Introducing a novel dust source identification method based on edge points and paths extracted from integration of time-series MODIS products

Abstract

In this paper, a novel method for identifying dust sources in the Middle East using multi-temporal MODIS images was introduced. This method was utilized to identify the sources of 14 Sand and Dust Storms (SDSs) events that occurred between 2008 and 2012 in Ahwaz city, in southwestern Iran. For this purpose, the SDS extents were detected using the proposed Thermal Infrared (TIR) algorithm consisting of MODIS TIR bands 20, 31, and 32, and the Brightness Temperatures Difference between the two bands 31 and 32. The true color RGB MODIS image of the study area showed that the proposed SDS detection algorithm was highly efficient in separating these storms. In the next step, potential dust sources were obtained based on the proposed algorithm, which included the main sub-steps of separating the major SDS extents and calculating the centroids and the edges of each, computing the angles between each point of the obtained edges with the centroid of the corresponding SDS extent, and applying two thresholds to separate potential sources. The dust source map was produced by overlaying all dilated potential dust sources and classifying them based on the number of overlapped layers. This map illustrated that dust sources were scattered in eastern Syria, northwestern and southeastern Iraq, and southwestern Iran. Interpretation of the results demonstrated that the degradation of vegetation covers and reducing the width of rivers and dry lake-beds were the main characteristics of these sources. From the results of this research, it was concluded that the proposed novel method is a promising and efficient algorithm for identifying dust sources.