lunasilvestre / ee_lst

Python package to estimate Land Surface Temperatures from Google Earth Engine's Landsat imagery

ee_lst

ee_lst is a Python package designed to provide functionalities related to Land Surface Temperature (LST) computation using the Landsat series of satellites. This package expands the use of the original Google Earth Engine (GEE) code, initially crafted in JavaScript by Sofia Ermida. Transitioning to Python not only grants more versatility to the code but also broadens its accessibility. The original repository by Sofia Ermida can be accessed here.

Table of Contents

• Installation
• Usage
• Refactoring Validation
• Examples
• Documentation
• Workflows
• Testing
• Reference
• Contributing
• License

Installation

To install the ee_lst package, follow these steps:

# Clone the repository
git clone https://github.com/lunasilvestre/ee_lst.git

# Navigate to the repository directory
cd ee_lst

# Install the package and its dependencies
pip install . && pip install -r requirements.txt

Usage

For using this package with Docker, especially regarding handling credentials, see this guide.

Refactoring Validation

Ensuring consistent outputs between the original JavaScript version and the refactored Python library is of paramount importance. We've established a validation process housed within the validation directory to ensure consistency. This process, largely automated by the refactoring_validation.yml workflow, involves:

• Adapting the original JavaScript library for NodeJS execution.
• Containerizing both the adapted JavaScript and refactored Python libraries using Docker.
• Generating GeoTIFF outputs from both libraries.
• Comparing these outputs for discrepancies.

More details about this validation process, including its structure and exact steps, can be found in the validation README.

Examples

Locate examples in the examples directory. To execute one:

python examples/example_1.py

More examples will be available soon.

Documentation

Documentation is housed in the docs directory. Also find a copy of Ermida et al. (2020) there.

Workflows

For insights into our CI/CD procedures and other workflows, peruse the workflows directory.

Testing

Tests reside in the tests directory. To initiate them:

pytest tests/

For a deeper dive into testing, check out the tests README

Reference

If leveraging this code or its derivative data, kindly cite:

Ermida, S.L., Soares, P., Mantas, V., Göttsche, F.-M., Trigo, I.F., 2020. Google Earth Engine open-source code for Land Surface Temperature estimation from the Landsat series. Remote Sensing, 12 (9), 1471; https://doi.org/10.3390/rs12091471

Contributing

Contributions are welcome! Please read the contributing guidelines (if available) before making any changes.

License

For licensing details, view the LICENSE file.