Zotahina-Rakotomahefa/madagascar-flood-risk-exposure-mapping

Python-based geospatial analysis of 100-year flood hazard and exposed population in Madagascar using Rasterio and GeoPandas. # Climate Risk Mapping: Flood Exposure Assessment in Madagascar This project assesses **population exposure to 100-year return period flood hazards (RP100)** in Madagascar using geospatial analysis. It integrates flood hazard rasters, population density data, and administrative boundaries to produce quantitative indicators and high-quality maps supporting climate risk and disaster impact studies. --- ## Overview Flooding is one of the most critical climate-related hazards affecting Madagascar. Understanding where people are exposed is essential for disaster risk reduction, climate adaptation planning, and policy decision-making. This project implements a reproducible Python-based GIS workflow to: - Align heterogeneous raster datasets - Quantify exposed population - Visualize flood risk spatially at national scale The workflow is optimized for scientific transparency, modularity, and scalability. --- ## Objectives - Clip flood hazard and population rasters to Madagascar boundaries - Harmonize spatial resolution, CRS, and extent - Estimate the total population exposed to RP100 flood events - Produce a publication-ready flood exposure map - Provide a modular and reusable Python workflow --- ## Project structure ``` project/ ├── data/ ├── boundaries/ # Administrative boundaries ├── flood/ # Flood hazard raster └── population/ # Population raster ├── outputs/ madagascar_flood_map.png ├── notebooks/ ├── run_flood_exposure.ipynb ├── src/ ├── import_config.py # Paths, CRS, constants ├── input_data.py # Data loading ├── spatial_clipping.py # Clip rasters to Madagascar ├── flood_hazard_analysis.py # Flood mask & statistics ├── population_resampling_to_flood_grid.py ├── exposed_population.py # Exposure calculation ├── downscaling.py # Resolution harmonization ├── population_classification.py # Populatio …