Comparison of soil salinity indices based on satellite imagery analysis in Syrdarya province, Uzbekistan

Abstract

Soil salinity is one of the widespread environmental threats worldwide, especially in arid and semi-arid areas. Saline soils mainly occur due to inadequate irrigation and extensive agricultural activities, which account for many soil degradation processes. Advanced technologies such as remote sensing (RS) data have become an economically efficient tool for assessing, detecting, mapping, and monitoring saline areas along with their spatial and temporal variations. This study aims to develop a spatial database to evaluate salinization using RS and GIS (geographical information system). This research employed seven soil salinity indices (SI2, SI3, SI4, NSI, VSSI, NDSI, and NDVI) calculated from Landsat 8 Operational Land Imager (OLI) images. Classification of salinity class was conducted using a supervised algorithm built-in ArcGIS with the government soil salinity map as the training data. The indices utilizing the combination of visible and near-infrared reflectance (NIR) bands produce higher accuracy than those using only visible ones. Among all of the used indices, VSSI showed the highest accuracy.