Ground Reference Dataset for Crop Type Mapping & Monitoring in Four Districts of Rwanda

Training and validation of crop classification models; AI-driven remote sensing; Agricultural monitoring; Yield and land use change analysis; Food security applications Notes / challenges: Spatial sampling biases due to accessibility constraints; Requires geo-processing expertise; Limited to four districts (not nationwide); Integration with inter-annual satellite time series is non-trivial