This comprehensive pilot study aims to globally map sand and dust storms (SDS) hazards, employing remote sensing data, advanced Geographic Information System (GIS) analysis and cutting-edge software such as Google Earth Engine, Python, R Studio, and PostgreSQL. The primary objective is to create a detailed hazard map, assessing the frequencies, intensities, and trends of SDS events worldwide. This mapping effort serves as a critical foundation for understanding the distribution and severity of SDS occurrences.
Beyond hazard mapping, the study delves into identifying key drivers behind SDS events, including climate change, land cover transformations, and over-grazing. Utilizing multi-regression statistical analyses, the research aims to isolate and calculate the individual contribution of these drivers, creating a statistical model that sheds light on the interaction between variables and their overall influence on SDS occurrences.
Furthermore, the study extends to impact assessment by intersecting the developed model with diverse databases. It seeks to identify significant SDS trends, analyzing the cascading effects on agriculture, drought susceptibility, soil degradation, migration patterns, and potential conflicts. This holistic approach is crucial for understanding the societal and environmental consequences of SDS events.
In essence, the pilot study aspires to provide a comprehensive understanding of SDS hazards, their drivers, and impacts. While hazard mapping remains the primary focus, the research acknowledges the importance of analyzing underlying factors and impacts. This endeavor represents a crucial step toward informed decision-making and the formulation of effective strategies to mitigate the impacts of SDS hazards on both the environment and society. This study exemplifies the potential of environmental data as a powerful tool for positive change in SDS hazard management.