Estimating soil salinity in different landscapes of the Yellow River Delta through Landsat OLI/TIRS and ETM+ Data

Abstract

Soil salinization has increasingly become a serious issue in coastal zone due to global climate changes and human disturbances. Assessment of soil salinity, especially at the landscape scale, is critical to coastal management and restoration. Two data from OLI/TIRS and ETM+ sensors of Landsat satellite were used to compare their ability to invert the spatial pattern of soil salinity in both farmland and salt marsh landscapes in the Yellow River Delta, China, respectively. The results showed that the in situ electrical conductivity (EC a ) of soil, representing soil salinity, were closely related with spectral parameters and salinity indices calculated by the remote sensing data. The results of multiple regression models have showed that nearly all the spectral parameters and salinity indices calculated by OLI/TRIS data were more sensitive to soil salinity than those by ETM+ data. Therefore, the models based on OLI/TIRS data are superior to those on ETM+ data in estimating the spatial pattern of soil salinity in farmland and salt marsh landscapes. Our results were very helpful to evaluate the levels of soil salinization in the Yellow River Delta.