Mapping soil salinity using a combined spectral response index for bare soil and vegetation: A case study in the former lake Texcoco, Mexico

Abstract Mapping soil salinity is difficult due to its large spatial and temporal variability. Remote sensing is widely used to lower survey costs, but existing studies usually analyze bare soils and make little reference to the halophytic plants and their role as salinity indicators. This paper aims to correlate soil characteristics (electric conductivity in saturation extract (EC e ) and sodium absorption ratio (SAR) with the spectral response of plant species and bare soils, integrating an algorithm to allow multi-scale mapping using remote sensors. Ground radiance was measured on different plant species and bare soils. A Combined Spectral Response Index (COSRI) was calculated for bare soils and vegetation by adjusting the normalized difference vegetation index (NDVI). EC e and SAR were determined in surface soil samples. Correlation coefficients between COSRI and soil salinity were obtained and a model was adjusted to predict soil salinity. Landsat-ETM and airborne digital images were used to calculate raster maps of COSRI, and EC e and SAR were estimated using adjusted models. Correlation between COSRI and EC e and SAR was of −0.885 and −0.857, respectively. Variance accounted for by exponential models for EC e and SAR was of 82.6% and 75.1%, respectively. It may be concluded that the method is an easy, low-cost procedure to map salt-affected areas.