Dust storms pose a considerable environmental challenge, predominantly in arid and semi-arid territories. A thorough analysis of the attributes of dust storms is imperative for appraising the associated risks to public health, agricultural yields, industrial operations, and communication networks. The deployment of remote sensing techniques yields an extensive and continuous dataset of atmospheric dust, which is instrumental in discerning dust characteristics. These characteristics encompass the overall dust budget on a global scale, the origination points, the distribution trends, and the regions impacted. In pursuit of these aims, we examine the utilization of satellite imagery datasets across three pivotal categories: (1) pinpointing the origins of dust, (2) tracking their pathways, and (3) evaluating their distribution both spatially and temporally. To facilitate this analysis, we employ datasets and computational models from EUMETSAT, Sentinel, MODIS, and the HYSPLIT model, in conjunction with pertinent indices such as the Brightness Difference Index (BDI), Aerosol Optical Depth (AOD), Dust Optical Depth (DOD), Absorption Index (AI), and Aerosol Extinction Model (AEM). These tools enable us to elucidate the spatiotemporal dynamics of dust sources and migration corridors, particularly in relation to climatic fluctuations.

Keywords