Combination of spectral indices of OLI and TIRS sensor and magnetic induction data in order to estimate the spatial variation of soil salinity

Soil salinity and alkalinity are among the most important soil degradation processes, especially in arid and semi-arid regions. The purpose of this study is to evaluate spectral indicators as well as use the data of the EM38 for identifying saline soils and spatial changes. The study area is Ghahavand plain that is located in Hamedan Province. In this study, Landsat 8 satellite data were used. Soil sampling of 37 points was performed and 86 points were read using an electromagnetic induction device. Using protomorphic units based on visual interpretation of OLI 543 false-color composite image and field observations, a total of 9 homogeneous units were identified in the region using these units as training regions for supervised classification. The results showed that the detection of soil salinity in the visible spectrum (blue, green, and red band) is feasible. The bands 5, 6, and 7 can be useful in differentiating salty white crust lands from salty gray crust lands. In the reflective bands, the white and smooth crust exhibits the highest reflectance. The results of classification accuracy showed that the highest total accuracy was 90.0 and the kappa coefficient was 80.45 when bands 1, 2, 3, 4, 5, 6, 7, 10, and 11 were used and shallow and abandoned plowed lands had the least accuracy. Also, the final model of salinity estimation showed that SI6 and SI11 indicators and electromagnetic induction vertical measurements (EMv) are the most suitable variables for estimating salinity spatial changes.