This project leverages geospatial data to analyze population growth patterns across Uganda, Rwanda, Burundi, and Tanzania. By classifying demographic shifts into Decline, Neutral, Growth, and High Growth categories, this analysis aids in identifying urbanization hotspots and resource allocation needs.
Based on the spatial analysis output (Map 2):
- High-Density Growth: Intense population pressure ("High Growth") is concentrated in the Lake Victoria basin, particularly impacting Rwanda, Burundi, and Southern Uganda.
- Urbanization Corridors: Tanzania exhibits a more dispersed growth pattern, with distinct clusters likely correlating with major urban centers and transit corridors.
- Population Decline: Specific pockets of population decline (Green) were identified, potentially indicating migration out of protected areas or rural-to-urban shifts in the Southern Highlands of Tanzania.
- Tools: Python (Geopandas, Rasterio, Matplotlib), QGIS (for final cartography).
- Data Source: WorldPop / National Census Projections.
- Methodology:
- Raster calculation to determine pixel-wise population change.
- Reclassification of growth rates into categorical tiers.
- Cartographic layout with scale bar (EPSG:xxxx) and North orientation.
- Clone the repository:
git clone https://github.com/Oystr97/East-African-demographic-shifts-in-population-size-distribution-and-growth-patterns.git
- Install dependencies:
pip install -r requirements.txt
- Run the Jupyter Notebook:
jupyter notebook notebooks/analysis.ipynb
The datasets used in this project were downloaded from the following sources:
- ICPAC Geoportal (African Administrative Boundaries)
- WorldPop (Global Demographic Data)
- Nature Scientific Data (Urban form and functions data)
- United Nations Population Division (World Population Prospects 2022)
- The World Bank Open Knowledge Repository (Africa's Cities)