inshepherd/Gasabo-LCLU

Twenty-Four Years of Land Cover Land Use Change in Gasabo, Rwanda, and Projection for 2032 # Gasabo District Population Analysis (2000–2032) Python code for population trend analysis, visualization, and statistical modeling for Gasabo District, Rwanda. ## Overview This repository contains Jupyter Notebook code to analyze and visualize population dynamics in Gasabo District from 2000 to 2032. The code processes observed census data (2000–2024) and official projections (2025–2032) from the National Institute of Statistics of Rwanda (NISR). ## Data Source - Population data: National Institute of Statistics of Rwanda (NISR) - 2002, 2012, 2022: National Population and Housing Censuses - 2000–2001: Back-calculated using exponential growth model - 2003–2021: Interpolated estimates - 2023–2024: Official estimates - 2025–2032: NISR population projections ## Study Justification The 2000–2024 study period is selected to: 1. Capture long-term population growth aligned with land use/land cover change analysis 2. Correspond with Rwanda’s administrative boundary stabilization (2006 territorial reform) 3. Ensure consistency with satellite imagery availability for geospatial analysis 4. Support integration with urban expansion and land use change modeling ## Features - Data preparation for observed and projected population (2000–2032) - Linear trend fitting and statistical analysis (slope, R², annual growth rate) - High-quality publication-ready plot (300 DPI) - Annotation of national census years (2002, 2012, 2022) - Clear visual distinction between observed and projected data ## Libraries Used - pandas - matplotlib - numpy - scipy ## Output - High-resolution plot: `Gasabo_Population_2000_2032.png` - Key statistics: total growth, annual growth rate, trend fitness ## Citation If you use this code, please cite: National Institute of Statistics of Rwanda (NISR). (2023). Fifth Rwanda Population and Housing Census. ## Author Research on Land Use Change and Population Dynamics – Gasabo District, Rwanda