Calculate environmental risk metrics for a given polygon
Project description
Environmental Risk Metrics
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
-
Clone the Repository
pip install environmental-risk-metrics
Examples
Using Jupyter Notebooks
Interactive analysis can be performed using the provided Jupyter notebooks.
-
Navigate to the Notebooks Directory
cd notebooks
-
Launch Jupyter Notebook
jupyter notebook -
Open and Run the Desired Notebook
For example, open
01 - all_metrics.ipynbto explore environmental risk metrics calculations.
Contributing
Contributions are welcome! Please follow these steps:
-
Fork the Repository
-
Create a Feature Branch
git checkout -b feature/YourFeature
-
Commit Your Changes
git commit -m "Add some feature"
-
Push to the Branch
git push origin feature/YourFeature
-
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.
Project details
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