Estimation of crop water stress index and leaf area index based on remote sensing data

Abstract Estimation of crop water stress index (CWSI) and leaf area (LAI) over large-irrigation schemes requires the use cutting-edge technologies. Combinations remote sensing techniques with ground-truth data have become available for at catchment level. These approaches allow us to estimate actual evapotranspiration capability monitoring status saving irrigation in water-scarce regions. This study was conducted eastern Mediterranean Region Turkiye. Fully distributed CWSI maps were generated we assessed relationship between LAI some specific crops winter season 2021. Landsat 7 8 used meteorological acquired from two stations area. ‘Mapping Evapotranspiration high Resolution Internalized Calibration’ methodology applied energy balance components. displayed spatiotemporal changes tandem crop-type variations. Consequently, results presented a correlation (r = 0.95 r 0.99 wheat lettuce, respectively) LAI, moderate 0.44) potatoes season. Thus, by utilizing remotely sensed data, values would be directly estimated without requiring any situ measurements canopy air temperature over-irrigation scheme.