Multitemporal Machine Learning Approach for 10-m Pixel-Based Crop Classification in the Fragmented Agricultural Fields of the Nile Delta, Egypt
Annual agricultural censuses in Egypt are often delayed, leaving crop data outdated and less reliable. This study addresses the challenge of fine-scale crop mapping in the fragmented Nile Delta, where accurate classification is vital for water resource management and food security. It uses 10-m multitemporal Sentinel-1...