Remote Sensing and AI for Climate-Driven Hazard Assessment

Geospatial Approaches to Risk, Monitoring, and Mitigation

Av Aqil Tariq, Mona S. Ramadan

2499 kr

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Beskrivning

Remote Sensing and AI for Climate-Driven Hazard Assessment: Geospatial Approaches to Risk, Monitoring, and Mitigation addresses the urgent need for advanced geospatial tools to manage increasing climate-related hazards. This volume combines satellite data, GIS technologies, and artificial intelligence to improve hazard detection, risk assessment, and mitigation strategies. It is designed for researchers, environmental scientists, GIS specialists, and policymakers working on climate vulnerability and disaster risk reduction. The book offers a structured approach across chapters, covering theory, data sources, analytical methods, and practical case studies from regions like the UAE, China, and Southeast Asia, emphasizing real-world applications. Its regional focus and integration of cutting-edge analytics enable professionals to develop innovative solutions for urban resilience and climate adaptation. By bridging foundational knowledge with advanced geospatial analysis, this reference empowers users to make data-driven decisions, enhance disaster preparedness, and support sustainable development in a changing climate.

Integrates remote sensing, AI, and geospatial analytics for hazard assessment
Applies analytical frameworks to diverse climate hazards with real-world datasets
Offers regional case studies from climate-vulnerable environments
Presents a templated chapter structure for clarity and comparability
Combines foundational concepts with advanced analytical methods

Produktinformation

Utgivningsdatum: 2027-04-01
Mått: 152 x 229 x undefined mm
Format: Häftad
Språk: Engelska
Serie: Earth Observation
Antal sidor: 380
Förlag: Elsevier Science
ISBN: 9780443454684

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Dr. Aqil Tariq is a Research Associate in the Department of Wildlife, Fisheries, and Aquaculture at Mississippi State University, USA. His research interests are 3D geoinformation, urban analytics, spatial analysis to examine land use/land cover, geospatial data science, urban planning, crop identification using SAR and optical satellite imagery, agriculture monitoring, forest fire, forest monitoring, forest cover dynamics, spatial statistics, multi-criteria algorithms, ecosystem sustainability, hazards risk reduction, statistical analysis and modeling (Google Earth Engine, HEC-RAS, FlowR, RAMMS, GeoClaw, COSI-Corr, SfM) using Python, R, and MATLAB. He is a member of different international science communities, i.e., Individual Membership of ISPRS, International Water Resources Association, International Association of Geodesy, and the Surveying & Spatial Sciences Institute (SSSI). He has attended more than 30 training workshops from the National Aeronautics and Space Agency (NASA) ARSET program.Dr. Mona S. Ramadan is an Assistant Professor in the Department of Geography and Urban Sustainability at UAE University. Her research interests include urban sustainability, climate change monitoring, air quality modeling, spatial decision support systems, and land use analysis. With more than 12 peer-reviewed publications indexed in Scopus and active roles as a co-investigator in several funded projects, Dr. Ramadan integrates remote sensing, AI, and MCDA to advance urban and environmental planning aligned with the Sustainable Development Goals (SDGs). Her expertise adds considerable value to the editorial vision of this book.

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