Estimation of Soil Salt and Ion Contents Based on Hyperspectral Remote Sensing Data: A Case Study of Baidunzi Basin, China

Soil salinity due to irrigation diversion affects regional agriculture, and the development of soil composition estimation models for dynamic monitoring is important control. In this study, we evaluated performance hyperspectral data measured using an analytical spectral device (ASD) field spec standard-res hand-held spectrometer satellite sensor visible shortwave infrared advanced imager (AHSI) in estimating salt content (SSC). First derivative analysis (FDA) principal component (PCA) were applied raw spectra (RS) select best model input data. We tested ability these three groups as partial least squares regression (PLSR), (PCR), multiple linear (MLR). Finally, SSC, Na+, Cl−, SO42− contents was established modeling method, a spatial distribution map drawn. The results show that obtained from laboratory consistent when SSC low, increased, curves ASD showed little change curve characteristics, while AHSI more pronounced features, manifested images darker pixels with lower brighter higher SSC. demonstrated strong response SSC; therefore, had greater advantage compared content. process, RS performed Na+ content, R2 reaching 0.79 0.58, respectively, obtaining low root mean squared error (RMSE) values. FDA PCA Cl− SO42−, MLR outperformed PLSR PCR components region. addition, camera used study very cost-effective can potentially be evaluation salinization wide range high accuracy, thus reducing errors associated collection individual samples instruments.