Project Overview

This project uses Python‑based GIS automation to calculate district‑level population density for Côte d'Ivoire using WorldPop raster data and GADM administrative boundaries. The final output is a ready‑to‑map GeoPackage containing boundary geometries enriched with zonal population statistics.

Data Sources

WorldPop Population Raster for Côte d'Ivoire

GADM Administrative Boundaries (country and district level)

Objective

To compute population totals and density values for each district using zonal statistics, and to export the results as a GeoPackage suitable for visualization in QGIS or other GIS platforms.

Workflow Summary

Environment Setup

Installed required Python libraries: geopandas, rasterio, rasterio.mask, and numpy.

Data Import

Loaded the GADM boundary files and the WorldPop raster into a Visual Studio Code notebook.

Raster Preparation

Reprojected and clipped the WorldPop raster to the Côte d'Ivoire boundary extent.

Zonal Statistics

Reprojected district boundaries to match the raster CRS.

Iterated through each polygon to extract population values.

Calculated summary statistics for each district.

Joined the statistics back to the boundary GeoDataFrame using pandas (similar to a table join in QGIS).

Export

Saved the enriched boundary layer as a GeoPackage in the project directory.