We identified over 60 dust sources in the study area using MODIS satellite images during the 2005–2016 period. We found that slope, geomorphology, and land use had a major influence in generating dust sources in this region. The results revealed that the developed method has the ability to predict dust source occurrences in the arid-semiarid area of the Middle East. This research's findings could assist decision-makers and land managers in properly managing the lands susceptible to dust generation and preventing consequent dust storms.
Application of remote sensing techniques and machine learning algorithms in dust source detection and dust source susceptibility mapping (Ecological Informatics)
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