Metadata-Version: 2.4
Name: environmental-risk-metrics
Version: 0.3.4
Summary: Calculate environmentalrisk metrics for a given polygon
Author-email: Thimm Zwiener <zwiener@gmail.com>, Thimm Zwiener <thimm@regenrate.com>
License-File: LICENSE
Requires-Python: >=3.10
Requires-Dist: beautifulsoup4>=4.12.0
Requires-Dist: geopandas>=1.0.1
Requires-Dist: geopy>=2.4.1
Requires-Dist: imageio>=2.31.0
Requires-Dist: ipython>=8.0.0
Requires-Dist: leafmap>=0.42.5
Requires-Dist: matplotlib>=3.7.0
Requires-Dist: numpy>=1.24.0
Requires-Dist: odc-stac>=0.3.10
Requires-Dist: pandas>=2.0.0
Requires-Dist: planetary-computer>=1.0.0
Requires-Dist: pyarrow>=18.1.0
Requires-Dist: pygbif>=0.6.5
Requires-Dist: pyproj>=3.5.0
Requires-Dist: pystac-client>=0.8.5
Requires-Dist: rasterstats>=0.20.0
Requires-Dist: requests>=2.31.0
Requires-Dist: rioxarray>=0.18.1
Requires-Dist: shapely>=2.0.0
Requires-Dist: tenacity>=8.2.0
Requires-Dist: tqdm>=4.65.0
Requires-Dist: xarray>=2023.1.0
Description-Content-Type: text/markdown

# Environmental Risk Metrics

![License](https://img.shields.io/badge/license-MIT-blue.svg)
![Python Version](https://img.shields.io/badge/Python-3.12%2B-blue.svg)

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

## Table of Contents

- [Features](#features)
- [Getting Started](#getting-started)
  - [Prerequisites](#prerequisites)
  - [Installation](#installation)
- [Usage](#usage)
  - [Running the API](#running-the-api)
  - [Using Jupyter Notebooks](#using-jupyter-notebooks)
- [Data Resources](#data-resources)
- [Contributing](#contributing)
- [License](#license)
- [Contact](#contact)

## 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](https://git-scm.com/)

### Installation

1. **Clone the Repository**

   ```bash
   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**

   ```bash
   cd notebooks
   ```

2. **Launch Jupyter Notebook**

   ```bash
   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**

   ```bash
   git checkout -b feature/YourFeature
   ```

3. **Commit Your Changes**

   ```bash
   git commit -m "Add some feature"
   ```

4. **Push to the Branch**

   ```bash
   git push origin feature/YourFeature
   ```

5. **Open a Pull Request**

## License

This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.

## Contact

Developed by [Thimm](mailto:thimm@regenrate.com). For any inquiries or feedback, please reach out via email.