Water deficit diagnosis and growing condition monitoring of winter wheat based on NDVI-Ts feature space

Information of 4 bands of NOAA meteorological satellite was utilized synthetically to confirm whether the NDVI-Ts feature space can be used to diagnose water deficit and monitor the crop growth. Based on the data foundation of NOAA17/AVHRR, NDVI was calculated using its 1 and 2 channel data, and Ts was inversed using UL92 split-window algorithm optimized by its 4 and 5 channel data. Took Handan area for case, water supply vegetation index (NDVI/Ts) was calculated, and NDVI-Ts two-dimensional feature space was used to analyze the growing situation of winter wheat. The results show that NDVI/Ts can be used to diagnose water deficit of winter wheat during key growth stages in Handan area. NDVI-Ts feature space indicates a linear and inverse relation between NDVI and Ts for winter wheat land，no relativity for bare land, which can prove that NDVI-Ts feature space is a practical theoretical method to diagnosis water deficit and monitor crop growth.