Get the latest AI Crop Mapping news, research and developments covering the use of artificial intelligence, satellite imagery and geospatial technologies to identify, classify and map crops and agricultural fields. This tag brings together developments in machine learning, deep learning, computer vision and Earth observation for large-scale agricultural monitoring.
Coverage includes crop classification, field-boundary mapping, satellite image analysis, multispectral and SAR data, foundation models, machine learning and AI-powered agricultural monitoring. In India, ISRO has developed the AI-based SASYA tool for crop mapping using C-band SAR data from EOS-04, while government programmes are integrating satellites, AI, remote sensing and GIS for crop monitoring and production forecasting.
Find news on crop acreage estimation, yield forecasting, crop insurance, precision agriculture, smallholder mapping and agricultural decision-support systems. Recent research is using Sentinel-1 and Sentinel-2 imagery with deep-learning and transformer models, while foundation models are being tested for mapping fragmented smallholder fields that are difficult to distinguish using conventional satellite methods. These technologies could support more timely crop assessments and improve the targeting of agricultural programmes.
30 September 2026, Cambridge: A satellite-based artificial intelligence tool developed at the University of Cambridge has correctly identified crop types across Senegal’s
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