Abstract:Hyper-spectral remote sensing has been successfully applied to quickly and efficiently monitoring field of soil salinization. In order to further promote the multi-source remote sensing technology development in agricultural production and management, Jiefangzha zone of Hetao Irrigation District, Inner Mongolia, was selected as the study area, based on the measured ground spectra, surface roughness and four polarization scattering data of C-band microwave synthetic aperture radar (radar SAR), respectively by using the method of principal component regress (PCR), multiple stepwise regress (MSR) and partial least square regress (PLSR) to select feature band, soil salinization distribution modeling was built and evaluated. First of all, through correlation analysis of the spectral reflectance and its logarithm, the first and second order derivative of these four kinds of spectral data, it was found that the first spectrum and second derivative had better correlation compared with the original spectrum and logarithmic transformation, correlation coefficient of the second derivative transformation of 618~622nm, 1802~1806nm, 2169~2173nm and 2344~2348nm characteristic band was 0.37, 0.28, 0.39 and 0.27, respectively;characteristic band selected value of PLSR was later than that of the MSR. However, the second-order derivative transformation model was inferior to the MSR. Second, in contrast to the soil salt simulation method of PCR, MSR and PLSR based on the second order inverse transform, the BP artificial neural network (BPANN) model was the best prediction model, which collaborated the characteristics spectrum band center reflectivity after the second derivative and radar scattering characteristics, surface roughness. And the R2 value of prediction model was 0.8908, and the stability and accuracy was better than those of the empirical regression model. The neural network model integrating multisource remote sensing data can monitor soil salinization distribution more accurately, providing basic information guidance for soil salinization monitoring and soil degradation prevention in irrigation area.
