Abstract
Multifarious regions around the world are exposed to natural hazards and disasters, each with unique characteristics. A higher frequency of extreme hydro-meteorological events, most probably related to climate change, and an increase in vulnerable population have been addressed as potential causes of such disasters. To mitigate the consequences of these disasters, Disaster Risk Management, including hazard assessment, elements-at-risk mapping, vulnerability and risk assessment of spatial components as well as Earth Observation (EO) products and Geographic Information Systems (GIS), should be considered. Multihazard assessment entails the evaluation of relationships between various hazards, including interconnected or cascading events, as well as focusing on various levels from global to local community levels, as each level manifests particular objectives and spatial data. This paper presents an overview of the diverse types of spatial data and explores the methods applied in hazard and risk assessments, with volcanic eruptions serving as a specific example. The rapid development of scientific research and the advancement of Earth Observation satellites in recent years have revolutionized the concepts of geologists and researchers. These satellites now play an indispensable role in supporting first responders during major disasters. The coordination of satellite deployment ensures a swift response along with allowing for the timely delivery of critical images. In tandem, remote sensing technologies and geographic information systems (GIS) have emerged as essential tools for geospatial analysis. The application of remote sensing and GIS for the detection of natural disasters was examined through a review of academic papers, offering an analysis of how remote sensing is utilized to assess natural hazards and their link to climate change.
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Alshehri, A. A. (2025). Utilizing Remote Sensing and GIS to Study Natural Disasters “Volcanoes” and Their Impact on Climate Change. Journal of Environmental and Earth Sciences, 7(1), 573–587. https://doi.org/10.30564/jees.v7i1.7828
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