Application of Remote Sensing in Crop Condition Monitoring for Agricultural Planning in Kano State

This study examines the application of satellite remote sensing for crop condition monitoring and its integration into agricultural planning processes in Kano State, North West Nigeria. Remote sensing offers cost-effective, spatially comprehensive crop monitoring capabilities that can inform production forecasting, food security early warning, and input supply chain planning. Kano State, with its large and economically important farming sector, would benefit significantly from improved crop monitoring systems. This study uses Sentinel-2 satellite imagery combined with field validation surveys to develop and test a crop condition monitoring protocol for the 2022 and 2023 growing seasons in Kano State. Normalised difference vegetation index, enhanced vegetation index, and leaf area index are derived from satellite data and validated against ground-measured vegetation parameters from 120 plot-level field visits. Seasonal crop condition maps are developed and compared against end-of-season yield estimates from the Kano ADP survey. Remote sensing-derived condition indicators are assessed for their agreement with ground-observed crop status. Findings reveal strong agreement between remote sensing NDVI trajectories and ground-measured biomass accumulation, with correlation coefficients above 0.82 for maize, sorghum, and groundnut. Mid-season NDVI at maximum canopy cover explains 74 percent of end-of-season yield variation. Late-season drought stress events are clearly detectable from NDVI decline curves. The study concludes that remote sensing-based crop monitoring is a practical and accurate tool for Kano State agricultural planning. It recommends integration into the state ADP monitoring and evaluation system.

Keywords: remote sensing, crop monitoring, NDVI, Kano State, agricultural planning.