Phenology-Based Remote Sensing Assessment of Crop Water Productivity

The assessment of crop water productivity (CWP) is practical significance for improving regional agricultural use efficiency and conservation levels. remote sensing method a common estimating large scale CWP, the errors in CWP by originate mainly from inversion yield evapotranspiration (ET). phenological period important factor ET estimation. coefficient (Kc) harvest index (HI), which are closely related to different periods, considered during processes detected enhanced vegetation (EVI) curves using Moderate Resolution Imaging Spectroradiometer (MODIS) data Sentinel-2 data. estimated surface–energy balance algorithm land (SEBAL) model Penman?Monteith (P-M) equation, dry matter mass–harvest method. calculated as ratio growing season. results show that daily images consistent with measured values. It found variation peaks appear at heading wheat maize, good agreement rainfall growth characteristics crop. relationship between shows negative parabolic correlation, linear correlation. average CWPs maize 1.60 kg/m3 1.39 kg/m3, respectively. indicate phenology-based has effect on Lixin County.