SAEON/sanbi-ecosystem-risk-atlas

This profiler provides access to ecosystem-level risk assessment based on the 2018 National Biodiversity Assessment (NBA) data from SANBI. It analyses, ecosystem level threat status, habitat transformation risk, and biodiversity vulnerability across South African biomes. # SANBI Ecosystem Risk Profiler A Streamlit web application for ecosystem-level risk assessment based on the **2018 National Biodiversity Assessment (NBA)** data from the South African National Biodiversity Institute (SANBI). It analyses ecosystem threat status, habitat transformation risk, and biodiversity vulnerability across South Africa's 10 biomes. --- ## Features - **Overview Dashboard** — national-level risk summary with threat level metrics (CR/EN/VU/NT/LC) and biome-wide charts - **Biome Explorer** — interactive three-level filtering (Biome → Bioregion → Ecosystem) with trend analysis and comparison against national averages - **Risk Categories** — deep dive into four risk factors: habitat transformation, biodiversity threat status, vegetation vulnerability, and protection gaps --- ## Tech Stack | Layer | Technology | |---|---| | Web framework | Streamlit ≥ 1.28 | | Visualisation | Plotly, Altair, Folium, Matplotlib, Seaborn | | Database | PostgreSQL + PostGIS | | ORM / DB adapter | SQLAlchemy ≥ 2.0, psycopg2 | | Geospatial | GeoPandas ≥ 0.14, Shapely ≥ 2.0 | | Data | pandas ≥ 2.1, NumPy, SciPy | | Config | python-dotenv, Pydantic ≥ 2.0 | | Runtime | Python 3.12, Docker | --- ## Prerequisites - Python 3.12+ - PostgreSQL with PostGIS extension (NBA 2018 data loaded) - Docker & Docker Compose (for containerised setup) --- ## Local Setup (without Docker) ```bash # 1. Clone the repository git clone github.com cd sanbi-ecosystem-risk-atlas # 2. Create and activate a virtual environment python -m venv venv source venv/bin/activate # Windows: venv\Scripts\activate # 3. Install dependencies pip install -r requirements.txt # 4. Configure environment variables cp .env.example .env # Edit .env with your database credentials (see Environment Variables below) # 5. (Optional) Test the database connection python scripts/test_database.py # 6. Run the app streamlit run main.py ``` App will be available …