LANDSAT Satellite Imageries

Remote Sensing Analytics with LANDSAT Satellite

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Table Of Contents

• About the Project
• Built With
• Getting Started
  • Prerequisites
  • Installation
• Usage
• Roadmap
• Contributing
• License
• Authors
• Acknowledgements

About The Project

One of the important urban and envirnomental planning metrics is the ambient temperature which correlates to thermal comfort. However we cannot have a accurate sensing of the ambient temperature because of the sparse ambient temperature sensors installed in Singapore.

We turn to USGS Landsat 8 satellite images to generate Land Surface Temperature (LST) maps. LST is the radiative skin temperature of the land derived from solar radiation. We use LST as a proxy to ambient temperature.

In this repository, you will find the scripts required to download, generate and stack LST maps.

Built With

• Anaconda
• R Studio

Getting Started

Prerequisites

Python Packages (in Conda)

conda install --file requirements.txt

R Packages (in R Studio)

maptools	rlist
raster	rstudioapi
RColorBrewer	sp
rgdal

install.packages(c("maptools", "raster", "RColorBrewer", "rgdal", "rlist", "rstudioapi", "sp"))

Installation

1. Register for an EarthExplorer account here.

2. Clone the repo

git clone https://github.com/hiewliwen/landsat.git

3. Install Python & R packages

4. REPLACE EARTHEXPLORER.PY WITH THIS

5. Enter your EarthExplorer credentials in CONFIG.py

Usage

Use this space to show useful examples of how a project can be used. Additional screenshots, code examples and demos work well in this space. You may also link to more resources.

For more examples, please refer to the Documentation

Roadmap

See the open issues for a list of proposed features (and known issues).

Contributing

Contributions are what make the open source community such an amazing place to be learn, inspire, and create. Any contributions you make are greatly appreciated.

• If you have suggestions for adding or removing projects, feel free to open an issue to discuss it, or directly create a pull request after you edit the README.md file with necessary changes.
• Please make sure you check your spelling and grammar.
• Create individual PR for each suggestion.

Creating A Pull Request

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

License

Distributed under the MIT License. See LICENSE for more information.

Authors

• HIEW Li Wen

Acknowledgements

• Yann Forget