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Environmental Risk Metrics

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Calculate environmental risk metrics for a given polygon using advanced geospatial and data processing tools.

Table of Contents

Features

  • NDVI Calculation: Compute Normalized Difference Vegetation Index (NDVI) values for specified polygons.
  • Sentinel-2 Integration: Load and process Sentinel-2 satellite data for various spectral bands.
  • Interactive Notebooks: Utilize Jupyter notebooks for data analysis and visualization.
  • Comprehensive Soil Data: Incorporates detailed soil type information for accurate risk assessment.
  • Protected Areas: Get nearest Ramsar protected sites for a given geometry
  • Social Indices: Get Global Witness data for the countries containing or intersecting the given geometry
  • Endangered Species: Get endangered species data for the countries containing or intersecting the given geometry
  • Climate Data: Get climate data for the countries containing or intersecting the given geometry

Getting Started

Prerequisites

  • Python 3.12+
  • Git

Installation

  1. Clone the Repository

    pip install environmental-risk-metrics

Examples

Using Jupyter Notebooks

Interactive analysis can be performed using the provided Jupyter notebooks.

  1. Navigate to the Notebooks Directory

    cd notebooks
  2. Launch Jupyter Notebook

    jupyter notebook
  3. Open and Run the Desired Notebook

    For example, open 01 - all_metrics.ipynb to explore environmental risk metrics calculations.

Contributing

Contributions are welcome! Please follow these steps:

  1. Fork the Repository

  2. Create a Feature Branch

    git checkout -b feature/YourFeature
  3. Commit Your Changes

    git commit -m "Add some feature"
  4. Push to the Branch

    git push origin feature/YourFeature
  5. Open a Pull Request

License

This project is licensed under the MIT License. See the LICENSE file for details.

Contact

Developed by Thimm. For any inquiries or feedback, please reach out via email.

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