AugustKizito/tanzania-bri-poverty-analysis

This project analyzes poverty resilience along Tanzania's BRI corridors using open-source geospatial data. It includes GEE scripts for data pre-processing, Python scripts for spatial modeling and visualization, and a synthetic dataset for reproducibility. The focus is on infrastructure-climate interaction tanzania-bri-poverty-analysis This repository provides scripts, processed datasets, and documentation used to reproduce the spatial econometric analysis conducted in a study examining climate variability, infrastructure access, and regional poverty dynamics in Tanzania. Repository Contents Code Python scripts used for spatial econometric modeling including: • Spatial Autoregressive Model (SAR) • Geographically Weighted Regression (GWR) • Spatial Durbin Model (SDM) Data Processed datasets used for regression analysis including: • poverty indicators • infrastructure variables • climatic indicators • spatial weights matrices Satellite Processing Scripts Google Earth Engine scripts used for: • Sentinel-2 preprocessing • NDVI computation • land cover classification • land cover change detection Supplementary Materials Additional methodological documentation and supporting tables. Note Raw household survey data cannot be shared due to confidentiality agreements. Aggregated datasets and scripts necessary for reproducing the analysis are provided. License MIT License