Evaluation of a WorldView-2 image for soil salinity monitoring in a moderately affected irrigated area

Abstract

Conventional methods for monitoring salt accumulation within irrigation schemes involve regular field visits to collect soil samples for laboratory analysis. Remote sensing has been proposed as a less time-consuming, more cost-effective alternative as it provides imagery covering large areas throughout the year. This study evaluated the efficacy of very high resolution (VHR) WorldView-2 imagery to map areas affected by salt accumulation. Classifications based on thresholds obtained from Jeffries–Matusita distance, regression modeling, classification and regression trees, as well as supervised classification approaches, were evaluated for discriminating between salt-affected and unaffected soils in Vaalharts, South Africa. The WorldView-2 bands were supplemented with salinity indices (SIs), principal components, and texture measures to increase the number of predictive variables. In situ soil samples were used for model development, classifier training, and accuracy assessment. The results showed that a simple threshold implemented on a normalized difference SI was the most successful in separating classes, with an overall accuracy of 80%. The findings suggest that VHR satellite imagery holds much potential for monitoring salt accumulation, but more research is needed to investigate why the classification results tend to overestimate salt-affected areas. More work is also needed to evaluate the transferability of the techniques to other irrigation schemes.