An Efficient Approach for Inverting the Soil Salinity in Keriya Oasis, Northwestern China, Based on the Optical-Radar Feature-Space Model

Soil salinity has been a major factor affecting agricultural production in the Keriya Oasis. It has a destructive effect on soil fertility and could destroy the soil structure of local land. Therefore, the timely monitoring of salt-affected areas is crucial to prevent land degradation and sustainable soil management. In this study, a typical salinized area in the Keriya Oasis was selected as a study area. Using Landsat 8 OLI optical data and ALOS PALSAR-2 SAR data, the optical remote sensing indexes NDVI, SAVI, NDSI, SI, were combined with the optimal radar polarized target decomposition feature component (VanZyl_vol_g) on the basis of feature space theory in order to construct an optical-radar two-dimensional feature space. The optical-radar salinity detection index (ORSDI) model was constructed to inverse the distribution of soil salinity in Keriya Oasis. The prediction ability of the ORSDI model was validated by a test on 40 measured salinity values. The test results show that the ORSDI model is highly correlated with soil surface salinity. The index ORSDI3 (R2 = 0.656) shows the highest correlation, and it is followed by indexes ORSDI1 (R2 = 0.642), ORSDI4 (R2 = 0.628), and ORSDI2 (R2 = 0.631). The results demonstrated the potential of the ORSDI model in the inversion of soil salinization in arid and semi-arid areas.