Estimation of Cotton Canopy Crop Water Stress Index (CWSI) Based on Hyperspectral Remote Sensing Infrared Images
基于红外热图像的棉花水分胁迫指数高光谱遥感估算研究

Thermal images and reflectance spectra of cotton canopy were acquired by using a radiometric video camera from Fluke company and a portable non-imaging hyperspectral spectrometer from ASD company in five growth stages of cotton respectively. The thermal images were processed and the crop water stress index (CWSI) was calculated according to Jones' definition. Through spectrum analysis, both the reflectance spectrum at the wavelength of 654 nm and the first derivative spectrum at the wavelength of 738 nm were considered as the sensitive wavebands of the CWSI. The linear correlation model equations were established. The regression function accuracy values were 72.4% and 80.5% respectively. The research result showed that by using infrared thermal imaging technology to acquire high spatial resolution information of crop canopy, the effects of background interference factors could be eliminated and the CWSI of cotton canopy could be calculated more accurately. Compared with the reflectance spectra, the first derivative spectra was more suitable for the real-time and dynamic calculation of the CWSI of cotton.