Modeling and Mapping of Salt-Affected Soils through Spectral Indices in Inland Plains of Semi-arid Agro-Ecological Region

Abstract

Mapping the salt affected soils through spectral indices derived from satellite imageries is essential for its monitoring, prevention and mitigation. Many research attempts have been demonstrated the application of spectral indices for predicting soil salinity in arid environment. Present study attempted to identify and map the salt-affected soils (SAS) in inland plains of semi-arid agro-ecological region using satellite image by means of spectral indices through GIS techniques. The satellite imagery of Resourcesat-1(IRS-P6) LISS IV was visually interpreted for mapping SAS and samples were collected for laboratory characterization. An integrated approach of spectral bands and indices along with analytical data was used to develop multiple regression equation for prediction. Correlation analysis was applied to find the best regression model to predict the salt-affected soils. The salt-affected soils predicted by multiple regression equations were 0.150, 0.101 and 0.046 for pH, EC and ESP, respectively due to weak variation in soil properties, sample density, vegetation cover by better management practices.