Estimating LAI and CCD of rice and wheat using hyperspectral remote sensing data

The aim of this study was to measure the changes of the canopy spectral reflectance, LAI and CCD of rice and wheat in different growth period, to analyze the correlation between hyperspectral vegetation indices, LAI and CCD, and to confirm the optimum vegetation indices for estimating LAI and CCD of rice and wheat. The result showed the change trend of LAI was similar with CCD, that is, the values increased at first and then decreased, but the time for maximum value of CCD and that of LAI in rice and wheat appeared at different growth stage; In near infrared region, the canopy spectral reflectance gradually increased at rice and wheat earlier growing stage, and then decreased gradually in late growth stage. The maximum value appeared around heading stage and filling stage, respectively. Comparison with the correlations among 14 vegetation indices, LAI and CCD, the modified soil adjusted vegetation index (MSAVI2) was significantly correlated with LAI and CCD in rice, and the correlation coefficients were more than 0.91. For wheat, the spectral reflectance at 800 nm (R800) was highly correlated with LAI and CCD, the correlation coefficients were higher than 0.92. Linear regression models were built for estimating LAI and CCD of rice and wheat using the MSAVI2 and R800, the determination coefficients were more than 0.85 (R2>0.85). These results provided an insight for monitoring the dynamics of crop and scientific management of agricultural production under different growth environment (irrigation- and rain-fed forming).