Phenology-driven multisensor unsupervised crop mapping in data-scarce irrigated agriculture: a case of Adea District in Ethiopia
Accurate irrigation planning, water allocation, and agricultural productivity assessment are frequently constrained in data-scare regions where reliable ground-based crop information and spatial coverage data are limited. This study addresses these gaps using a phenology-driven, multisensor unsupervised crop-mapping...