Identifying interior sources of dust storms using remote sensing, GIS and geology (case study: Khuzestan province)

Significant damages have been caused by dust storm in Iran, particularly in Khuzestan province. Thus, as a primary step to fight with dust storms, it is necessary to map dust sources. The purpose of this study is to identify dust sources using a combination approach of remote sensing, GIS and sedimentology in Khuzestan province. For this, spatial data of soil, land use, climate, slope (collected from related organizations) and sedimentology were used as constraint layers, and vegetation, land surface temperature (LST) and soil moisture constitute the main layers. Sedimentology map was prepared by field sampling (900 samples) and remote sensing techniques. Also the main layers were extracted by performing the necessary computational processes on Landsat 8 satellite images. The constraint layers were applied to remove the areas without any potential of dust source. In next step, main layers weighting was done using pairwise comparison and Fuzzy Analytic Hierarchy Process (FAHP) methods. For preparing map of dust sources, each major layer was multiplied by corresponding weight and were then integrated to present a dust source zonation map. To validate the results, a field work was carried out in 180 points of source areas that verifies high accuracy of the prepared map. Results showed that 9 percent of Khuzestan plain, equivalent to 349254 hectares, are dust-generating sources. Based on land use type and area, the identified zones include destroyed range, rainfed agriculture lands, bare lands, wetlands, dried ponds and irrigated agriculture lands, respectively.