Natural Disasters Under Changing Climate: Modeling Strategies, Predictions, and Management is an essential textbook within the natural disaster prediction domain. It functions as a comprehensive book on natural disasters, and focuses 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 wide range of natural disasters into account, it covers novel approaches in the field of artificial intelligence and remote sensing in detail. It also 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. This textbook delves into applications of novel artificial intelligence approaches, including machine-learning and deep-learning algorithms and new remote sensing platforms and techniques. It presents the scientific frameworks for spatial prediction of a wide suite of natural disasters with a focus on specific triggers and processes. 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. This textbook is a critical resource for upper-level undergraduate students in earth and environmental sciences, specifically those studying or researching physical geography, environmental sciences, geospatial and geohazard modeling, and integrated watershed management. It is also useful for professionals in the field of environmental science, natural disasters, climate change, and sustainability. This textbook contains study questions and case studies as additional resources for students and instructors.
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Dr. Omid Rahmati is a Geo-environmental Researcher and Assistant Professor at the AREEO institute, Iran. He has widespread research interests in risk, modeling, uncertainty, and decision-making in relation to natural hazards and natural resources management. He has published over 70 articles in international peer-reviewed journals and has been cited over 7000 times. He has been selected as the Highly Cited Researchers (the world's top 1% scientists) in 2022 and 2023 based on the Web of Science (Clarivate) who has demonstrated broad and significant influence reflected in his publications over the last decade.
Zahra Kalantari has successfully led and carried out interdisciplinary research with focus on understanding of earth and human systems to develop science, technology and innovation solutions to planet's most pressing environmental challenges associated with the combined effects of changes in climate, land-use and water-use in terrestrial environments.
Bahram Choubin is an Assistant Professor at the West Azarbaijan Agricultural and Natural Resources Research and Education Center in Urmia, Iran. He has been working at this center since 2019. Before that, he was a Postdoctoral Researcher at the University of Tehran from 2018 to 2019. He has published more than 50 articles in JCR-indexed journals and is a scientific reviewer for more than 80 ISI journals. According to Elsevier's World Scientists Rankings, he is among the top 2% of scientists in the world. Choubin's primary research interests encompass hydrometeorology, natural hazard prediction, forecasting in ungauged basins (PUB), advanced machine learning techniques, and cutting-edge radar/remodeling applications in hazard assessment. As a prolific co-author of numerous peer-reviewed research articles and book chapters within these fields, Choubin has been recognized with several prestigious awards for his scientific contributions (e.g., from Iran's National Elites Foundation).
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Taschenbuch. Etat : Neu. Neuware -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. 752 pp. Englisch. N° de réf. du vendeur 9780443338793
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Taschenbuch. Etat : Neu. Neuware -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. 752 pp. Englisch. N° de réf. du vendeur 9780443338793
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Taschenbuch. Etat : Neu. Neuware -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. N° de réf. du vendeur 9780443338793
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Taschenbuch. Etat : Neu. Natural Disasters Under Changing Climate | Modeling Strategies, Predictions, and Management | Omid Rahmati (u. a.) | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2026 | Elsevier LTD | EAN 9780443338793 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu. N° de réf. du vendeur 136363093
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Taschenbuch. Etat : Neu. Neuware -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.Libri GmbH, Europaallee 1, 36244 Bad Hersfeld 752 pp. Englisch. N° de réf. du vendeur 9780443338793
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