Natural Disasters Under Changing Climate: Modeling Strategies, Predictions, and Management is an essential textbook within the natural disaster prediction domain, functioning as a comprehensive book on natural disasters, and focusing on floods, landslides, earthquakes, dust storms, land subsidence, wildfire, sea level rise, drought, snow avalanches, debris flow, desertification, sand dune migration, and heatwaves. In addition to taking a range of natural disasters into account, it covers novel approaches in artificial intelligence and remote sensing and provides an overview of the different concepts of natural disasters perception and how geo-environmental, topo-hydrological, and edaphic variables are connected with their occurrences.

The initial chapters of the book shed light on the main principles and mechanisms of disasters prediction and the application of artificial intelligence algorithms in natural disasters domain. They discuss the applicability of the predictive models in the natural hazards domain and how the understanding of disaster management can happen with the help of disaster susceptibility maps. The book then pivots into landslide susceptibility modeling under climate change and details the use of DInSAR as a powerful tool for studying the effects of earthquakes in various regions. Following that, dust storm frequency and intensity, and how these are impacted by climatic factors, as well as water and land use management, is discussed at length.

• Functions as a comprehensive textbook on natural disasters, focusing on floods, landslides, earthquakes, dust storms, land subsidence, wildfire, sea level rise, drought, snow avalanches, debris flow, and desertification
• Provides unique and cutting-edge research on natural disaster prediction
• Explores novel approaches in the field of artificial intelligence and remote sensing
• Presents scientific frameworks for the spatial prediction of a wide suite of natural disaster types, with a focus on their specific triggers and processes
• Offers study questions and case studies for students and instructors