Merge branch 'feature/open_buildings' of https://github.com/wri/citie…

…s-cif into feature/smart_cities_lulc

README.md

@@ -5,6 +5,17 @@ The Cities Indicator Framework (CIF) is a set of Python tools to make it easier
 ## Quick start
 If all you want to do is use the CIF, the quickest way to get started is to use our [WRI Cities Indicator Framework Colab Notebook](https://colab.research.google.com/drive/1PV1H-godxJ6h42p74Ij9sdFh3T0RN-7j#scrollTo=eM14UgpmpZL-)
 
+## PR Review
+0. Prerequisites
+  1. Git
+    * On Windows I recommend WSL https://learn.microsoft.com/en-us/windows/wsl/tutorials/wsl-git
+  3. https://cli.github.com/
+    * On MacOS I recommend the Homebrew option
+    * If you don't have an ssh key, it will install one for you
+  4. Conda (or Mamba) to install dependencies
+    * If you have Homebrew `brew install --cask miniconda`
+
+
 ## Dependencies
 ### Conda
 `conda env create -f environment.yml`

docs/developer.md

@@ -79,6 +79,16 @@ Hopefully we already have the layers you need in `city_metrix/layers/` and you c
 
 4. Import the new layer class to [city_metrix/layers/\_\_init\_\_.py](../city_metrix/layers/__init__.py)
 
+5. Add a test to [tests/layers.py](../tests/layers.py) to ensure the new layer is working as expected.
+
+6. Add a section to the get layers.ipynb notebook to demonstrate how to use the new layer.
+
+7. Create a PR to merge the new layer into the main branch with these in the PR description:
+    - Link to Jira ticket (if any)
+    - A brief description of the new layer
+    - A link to the Airtable record for the new layer
+    - Explain how to test the new layer
+
 
 ## Adding an Indicator
 Once you have all the data layers you need as inputs, here is the process to create an indicator using them.

environment.yml

@@ -17,6 +17,7 @@ dependencies:
   - dask[complete]=2023.11.0
   - matplotlib=3.8.2
   - jupyterlab=4.0.10
+  - geemap=0.32.0
   - pip=23.3.1
   - pip:
     - cartoframes==1.2.5