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Advanced GIScience in Hydro-Geological Hazards

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Produktnummer: 18e3db8d98b8ae41eb953381881449b671
Themengebiete: Artificial Intelligence Artificial Neural Networks Deep Learning GIS Geospatial Technology Hazard Hydro-geological Hazards Machine Learning Remote Sensing Support Vector Machine
Veröffentlichungsdatum: 03.02.2025
EAN: 9783031761881
Sprache: Englisch
Seitenzahl: 401
Produktart: Gebunden
Herausgeber: Rahman, Atiqur Rahman, Md. Rejaur Saha, S. K.
Verlag: Springer International Publishing
Untertitel: Applications, Modelling and Management
Produktinformationen "Advanced GIScience in Hydro-Geological Hazards"
In recent decades, natural hazards have increasingly threatened lives, livelihoods, and economies, with annual losses totalling billions of dollars globally. According to the Insurance Information Institute (III) and the Zebra, USA, natural disaster losses reached $74.4 billion in 2020, and an average of 6,800 natural disasters occur each year, claiming around 1.35 million lives. Hydrological and geological hazards, in particular, have significant societal and environmental impacts, making them critical areas of research. Understanding and mitigating these hazards is vital for developing legal mechanisms related to environmental restoration, societal improvements, and sustainable development.Modern technologies and earth observation data play a crucial role in disaster monitoring, prediction, modelling, and management. Recent advancements in geoinformation science have introduced multi-source data for natural hazards research. In addition, cutting-edge methods such as machine learning, deep learning, and big data science offer powerful tools for in-depth studies of natural hazards through remote sensing and geoinformatics. This book, Advanced GIScience in Hydro-Geological Hazards, presents up-to-date contributions on applying advanced GIScience to research various hydro-geological hazards, including floods, landslides, tropical cyclones, soil erosion, coastal erosion, riverbank erosion, coastal area vulnerability, drought, wetlands shrinking etc. It also explores multi-hazard studies using SAR, GNSS, and other innovative methods. The chapters focus on integrating artificial intelligence, machine learning techniques, and remote sensing to enhance preparedness, response, and resilience against these hazards. Targeting a broad audience of academics, scientists, students, environmentalists, government agencies, disaster planners, and GIS experts, this book aims to showcase the latest advancements in GIScience for assessing and managing hydro-geological hazards. It offers strategies for disaster risk reduction and capacity building, providing readers with the knowledge needed to address pressing environmental challenges.
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