Inversion of soil salinity according to different salinization grades using multi-source remote sensing
Danyang Wang, Hongyan Chen, Wang ZhuoRan, Ma Ying
Abstract
Soil salt information from unified soil salinity content (SSC) inversion models based on all samples is insufficient for accurate regional SSC monitoring. Here, a method of building SSC inversion models for different salinization grades is proposed, combined with unmanned aerial vehicle (UAV) and Sentinel-2A images. According to different salinization grades, three groups of samples (mild (M), medium-severe (S), and whole (W)) were obtained. Their SSC spectra characteristics, parameters, and quantitative inversion models were analysed, constructed, and compared, based on UAV images, and substituted into different salinization grade areas in Sentinel-2A. The UAV-based models for M and S outperformed those for W; the same trend occurred after substituted into Sentinel-2A images. The inversion results were closer to the field survey results. Models for different salinization grades achieved better regional inversion than those of the whole. UAV-based SSC models can be applied to satellite imagery to invert regional SSC.