Developing global dataset of salt pans and salt playas using Landsat-8 imagery: a case study of western North America

Abstract

Monitoring salt pans is important especially for agricultural management in arid or semi-arid regions because salt pans can negatively affect human life, wildlife, and ecology. Some of the harmful impacts of salt pans are accelerated desertification, cropland loss, economic downturn, wildlife loss, and forced migration of humans and animals due to salt storms. Spectral salt pan indices based upon remotely sensed data (using spectral properties of Landsat-8 imagery) suggested in previous studies vary by location. In other words, the spectral configuration of a salt index for a given location may not be readily applicable to another location due to spatial heterogeneity of salt components across the continental surface. Using Landsat-8 OLI imagery and climate data sets, this study aims to develop a mapping framework which can effectively extract salt pans and salt playas under various spectral conditions in different geographic locations. Based on training samples selected in eight major salt pans/playas in North America, Central Asia, Africa, and Australia, the mapping framework was designed to include the following steps: i) a conservative salt index to highlight potential salt-covered regions, ii) a calibrated support vector machine (SVM) to extract high-salinity areas in the mask regions, and iii) a posterior quality assurance/ quality control (QA/QC) with assistance of auxiliary datasets (e.g., surface slope and land covers) to eliminate commission errors and refine the extracted saltpan areas. The developed mapping framework was validated in the arid endorheic regions across the western United States, with a total area of 699 thousand square kilometers. Both qualitative and quantitative assessments of the results show reliability of the developed framework. The overall accuracy of the extracted salt pans prior to QA/QC is 97%. The final product after QA/QC achieves an overall accuracy of 99.95% and a Kappa statistic of 0.99.According to the results of salt pans areas and endorheic basins areas, it can be concluded that two aforementioned variables of this study are positively correlated to each other, and 1.10 percent of the entire case study area is covered by salt pans. The accuracy of the results suggests a potential that the mapping framework, together with the collected training sample and algorithms, may be applicable to identify salt pan and salt playa regions across the Earth’s land surface.