Radiative transfer models (RTMs) for field phenotyping inversion of rice based on UAV hyperspectral remote sensing

The nondestructive and rapid acquisition of rice field phenotyping information is very important for the precision management of the rice growth process. In this research, the phenotyping information LAI (leaf area index), leaf chlorophyll content (Cab), canopy water content (Cw), and dry matter content (Cdm) of rice was inversed based on the hyperspectral remote sensing technology of an unmanned aerial vehicle (UAV). The improved Sobol global sensitivity analysis (GSA) method was used to analyze the input parameters of the PROSAIL model in the spectral band range of 400-1100 nm, which was obtained by hyperspectral remote sensing by the UAV. The results show that Cab mainly affects the spectrum on 400-780 nm band, Cdm on 760-1000 nm band, Cw on 900-1100 nm band, and LAI on the entire band. The hyperspectral data of the 400-1100 nm band of the rice canopy were acquired by using the M600 UAV remote sensing platform, and the radiance calibration was converted to the canopy emission rate. In combination with the PROSAIL model, the particle swarm optimization algorithm was used to retrieve rice phenotyping information by constructing the cost function. The results showed the following: (1) an accuracy of R2=0.833 and RMSE=0.0969, where RMSE denotes root-mean-square error, was obtained for Cab retrieval; R2=0.816 and RMSE=0.1012 for LAI inversion; R2=0.793 and RMSE=0.1084 for Cdm; and R2=0.665 and RMSE=0.1325 for Cw. The Cw inversion accuracy was not particularly high. (2) The same band will be affected by multiple parameters at the same time. (3) This study adopted the rice phenotyping information inversion method to expand the rice hyperspectral information acquisition field of a UAV based on the phenotypic information retrieval accuracy using a high level of field spectral radiometric accuracy. The inversion method featured a good mechanism, high universality, and easy implementation, which can provide a reference for nondestructive and rapid inversion of rice biochemical parameters using UAV hyperspectral remote sensing.