Generating soil electrical conductivity maps at regional level by integrating measurements on the ground and remote sensing data

In arid and semi-arid areas, salinization of soil and water resources is one of the major threats to irrigated agriculture. For management purposes, quantifying both the extent and distribution of salinization is important, but accurate data with sufficient spatial resolution are often not available. Commonly used techniques such as soil sampling and geophysical methods are time-consuming and yield only point data. A method is described in which multispectral remote sensing images can be used to regionalize point data measured on the field. Field data consist of measurements of electrical conductivity and are obtained by the combination of geophysical methods and the analysis of field soil samples. Uncalibrated salinity maps were calculated with spectral correlation mapping using image-based reference spectra of saline areas. As an alternative indicator for soil salinity, the NDVI was used. The method was verified in the Yanqi Basin, northwestern China. Correlations between field data and the uncalibrated salinity maps were found over non-irrigated sites for all images. Good correlations (R-2 up to 0.85) resulted for images collected during the winter months. The high correlation coefficients allow the uncalibrated salinity maps to be scaled to electrical conductivity maps.