[Objective]The present study was to calculate crop water stress index (CWSI) based on the thermal images,and estimation of CWSI by using hyperspectral vegetation index,which intends to provide the scientific evidence to monitor cotton canopy water status by combining infrared thermography and hyperspectral techniques in the fields.[Method] With Fluke infrared thermal camera and ASD portable non-imaging hyperspectral spectrometer,canopy infrared thermal images and hyperspectral reflectance data were obtained,respectively,at five key growth stages of cotton in an open experimental field including 2 cotton cultivars with 4 level water treatments.Thermal image was processed and the crop water stress index CWSI was calculated according to Jones'formula.Regression analysis was carried out of the four vegetation indices derived from hyperspectral reflectance data.[Result] It was significant for the four linear regression function models at 1％ level,among the four vegetation indices,RENDVI (Red Normalize Vegetation Index) had the highest negative linear correlation with CWSI,according to their model function,estimation of CWSI,correlation between measured CWSI and the estimated CWSI was significant (r =0.839 9 * *,n =30,α =1％).[Conclusipy.Combination of infrared thermography and hyperspectral remote sensing technology can precisely estimate CWSI of cotton,which is helpful to have a better diagnosis of water status of cotton canopy.
cotton canopyinfrared thermographyCWSIhyperspectral vegetative index
国家科技期刊平台
NSTL
万方数据
维普
