LAUSR

Soil salinization leads to dehydration of plants, which seriously threatens ecologically sustainable development and food security guarantee. In the complex and diverse coastal wetland environment, the impervious surface and bare soil have similar spectral features with salinized soil, which make it difficult for traditional satellite data and algorithms to accurately and timely monitor the small surface features of salinization. This article presents a baseline-based soil salinity index (BSSI) for soil salinization monitoring using medium-resolution data. In BSSI, we construct a virtual salinization baseline by connecting the near-infrared (NIR) band and the short-wave infrared-2 (SWIR2) band to enhance the spectral feature of salinized soils which border on the impervious surface. In addition, we calculate the distance between the short-wave infrared-1 (SWIR1) band and the virtual salinization baseline as the BSSI, which can effectively improve the stability of salinity inversion for different soils. Through data comparison and model simulations, BSSI has shown advantages over a series of the traditional salinization spectral indices (SSIs). The results show that the saline soil extraction accuracy of BSSI exceeds 85% and the correlation coefficient of the BSSI and the degree of soil salinization exceeds 0.90. Since the related spectral bands, such as NIR, SWIR1, and SWIR2, are available on many existing satellite sensors such as Landsat TM/ETM+, OLI, and sentinel 2, the BSSI concept can be extended to establish long-term records for soil salinization monitoring.