This edited volume assesses capabilities of data mining algorithms for spatial modeling of natural hazards in different countries based on a collection of essays written by experts in the field. The book is organized on different hazards including landslides, flood, forest fire, land subsidence, earthquake, and gully erosion. Chapters were peer-reviewed by recognized scholars in the field of natural hazards research. Each chapter provides an overview on the topic, methods applied, and discusses examples used. The concepts and methods are explained at a level that allows undergraduates to understand and other readers learn through examples. This edited volume is shaped and structured to provide the reader with a comprehensive overview of all covered topics. It serves as a reference for researchers from different fields including land surveying, remote sensing, cartography, GIS, geophysics, geology, natural resources, and geography. It also serves as a guide for researchers, students, organizations, and decision makers active in land use planning and hazard management.
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Hamid Reza Pourghasemi is an Assistant Professor of Watershed Management Engineering in the College of Agriculture, Shiraz University, Iran. He has a BSc (2004) in watershed management engineering from the University of Gorgan, Iran, a MSc (2008) in watershed management engineering and a PhD degree (2014) in watershed management engineering from Tarbiat Modares University, Iran. His main research interests are GIS-based spatial modelling using machine learning/data mining techniques in different fields such as landslide susceptibility and hazard, flood, gully erosion, forest fire, and groundwater. Also, Hamid Reza works on multi-criteria decision-making methods in natural resources and environment. He has published more than 70 research papers in different international journals (h-index 17).
Mauro Rossi is a Research Scientist from the “Consiglio Nazionale delle Ricerche” (CNR) in Roma, Italy. He is pursuing his research at the “Istituto di Ricerca per laProtezione Idrogeologica” (IRPI) in Perugia, Italy. He has diversified research interests mainly focused on mapping, modelling and forecasting of landslides, floods and erosion processes in different geo-environmental and anthropic contexts. Mauro Rossi has developed (i) new methodologies for statistical and deterministic analysis of the susceptibility and hazard posed by different geo-hydrological phenomena and for the estimation of their impacts, (ii) new approaches to the definition of rainfall thresholds for triggering Landslides, (iii) early warning systems, (iv) approaches to the design optimal models for estimating landslide susceptibility and for the assessment of social risk posed by landslides and floods. He has also developed specific software for the landslide susceptibility modelling, for the landslide magnitude modelling and for the joint modelling of landslides and erosion processes in relation to different scenarios of geomorphological, climatic, vegetation and anthropic changes, in order to adequately characterize the hill slopes and the hydrological basins dynamics. He has published more than 150 research papers in many international journals (h-index 31).
This edited volume assesses capabilities of data mining algorithms for spatial modeling of natural hazards in different countries based on a collection of essays written by experts in the field. The book is organized on different hazards including landslides, flood, forest fire, land subsidence, earthquake, and gully erosion. Chapters were peer-reviewed by recognized scholars in the field of natural hazards research. Each chapter provides an overview on the topic, methods applied, and discusses examples used. The concepts and methods are explained at a level that allows undergraduates to understand and other readers learn through examples. This edited volume is shaped and structured to provide the reader with a comprehensive overview of all covered topics. It serves as a reference for researchers from different fields including land surveying, remote sensing, cartography, GIS, geophysics, geology, natural resources, and geography. It also serves as a guide for researchers, students, organizations, and decision makers active in land use planning and hazard management.
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Da: Universitätsbuchhandlung Herta Hold GmbH, Berlin, Germania
25 cm. XXII, 296 p. Hardcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Advances in Natural and Technological Hazards Research. Volume 48. Sprache: Englisch. Codice articolo 34430AB
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Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This edited volume assesses capabilities of data mining algorithms for spatial modeling of natural hazards in different countries based on a collection of essays written by experts in the field. The book is organized on different hazards including landslides, flood, forest fire, land subsidence, earthquake, and gully erosion. Chapters were peer-reviewed by recognized scholars in the field of natural hazards research. Each chapter provides an overview on the topic, methods applied, and discusses examples used. The concepts and methods are explained at a level that allows undergraduates to understand and other readers learn through examples. This edited volume is shaped and structured to provide the reader with a comprehensive overview of all covered topics. It serves as a reference for researchers from different fields including land surveying, remote sensing, cartography, GIS, geophysics, geology, natural resources, and geography. It also serves as a guide for researchers, students, organizations, and decision makers active in land use planning and hazard management. 320 pp. Englisch. Codice articolo 9783319733821
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Offers useful studies on geo-spatial modelling for optimal land use management and planning Discusses with concrete examples the use of data mining algorithms for spatial modeling of natural hazards in different countries Offers high accu. Codice articolo 196939964
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Buch. Condizione: Neu. Natural Hazards GIS-Based Spatial Modeling Using Data Mining Techniques | Hamid Reza Pourghasemi (u. a.) | Buch | xxii | Englisch | 2019 | Springer | EAN 9783319733821 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand. Codice articolo 111054817
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Buch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This edited volume assesses capabilities of data mining algorithms for spatial modeling of natural hazards in different countries based on a collection of essays written by experts in the field. The book is organized on different hazards including landslides, flood, forest fire, land subsidence, earthquake, and gully erosion. Chapters were peer-reviewed by recognized scholars in the field of natural hazards research. Each chapter provides an overview on the topic, methods applied, and discusses examples used. The concepts and methods are explained at a level that allows undergraduates to understand and other readers learn through examples. This edited volume is shaped and structured to provide the reader with a comprehensive overview of all covered topics. It serves as a reference for researchers from different fields including land surveying, remote sensing, cartography, GIS, geophysics, geology, natural resources, and geography. It also serves as a guide for researchers, students, organizations, and decision makers active in land use planning and hazard management.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 320 pp. Englisch. Codice articolo 9783319733821
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