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Book synopsis

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 into three parts which were under the editorial responsibility of different section editors: (1) Geophysical disasters, (2) Hydrological disasters, and (3) climatological disaster. The first part consists of landslides and earthquake (seismic) disasters. The second part includes flash flood, erosion, and land subsidence research. The final part focuses on climate change, forest fire, land fire, and drought subjects. 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.

Book details

Book category Books in English Computing & information technology Computer science Artificial intelligence

• Full title: Natural Hazards GIS-Based Spatial Modeling Using Data Mining Techniques
• Author: Hamid Reza Pourghasemi, Mauro Rossi
• Language: English
• Binding: Hardback
• Number of pages: 296
• EAN: 9783319733821
• ISBN: 3319733826
• ID: 18656954
• Publisher: Springer International Publishing AG
• Weight: 776 g
• Dimensions: 235 × 155 × 21 mm
• Date of publishing: 24. January 2019

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