abankwahb1/EcoDrainMap

Flood-risk mapping and prediction platform for Accra, combining OpenStreetMap, SRTM elevation data, and Sentinel-2 satellite imagery to help municipal teams identify high-risk areas before flooding happens. # GH EcoDrain-MAP: Strategic NADMO Decision Support System ## Overview GH EcoDrain-MAP is an intelligent flood risk assessment and decision support system developed for the National Disaster Management Organisation (NADMO) in Ghana. The system combines hydrological modelling, terrain analysis, machine learning, and geospatial data to identify areas vulnerable to flash flooding across Accra. The application provides an interactive interface for simulating rainfall events, evaluating flood susceptibility, and supporting emergency planning using both rule-based and machine learning approaches. ## Features - Interactive flood risk simulation - Machine Learning flood susceptibility prediction (Random Forest) - Real elevation and slope data (SRTM) - OpenStreetMap drainage network integration - Google Earth Engine integration for Sentinel-2 impervious surface analysis - Interactive Folium map visualization - Flood hotspot identification - Critical infrastructure risk assessment - Decision support dashboard for disaster management --- ## Technologies Used - Python - Streamlit - Scikit-learn - Pandas - NumPy - Folium - Streamlit-Folium - Google Earth Engine - OpenStreetMap (Overpass API) - OpenTopoData API ## Installation Clone the repository ```bash git clone github.com cd ecodrainmap ``` Install the required packages ```bash pip install -r requirements.txt ``` Run the application ```bash streamlit run app.py ``` --- ## Google Earth Engine Configuration To use real Sentinel-2 impervious surface data: 1. Create a Google Cloud Project. 2. Enable the Earth Engine API. 3. Create a Service Account. 4. Download the Service Account JSON key. 5. Configure Streamlit Secrets. Example: ```toml gee_project = "your-project-id" gee_service_account_path = "C:/path/to/service-account.json" ``` --- ## Project Structure ``` EcoDrainMap/ │ ├── app.py ├── ml_model.py ├── requirements.txt ├── README.md ├── .streamlit/ │ └── secrets …