@@ -0,0 +1,171 @@
+/* quarto syntax highlight colors */
+:root {
+  --quarto-hl-ot-color: #003B4F;
+  --quarto-hl-at-color: #657422;
+  --quarto-hl-ss-color: #20794D;
+  --quarto-hl-an-color: #5E5E5E;
+  --quarto-hl-fu-color: #4758AB;
+  --quarto-hl-st-color: #20794D;
+  --quarto-hl-cf-color: #003B4F;
+  --quarto-hl-op-color: #5E5E5E;
+  --quarto-hl-er-color: #AD0000;
+  --quarto-hl-bn-color: #AD0000;
+  --quarto-hl-al-color: #AD0000;
+  --quarto-hl-va-color: #111111;
+  --quarto-hl-bu-color: inherit;
+  --quarto-hl-ex-color: inherit;
+  --quarto-hl-pp-color: #AD0000;
+  --quarto-hl-in-color: #5E5E5E;
+  --quarto-hl-vs-color: #20794D;
+  --quarto-hl-wa-color: #5E5E5E;
+  --quarto-hl-do-color: #5E5E5E;
+  --quarto-hl-im-color: #00769E;
+  --quarto-hl-ch-color: #20794D;
+  --quarto-hl-dt-color: #AD0000;
+  --quarto-hl-fl-color: #AD0000;
+  --quarto-hl-co-color: #5E5E5E;
+  --quarto-hl-cv-color: #5E5E5E;
+  --quarto-hl-cn-color: #8f5902;
+  --quarto-hl-sc-color: #5E5E5E;
+  --quarto-hl-dv-color: #AD0000;
+  --quarto-hl-kw-color: #003B4F;
+}
+
+/* other quarto variables */
+:root {
+  --quarto-font-monospace: SFMono-Regular, Menlo, Monaco, Consolas, "Liberation Mono", "Courier New", monospace;
+}
+
+pre > code.sourceCode > span {
+  color: #003B4F;
+}
+
+code span {
+  color: #003B4F;
+}
+
+code.sourceCode > span {
+  color: #003B4F;
+}
+
+div.sourceCode,
+div.sourceCode pre.sourceCode {
+  color: #003B4F;
+}
+
+code span.ot {
+  color: #003B4F;
+}
+
+code span.at {
+  color: #657422;
+}
+
+code span.ss {
+  color: #20794D;
+}
+
+code span.an {
+  color: #5E5E5E;
+}
+
+code span.fu {
+  color: #4758AB;
+}
+
+code span.st {
+  color: #20794D;
+}
+
+code span.cf {
+  color: #003B4F;
+}
+
+code span.op {
+  color: #5E5E5E;
+}
+
+code span.er {
+  color: #AD0000;
+}
+
+code span.bn {
+  color: #AD0000;
+}
+
+code span.al {
+  color: #AD0000;
+}
+
+code span.va {
+  color: #111111;
+}
+
+code span.pp {
+  color: #AD0000;
+}
+
+code span.in {
+  color: #5E5E5E;
+}
+
+code span.vs {
+  color: #20794D;
+}
+
+code span.wa {
+  color: #5E5E5E;
+  font-style: italic;
+}
+
+code span.do {
+  color: #5E5E5E;
+  font-style: italic;
+}
+
+code span.im {
+  color: #00769E;
+}
+
+code span.ch {
+  color: #20794D;
+}
+
+code span.dt {
+  color: #AD0000;
+}
+
+code span.fl {
+  color: #AD0000;
+}
+
+code span.co {
+  color: #5E5E5E;
+}
+
+code span.cv {
+  color: #5E5E5E;
+  font-style: italic;
+}
+
+code span.cn {
+  color: #8f5902;
+}
+
+code span.sc {
+  color: #5E5E5E;
+}
+
+code span.dv {
+  color: #AD0000;
+}
+
+code span.kw {
+  color: #003B4F;
+}
+
+.prevent-inlining {
+  content: "</";
+}
+
+/*# sourceMappingURL=debc5d5d77c3f9108843748ff7464032.css.map */
diff --git a/docs/resources/stac_mount_save_files/libs/quarto-html/quarto.js b/docs/resources/stac_mount_save_files/libs/quarto-html/quarto.js
new file mode 100644
index 0000000..c7e1c84
--- /dev/null
+++ b/docs/resources/stac_mount_save_files/libs/quarto-html/quarto.js
@@ -0,0 +1,667 @@
+const sectionChanged = new CustomEvent("quarto-sectionChanged", {
+  detail: {},
+  bubbles: true,
+  cancelable: false,
+  composed: false,
+});
+
+window.document.addEventListener("DOMContentLoaded", function (_event) {
+  const tocEl = window.document.querySelector('nav[role="doc-toc"]');
+  const sidebarEl = window.document.getElementById("quarto-sidebar");
+  const leftTocEl = window.document.getElementById("quarto-sidebar-toc-left");
+  const marginSidebarEl = window.document.getElementById(
+    "quarto-margin-sidebar"
+  );
+  // function to determine whether the element has a previous sibling that is active
+  const prevSiblingIsActiveLink = (el) => {
+    const sibling = el.previousElementSibling;
+    if (sibling && sibling.tagName === "A") {
+      return sibling.classList.contains("active");
+    } else {
+      return false;
+    }
+  };
+
+  // fire slideEnter for bootstrap tab activations (for htmlwidget resize behavior)
+  function fireSlideEnter(e) {
+    const event = window.document.createEvent("Event");
+    event.initEvent("slideenter", true, true);
+    window.document.dispatchEvent(event);
+  }
+  const tabs = window.document.querySelectorAll('a[data-bs-toggle="tab"]');
+  tabs.forEach((tab) => {
+    tab.addEventListener("shown.bs.tab", fireSlideEnter);
+  });
+
+  // Track scrolling and mark TOC links as active
+  // get table of contents and sidebar (bail if we don't have at least one)
+  const tocLinks = tocEl
+    ? [...tocEl.querySelectorAll("a[data-scroll-target]")]
+    : [];
+  const makeActive = (link) => tocLinks[link].classList.add("active");
+  const removeActive = (link) => tocLinks[link].classList.remove("active");
+  const removeAllActive = () =>
+    [...Array(tocLinks.length).keys()].forEach((link) => removeActive(link));
+
+  // activate the anchor for a section associated with this TOC entry
+  tocLinks.forEach((link) => {
+    link.addEventListener("click", () => {
+      if (link.href.indexOf("#") !== -1) {
+        const anchor = link.href.split("#")[1];
+        const heading = window.document.querySelector(
+          `[data-anchor-id=${anchor}]`
+        );
+        if (heading) {
+          // Add the class
+          heading.classList.add("reveal-anchorjs-link");
+
+          // function to show the anchor
+          const handleMouseout = () => {
+            heading.classList.remove("reveal-anchorjs-link");
+            heading.removeEventListener("mouseout", handleMouseout);
+          };
+
+          // add a function to clear the anchor when the user mouses out of it
+          heading.addEventListener("mouseout", handleMouseout);
+        }
+      }
+    });
+  });
+
+  const sections = tocLinks.map((link) => {
+    const target = link.getAttribute("data-scroll-target");
+    if (target.startsWith("#")) {
+      return window.document.getElementById(decodeURI(`${target.slice(1)}`));
+    } else {
+      return window.document.querySelector(decodeURI(`${target}`));
+    }
+  });
+
+  const sectionMargin = 200;
+  let currentActive = 0;
+  // track whether we've initialized state the first time
+  let init = false;
+
+  const updateActiveLink = () => {
+    // The index from bottom to top (e.g. reversed list)
+    let sectionIndex = -1;
+    if (
+      window.innerHeight + window.pageYOffset >=
+      window.document.body.offsetHeight
+    ) {
+      sectionIndex = 0;
+    } else {
+      sectionIndex = [...sections].reverse().findIndex((section) => {
+        if (section) {
+          return window.pageYOffset >= section.offsetTop - sectionMargin;
+        } else {
+          return false;
+        }
+      });
+    }
+    if (sectionIndex > -1) {
+      const current = sections.length - sectionIndex - 1;
+      if (current !== currentActive) {
+        removeAllActive();
+        currentActive = current;
+        makeActive(current);
+        if (init) {
+          window.dispatchEvent(sectionChanged);
+        }
+        init = true;
+      }
+    }
+  };
+
+  const inHiddenRegion = (top, bottom, hiddenRegions) => {
+    for (const region of hiddenRegions) {
+      if (top <= region.bottom && bottom >= region.top) {
+        return true;
+      }
+    }
+    return false;
+  };
+
+  const categorySelector = "header.quarto-title-block .quarto-category";
+  const activateCategories = (href) => {
+    // Find any categories
+    // Surround them with a link pointing back to:
+    // #category=Authoring
+    try {
+      const categoryEls = window.document.querySelectorAll(categorySelector);
+      for (const categoryEl of categoryEls) {
+        const categoryText = categoryEl.textContent;
+        if (categoryText) {
+          const link = `${href}#category=${encodeURIComponent(categoryText)}`;
+          const linkEl = window.document.createElement("a");
+          linkEl.setAttribute("href", link);
+          for (const child of categoryEl.childNodes) {
+            linkEl.append(child);
+          }
+          categoryEl.appendChild(linkEl);
+        }
+      }
+    } catch {
+      // Ignore errors
+    }
+  };
+  function hasTitleCategories() {
+    return window.document.querySelector(categorySelector) !== null;
+  }
+
+  function offsetRelativeUrl(url) {
+    const offset = getMeta("quarto:offset");
+    return offset ? offset + url : url;
+  }
+
+  function offsetAbsoluteUrl(url) {
+    const offset = getMeta("quarto:offset");
+    const baseUrl = new URL(offset, window.location);
+
+    const projRelativeUrl = url.replace(baseUrl, "");
+    if (projRelativeUrl.startsWith("/")) {
+      return projRelativeUrl;
+    } else {
+      return "/" + projRelativeUrl;
+    }
+  }
+
+  // read a meta tag value
+  function getMeta(metaName) {
+    const metas = window.document.getElementsByTagName("meta");
+    for (let i = 0; i < metas.length; i++) {
+      if (metas[i].getAttribute("name") === metaName) {
+        return metas[i].getAttribute("content");
+      }
+    }
+    return "";
+  }
+
+  async function findAndActivateCategories() {
+    const currentPagePath = offsetAbsoluteUrl(window.location.href);
+    const response = await fetch(offsetRelativeUrl("listings.json"));
+    if (response.status == 200) {
+      return response.json().then(function (listingPaths) {
+        const listingHrefs = [];
+        for (const listingPath of listingPaths) {
+          const pathWithoutLeadingSlash = listingPath.listing.substring(1);
+          for (const item of listingPath.items) {
+            if (
+              item === currentPagePath ||
+              item === currentPagePath + "index.html"
+            ) {
+              // Resolve this path against the offset to be sure
+              // we already are using the correct path to the listing
+              // (this adjusts the listing urls to be rooted against
+              // whatever root the page is actually running against)
+              const relative = offsetRelativeUrl(pathWithoutLeadingSlash);
+              const baseUrl = window.location;
+              const resolvedPath = new URL(relative, baseUrl);
+              listingHrefs.push(resolvedPath.pathname);
+              break;
+            }
+          }
+        }
+
+        // Look up the tree for a nearby linting and use that if we find one
+        const nearestListing = findNearestParentListing(
+          offsetAbsoluteUrl(window.location.pathname),
+          listingHrefs
+        );
+        if (nearestListing) {
+          activateCategories(nearestListing);
+        } else {
+          // See if the referrer is a listing page for this item
+          const referredRelativePath = offsetAbsoluteUrl(document.referrer);
+          const referrerListing = listingHrefs.find((listingHref) => {
+            const isListingReferrer =
+              listingHref === referredRelativePath ||
+              listingHref === referredRelativePath + "index.html";
+            return isListingReferrer;
+          });
+
+          if (referrerListing) {
+            // Try to use the referrer if possible
+            activateCategories(referrerListing);
+          } else if (listingHrefs.length > 0) {
+            // Otherwise, just fall back to the first listing
+            activateCategories(listingHrefs[0]);
+          }
+        }
+      });
+    }
+  }
+  if (hasTitleCategories()) {
+    findAndActivateCategories();
+  }
+
+  const findNearestParentListing = (href, listingHrefs) => {
+    if (!href || !listingHrefs) {
+      return undefined;
+    }
+    // Look up the tree for a nearby linting and use that if we find one
+    const relativeParts = href.substring(1).split("/");
+    while (relativeParts.length > 0) {
+      const path = relativeParts.join("/");
+      for (const listingHref of listingHrefs) {
+        if (listingHref.startsWith(path)) {
+          return listingHref;
+        }
+      }
+      relativeParts.pop();
+    }
+
+    return undefined;
+  };
+
+  const manageSidebarVisiblity = (el, placeholderDescriptor) => {
+    let isVisible = true;
+
+    return (hiddenRegions) => {
+      if (el === null) {
+        return;
+      }
+
+      // Find the last element of the TOC
+      const lastChildEl = el.lastElementChild;
+
+      if (lastChildEl) {
+        // Find the top and bottom o the element that is being managed
+        const elTop = el.offsetTop;
+        const elBottom =
+          elTop + lastChildEl.offsetTop + lastChildEl.offsetHeight;
+
+        // Converts the sidebar to a menu
+        const convertToMenu = () => {
+          for (const child of el.children) {
+            child.style.opacity = 0;
+            child.style.display = "none";
+          }
+
+          const toggleContainer = window.document.createElement("div");
+          toggleContainer.style.width = "100%";
+          toggleContainer.classList.add("zindex-over-content");
+          toggleContainer.classList.add("quarto-sidebar-toggle");
+          toggleContainer.classList.add("headroom-target"); // Marks this to be managed by headeroom
+          toggleContainer.id = placeholderDescriptor.id;
+          toggleContainer.style.position = "fixed";
+
+          const toggleIcon = window.document.createElement("i");
+          toggleIcon.classList.add("quarto-sidebar-toggle-icon");
+          toggleIcon.classList.add("bi");
+          toggleIcon.classList.add("bi-caret-down-fill");
+
+          const toggleTitle = window.document.createElement("div");
+          const titleEl = window.document.body.querySelector(
+            placeholderDescriptor.titleSelector
+          );
+          if (titleEl) {
+            toggleTitle.append(titleEl.innerText, toggleIcon);
+          }
+          toggleTitle.classList.add("zindex-over-content");
+          toggleTitle.classList.add("quarto-sidebar-toggle-title");
+          toggleContainer.append(toggleTitle);
+
+          const toggleContents = window.document.createElement("div");
+          toggleContents.classList = el.classList;
+          toggleContents.classList.add("zindex-over-content");
+          toggleContents.classList.add("quarto-sidebar-toggle-contents");
+          for (const child of el.children) {
+            if (child.id === "toc-title") {
+              continue;
+            }
+
+            const clone = child.cloneNode(true);
+            clone.style.opacity = 1;
+            clone.style.display = null;
+            toggleContents.append(clone);
+          }
+          toggleContents.style.height = "0px";
+          toggleContainer.append(toggleContents);
+          el.parentElement.prepend(toggleContainer);
+
+          // Process clicks
+          let tocShowing = false;
+          // Allow the caller to control whether this is dismissed
+          // when it is clicked (e.g. sidebar navigation supports
+          // opening and closing the nav tree, so don't dismiss on click)
+          const clickEl = placeholderDescriptor.dismissOnClick
+            ? toggleContainer
+            : toggleTitle;
+
+          const closeToggle = () => {
+            if (tocShowing) {
+              toggleContainer.classList.remove("expanded");
+              toggleContents.style.height = "0px";
+              tocShowing = false;
+            }
+          };
+
+          const positionToggle = () => {
+            // position the element (top left of parent, same width as parent)
+            const elRect = el.getBoundingClientRect();
+            toggleContainer.style.left = `${elRect.left}px`;
+            toggleContainer.style.top = `${elRect.top}px`;
+            toggleContainer.style.width = `${elRect.width}px`;
+          };
+
+          // Get rid of any expanded toggle if the user scrolls
+          window.document.addEventListener(
+            "scroll",
+            throttle(() => {
+              closeToggle();
+            }, 50)
+          );
+
+          // Handle positioning of the toggle
+          window.addEventListener(
+            "resize",
+            throttle(() => {
+              positionToggle();
+            }, 50)
+          );
+          positionToggle();
+
+          // Process the click
+          clickEl.onclick = () => {
+            if (!tocShowing) {
+              toggleContainer.classList.add("expanded");
+              toggleContents.style.height = null;
+              tocShowing = true;
+            } else {
+              closeToggle();
+            }
+          };
+        };
+
+        // Converts a sidebar from a menu back to a sidebar
+        const convertToSidebar = () => {
+          for (const child of el.children) {
+            child.style.opacity = 1;
+            clone.style.display = null;
+          }
+
+          const placeholderEl = window.document.getElementById(
+            placeholderDescriptor.id
+          );
+          if (placeholderEl) {
+            placeholderEl.remove();
+          }
+
+          el.classList.remove("rollup");
+        };
+
+        if (isReaderMode()) {
+          convertToMenu();
+          isVisible = false;
+        } else {
+          if (!isVisible) {
+            // If the element is current not visible reveal if there are
+            // no conflicts with overlay regions
+            if (!inHiddenRegion(elTop, elBottom, hiddenRegions)) {
+              convertToSidebar();
+              isVisible = true;
+            }
+          } else {
+            // If the element is visible, hide it if it conflicts with overlay regions
+            // and insert a placeholder toggle (or if we're in reader mode)
+            if (inHiddenRegion(elTop, elBottom, hiddenRegions)) {
+              convertToMenu();
+              isVisible = false;
+            }
+          }
+        }
+      }
+    };
+  };
+
+  // Find any conflicting margin elements and add margins to the
+  // top to prevent overlap
+  const marginChildren = window.document.querySelectorAll(
+    ".column-margin.column-container > * "
+  );
+  let lastBottom = 0;
+  for (const marginChild of marginChildren) {
+    const top = marginChild.getBoundingClientRect().top;
+    if (top < lastBottom) {
+      const margin = lastBottom - top;
+      marginChild.style.marginTop = `${margin}px`;
+    }
+    const styles = window.getComputedStyle(marginChild);
+    const marginTop = parseFloat(styles["marginTop"]);
+
+    lastBottom = top + marginChild.getBoundingClientRect().height + marginTop;
+  }
+
+  // Manage the visibility of the toc and the sidebar
+  const marginScrollVisibility = manageSidebarVisiblity(marginSidebarEl, {
+    id: "quarto-toc-toggle",
+    titleSelector: "#toc-title",
+    dismissOnClick: true,
+  });
+  const sidebarScrollVisiblity = manageSidebarVisiblity(sidebarEl, {
+    id: "quarto-sidebarnav-toggle",
+    titleSelector: ".title",
+    dismissOnClick: false,
+  });
+  let tocLeftScrollVisibility;
+  if (leftTocEl) {
+    tocLeftScrollVisibility = manageSidebarVisiblity(leftTocEl, {
+      id: "quarto-lefttoc-toggle",
+      titleSelector: "#toc-title",
+      dismissOnClick: true,
+    });
+  }
+
+  // Find the first element that uses formatting in special columns
+  const conflictingEls = window.document.body.querySelectorAll(
+    '[class^="column-"], [class*=" column-"], aside, [class*="margin-caption"], [class*=" margin-caption"], [class*="margin-ref"], [class*=" margin-ref"]'
+  );
+
+  // Filter all the possibly conflicting elements into ones
+  // the do conflict on the left or ride side
+  const arrConflictingEls = Array.from(conflictingEls);
+  const leftSideConflictEls = arrConflictingEls.filter((el) => {
+    if (el.tagName === "ASIDE") {
+      return false;
+    }
+    return Array.from(el.classList).find((className) => {
+      return (
+        className !== "column-body" &&
+        className.startsWith("column-") &&
+        !className.endsWith("right") &&
+        !className.endsWith("container") &&
+        className !== "column-margin"
+      );
+    });
+  });
+  const rightSideConflictEls = arrConflictingEls.filter((el) => {
+    if (el.tagName === "ASIDE") {
+      return true;
+    }
+
+    const hasMarginCaption = Array.from(el.classList).find((className) => {
+      return className == "margin-caption";
+    });
+    if (hasMarginCaption) {
+      return true;
+    }
+
+    return Array.from(el.classList).find((className) => {
+      return (
+        className !== "column-body" &&
+        !className.endsWith("container") &&
+        className.startsWith("column-") &&
+        !className.endsWith("left")
+      );
+    });
+  });
+
+  const kOverlapPaddingSize = 10;
+  function toRegions(els) {
+    return els.map((el) => {
+      const top =
+        el.getBoundingClientRect().top +
+        document.documentElement.scrollTop -
+        kOverlapPaddingSize;
+      return {
+        top,
+        bottom: top + el.scrollHeight + 2 * kOverlapPaddingSize,
+      };
+    });
+  }
+
+  const hideOverlappedSidebars = () => {
+    marginScrollVisibility(toRegions(rightSideConflictEls));
+    sidebarScrollVisiblity(toRegions(leftSideConflictEls));
+    if (tocLeftScrollVisibility) {
+      tocLeftScrollVisibility(toRegions(leftSideConflictEls));
+    }
+  };
+
+  window.quartoToggleReader = () => {
+    // Applies a slow class (or removes it)
+    // to update the transition speed
+    const slowTransition = (slow) => {
+      const manageTransition = (id, slow) => {
+        const el = document.getElementById(id);
+        if (el) {
+          if (slow) {
+            el.classList.add("slow");
+          } else {
+            el.classList.remove("slow");
+          }
+        }
+      };
+
+      manageTransition("TOC", slow);
+      manageTransition("quarto-sidebar", slow);
+    };
+
+    const readerMode = !isReaderMode();
+    setReaderModeValue(readerMode);
+
+    // If we're entering reader mode, slow the transition
+    if (readerMode) {
+      slowTransition(readerMode);
+    }
+    highlightReaderToggle(readerMode);
+    hideOverlappedSidebars();
+
+    // If we're exiting reader mode, restore the non-slow transition
+    if (!readerMode) {
+      slowTransition(!readerMode);
+    }
+  };
+
+  const highlightReaderToggle = (readerMode) => {
+    const els = document.querySelectorAll(".quarto-reader-toggle");
+    if (els) {
+      els.forEach((el) => {
+        if (readerMode) {
+          el.classList.add("reader");
+        } else {
+          el.classList.remove("reader");
+        }
+      });
+    }
+  };
+
+  const setReaderModeValue = (val) => {
+    if (window.location.protocol !== "file:") {
+      window.localStorage.setItem("quarto-reader-mode", val);
+    } else {
+      localReaderMode = val;
+    }
+  };
+
+  const isReaderMode = () => {
+    if (window.location.protocol !== "file:") {
+      return window.localStorage.getItem("quarto-reader-mode") === "true";
+    } else {
+      return localReaderMode;
+    }
+  };
+  let localReaderMode = null;
+
+  // Walk the TOC and collapse/expand nodes
+  // Nodes are expanded if:
+  // - they are top level
+  // - they have children that are 'active' links
+  // - they are directly below an link that is 'active'
+  const walk = (el, depth) => {
+    // Tick depth when we enter a UL
+    if (el.tagName === "UL") {
+      depth = depth + 1;
+    }
+
+    // It this is active link
+    let isActiveNode = false;
+    if (el.tagName === "A" && el.classList.contains("active")) {
+      isActiveNode = true;
+    }
+
+    // See if there is an active child to this element
+    let hasActiveChild = false;
+    for (child of el.children) {
+      hasActiveChild = walk(child, depth) || hasActiveChild;
+    }
+
+    // Process the collapse state if this is an UL
+    if (el.tagName === "UL") {
+      if (depth === 1 || hasActiveChild || prevSiblingIsActiveLink(el)) {
+        el.classList.remove("collapse");
+      } else {
+        el.classList.add("collapse");
+      }
+
+      // untick depth when we leave a UL
+      depth = depth - 1;
+    }
+    return hasActiveChild || isActiveNode;
+  };
+
+  // walk the TOC and expand / collapse any items that should be shown
+
+  if (tocEl) {
+    walk(tocEl, 0);
+    updateActiveLink();
+  }
+
+  // Throttle the scroll event and walk peridiocally
+  window.document.addEventListener(
+    "scroll",
+    throttle(() => {
+      if (tocEl) {
+        updateActiveLink();
+        walk(tocEl, 0);
+      }
+      if (!isReaderMode()) {
+        hideOverlappedSidebars();
+      }
+    }, 5)
+  );
+  window.addEventListener(
+    "resize",
+    throttle(() => {
+      if (!isReaderMode()) {
+        hideOverlappedSidebars();
+      }
+    }, 10)
+  );
+  hideOverlappedSidebars();
+  highlightReaderToggle(isReaderMode());
+});
+
+function throttle(func, wait) {
+  let waiting = false;
+  return function () {
+    if (!waiting) {
+      func.apply(this, arguments);
+      waiting = true;
+      setTimeout(function () {
+        waiting = false;
+      }, wait);
+    }
+  };
+}
diff --git a/docs/resources/stac_mount_save_files/libs/quarto-html/tippy.css b/docs/resources/stac_mount_save_files/libs/quarto-html/tippy.css
new file mode 100644
index 0000000..e6ae635
--- /dev/null
+++ b/docs/resources/stac_mount_save_files/libs/quarto-html/tippy.css
@@ -0,0 +1 @@
+.tippy-box[data-animation=fade][data-state=hidden]{opacity:0}[data-tippy-root]{max-width:calc(100vw - 10px)}.tippy-box{position:relative;background-color:#333;color:#fff;border-radius:4px;font-size:14px;line-height:1.4;white-space:normal;outline:0;transition-property:transform,visibility,opacity}.tippy-box[data-placement^=top]>.tippy-arrow{bottom:0}.tippy-box[data-placement^=top]>.tippy-arrow:before{bottom:-7px;left:0;border-width:8px 8px 0;border-top-color:initial;transform-origin:center top}.tippy-box[data-placement^=bottom]>.tippy-arrow{top:0}.tippy-box[data-placement^=bottom]>.tippy-arrow:before{top:-7px;left:0;border-width:0 8px 8px;border-bottom-color:initial;transform-origin:center bottom}.tippy-box[data-placement^=left]>.tippy-arrow{right:0}.tippy-box[data-placement^=left]>.tippy-arrow:before{border-width:8px 0 8px 8px;border-left-color:initial;right:-7px;transform-origin:center left}.tippy-box[data-placement^=right]>.tippy-arrow{left:0}.tippy-box[data-placement^=right]>.tippy-arrow:before{left:-7px;border-width:8px 8px 8px 0;border-right-color:initial;transform-origin:center right}.tippy-box[data-inertia][data-state=visible]{transition-timing-function:cubic-bezier(.54,1.5,.38,1.11)}.tippy-arrow{width:16px;height:16px;color:#333}.tippy-arrow:before{content:"";position:absolute;border-color:transparent;border-style:solid}.tippy-content{position:relative;padding:5px 9px;z-index:1}
\ No newline at end of file
diff --git a/docs/resources/stac_mount_save_files/libs/quarto-html/tippy.umd.min.js b/docs/resources/stac_mount_save_files/libs/quarto-html/tippy.umd.min.js
new file mode 100644
index 0000000..ca292be
--- /dev/null
+++ b/docs/resources/stac_mount_save_files/libs/quarto-html/tippy.umd.min.js
@@ -0,0 +1,2 @@
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+
diff --git a/docs/resources/third_meeting_notes.md b/docs/resources/third_meeting_notes.md
new file mode 100644
index 0000000..19abeda
--- /dev/null
+++ b/docs/resources/third_meeting_notes.md
@@ -0,0 +1,83 @@
+# Primary Meeting Day 11-15: Finalization and Conclusion
+
+## Meeting Details
+- **Dates:**
+- **Times:**
+- **Location:**
+- **Facilitator:**
+
+## Attendees
+- List of attendees
+
+## Daily Agenda
+
+### Day 11: Alignment and Focus
+
+#### Realigning Objectives
+- Review the project's main goals to ensure alignment with the final output.
+- Address any misalignments or deviations from the original plan.
+
+#### Prioritization of Tasks
+- Identify critical tasks that need to be completed.
+- Allocate resources and efforts to ensure these priorities are met.
+
+### Day 12-14: Intensive Work Period
+
+#### Task Completion
+- Dedicated time for team members to complete their individual contributions.
+- Regular check-ins to track progress and address any blockers.
+
+#### Integration of Work
+- Begin to combine individual contributions into a cohesive whole.
+- Review the integration to ensure consistency and coherency across the project.
+
+#### Final Reviews and Edits
+- Conduct thorough reviews of the project's outputs.
+- Perform final edits to refine the quality of the work.
+
+### Day 15: Closure and Celebration
+
+#### Final Presentation
+- Present the completed project to the group.
+- Discuss any last-minute adjustments or refinements needed.
+
+#### Reflective Session
+- Reflect on the achievements and learnings from the project.
+- Share appreciation for the team's hard work and dedication.
+
+#### Celebration
+- Acknowledge the successful completion of the project.
+- Plan for any dissemination of the project's findings or outputs.
+
+## Detailed Notes
+
+### Day 11 Notes
+- ...
+
+### Day 12 Notes
+- ...
+
+### Day 13 Notes
+- ...
+
+### Day 14 Notes
+- ...
+
+### Day 15 Notes
+- ...
+
+## Action Items
+- [ ] Finalize manuscript for publication: Assigned to - Deadline
+- [ ] Prepare data for repository submission: Assigned to - Deadline
+- [ ] Organize project materials for archival: Assigned to - Deadline
+- ...
+
+## Reflections and Comments
+- (Space for any additional thoughts, insights, or personal reflections on the meeting and the project as a whole.)
+
+## Next Steps
+- Define the publication and dissemination plan.
+- Outline any follow-up research or projects that have stemmed from this work.
+
+## Additional Documentation
+- (Include or link to any additional documents, charts, or resources that were created or referenced during the meeting.)
diff --git a/docs/resources/visualizations.md b/docs/resources/visualizations.md
new file mode 100644
index 0000000..2857a8b
--- /dev/null
+++ b/docs/resources/visualizations.md
@@ -0,0 +1,50 @@
+# Visualization Strategy and Development Documentation
+
+## Overview
+- Brief overview of the visualization goals and their alignment with the overall project objectives.
+
+## Visualization Strategy
+
+### Identifying Key Messages
+- Discuss main messages or insights to communicate through visualizations.
+- Identify target audience and their specific needs.
+
+### Selecting Appropriate Visualization Types
+- Explore different types of visualizations (charts, graphs, 3D, interactive elements) suitable for the data and message.
+- Brainstorm creative visualization approaches.
+
+## Visualization Development
+
+### Code-Generated Visualizations
+- Outline initial visualizations generated from the data pipeline.
+- Include code snippets and explanations.
+
+```python
+# Example Python code for a basic plot
+import matplotlib.pyplot as plt
+plt.plot(data['x'], data['y'])
+plt.show()
+```
+
+### Enhancing Visualizations
+- Steps for annotating, animating, creating 3D, immersive, or interactive visualizations.
+- Discuss challenges and solutions in enhancing visuals.
+
+### Versioning and Iterations
+- Document different versions and iterations of visualizations.
+- Reflect on improvements or changes in each version.
+
+### Finalizing Visualizations
+- Process of finalizing visuals for presentation or publication.
+- Feedback incorporation from team or test audiences.
+
+### Documentation of Tools and Resources
+- List software, libraries, and tools used for visualization.
+- Reference external resources or tutorials.
+
+### Conclusions
+- Summarize the visualization process and contributions to the project.
+- Reflect on lessons learned and potential future improvements.
+
+### References
+- Cite external sources, inspirations, or frameworks used in visualization.
diff --git a/docs/resources/working_groups_and_postdocs.md b/docs/resources/working_groups_and_postdocs.md
new file mode 100644
index 0000000..ffa9ca5
--- /dev/null
+++ b/docs/resources/working_groups_and_postdocs.md
@@ -0,0 +1,30 @@
+# ESIIL Postdoctoral Researcher Responsibilities and Opportunities
+
+## Primary Responsibilities
+
+- **Independent Research:**
+   - Conducting self-proposed research projects.
+   - Adhering to open data principles.
+- **Data and Code Storage:**
+   - Storing all research code and data in the designated ESIIL repository.
+- **Use of CyVerse:**
+   - Utilizing CyVerse as the primary computational platform.
+
+## Opportunities for Collaboration
+
+- **Joining Working Groups:**
+   - Opportunity to collaborate with working groups within ESIIL, subject to invitation.
+- **Networking and Collaboration:**
+   - Engaging in regular meetings and seminars for networking.
+
+## Additional Responsibilities
+
+- **Reviewing Working Group Applications:**
+   - Assisting in the review process of working group applications.
+- **Supporting Working Groups:**
+   - Providing support to working groups in various capacities, even if not an author.
+
+## Note
+- Primary research commitments should be prioritized unless otherwise directed by supervisors or ESIIL's administrative body.
+
+This framework ensures that ESIIL postdocs balance independent research with collaborative opportunities, adhering to open data principles, and utilizing designated platforms for their work.
diff --git a/mkdocs.yml b/mkdocs.yml
new file mode 100644
index 0000000..0743960
--- /dev/null
+++ b/mkdocs.yml
@@ -0,0 +1,91 @@
+site_name: 'ESIIL Postdoctoral Researcher OASIS'
+site_description: 'Central resource for ESIIL postdoctoral researchers'
+site_author: Ty Tuff
+site_url: https://cu-esiil.github.io/Postdoc_OASIS
+
+# Repository
+repo_name: Postdoc_OASIS
+repo_url: https://github.com/CU-ESIIL/Postdoc_OASIS
+edit_uri: edit/main/docs/
+# Copyright
+copyright: 'Copyright &copy; 2023 University of Colorado Boulder'
+
+# Page tree
+nav:
+  - Home: index.md
+  - Resources:
+       - Code of Conduct: resources/code-of-conduct.md
+       - Participant agreement: resources/participant_agreement.md
+       - R and Python bilingualism: resources/bilingualism_md.md
+       - STAC: resources/stac_mount_save.md
+       - Sentinal 2 STAC example: resources/Pull_Sentinal2_l2_data.md
+       - Markdown: resources/markdown_basics.md
+       - Cyverse basics: resources/cyverse_basics.md
+       - Github basics: resources/github_basics.md
+       - Cyverse hacks: resources/cyverse_hacks.md
+       - Docker basics: resources/docker_basics.md
+       - Working groups: resources/working_groups_and_postdocs.md
+  - Notes:
+       - OASIS orientation: resources/pre_meeting_notes.md
+  - Code documentation:
+       - Data processing: resources/data_processing.md
+       - Data analysis: resources/data_analysis.md
+       - Visualizations: resources/visualizations.md 
+  - Manuscript drafts:
+       - Manuscript: resources/manuscript.md
+  - References:
+       - Notes from readings: resources/notes_from_readings.md
+       - Citations: resources/citations.md
+
+# Configuration
+theme:
+  highlightjs: true
+  name: material
+  font:
+    text: 'Open Sans'
+    code: 'Roboto Mono'
+  logo: 'assets/ESIIL_logo.png'
+  favicon: 'assets/favicon.ico'
+  # setting features for the navigation tab
+  features:
+    - navigation.sections
+    - navigation.instant
+    - navigation.tracking
+    - navigation.indexes
+    - navigation.top
+    - toc.integrate
+    - toc.follow
+    - content.code.copy
+  # Default values, taken from mkdocs_theme.yml
+  language: en
+  palette:
+    # Palette toggle for light mode
+    - media: "(prefers-color-scheme: white)"
+      primary: 'white'
+      toggle:
+        icon: material/weather-night
+        name: Switch to dark mode
+
+    # Palette toggle for dark mode
+    - media: "(prefers-color-scheme: dark)"
+      scheme: slate
+      toggle:
+        icon: material/weather-sunny
+        name: Switch to system preference
+
+# Options
+extra:
+  social:
+    - icon: fontawesome/brands/github
+      link: https://github.com/cu-esiil/
+
+extra_css:
+  - stylesheets/extra.css
+
+plugins:
+    - search
+    - mkdocstrings
+    - git-revision-date
+    - mkdocs-jupyter:
+          include_source: True
+          ignore_h1_titles: True
diff --git a/requirements.txt b/requirements.txt
new file mode 100644
index 0000000..c3bae1f
--- /dev/null
+++ b/requirements.txt
@@ -0,0 +1,33 @@
+bump2version
+coverage
+flake8
+grip
+ipykernel
+livereload
+nbconvert==6.5
+pip
+sphinx
+tox
+twine
+watchdog
+wheel
+mkdocs-git-revision-date-plugin 
+mkdocs-jupyter 
+mkdocs-material 
+mkdocs-pdf-export-plugin
+mkdocstrings 
+mkdocstrings-crystal
+mkdocstrings-python-legacy
+
+# Requirements for core
+jinja2>=3.0
+markdown>=3.2
+mkdocs==1.5.3
+mkdocs-material-extensions>=1.1
+pygments>=2.14
+pymdown-extensions>=9.9.1
+
+# Requirements for plugins
+colorama>=0.4
+regex>=2022.4.24
+requests>=2.26