Lunga-N/wildfire_app

A data-driven intelligence platform designed to enhance disaster preparedness and fire management in the Kingdom of Eswatini. # eSwatini Wildfire Predictor 🔥 The **eSwatini Wildfire Predictor** is a data-driven intelligence platform designed to enhance disaster preparedness and fire management in the Kingdom of Eswatini. By shifting from reactive firefighting to **anticipatory prevention**, this platform leverages advanced Machine Learning to identify wildfire risks before they escalate. ## 🚀 Key Features - **Wildfire Risk Prediction**: Uses a high-performance **XGBoost** model to calculate fire probability based on real time environmental data. - **Deep Data Analysis**: Explore spatiotemporal drivers of fire, including meteorology (ERA5), vegetation indices (NASA FIRMS/GEE), and human activity. - **Interactive Mapping**: Geographic distribution of risk factors and historical wildfire clusters using Folium and MarkerClusters. - **Scenario Analysis**: "What if" checks to see how changes in temperature or precipitation impact regional risk. - **Mobile Responsive**: Optimised for both desktop and mobile field use with a sleek, user-friendly interface. ## 🧠 Technology Stack - **Framework**: Streamlit - **Machine Learning**: XGBoost, Scikit-Learn - **Visualization**: Plotly, Folium - **Data Sources**: NASA FIRMS, Google Earth Engine, ERA5 (Copernicus) ## 🛠️ Installation & Setup 1. **Clone the repository**: ```bash git clone github.com cd wildfire_app ``` 2. **Install dependencies**: ```bash pip install -r requirements.txt ``` 3. **Run the application**: ```bash streamlit run app.py ``` ## 🤝 Contact - **Developer**: Lunga Ndzimandze - **Email**: ndzimandzelunga@gmail.com --- *Lunga Ndzimandze © 2026*