Natural Hazards GIS-Based Spatial Modeling Using Data Mining Techniques (Hardcover, 1st ed. 2019)

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.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Series:	Advances in Natural and Technological Hazards Research, 48
Release date:	2019
First published:	2019
Editors:	Hamid Reza Pourghasemi • mauro rossi
Dimensions:	235 x 155mm (L x W)
Format:	Hardcover
Pages:	296
Edition:	1st ed. 2019
ISBN-13:	978-3-319-73382-1
Categories:	Books > Earth & environment > The environment > Environmental impact of natural disasters & phenomena Books > Earth & environment > Geography > Cartography, geodesy & geographic information systems (GIS) > Geographical information systems (GIS) Books > Earth & environment > Geography > Cartography, geodesy & geographic information systems (GIS) > Remote sensing Books > Computing & IT > Applications of computing > Databases > Data mining Books > Computing & IT > Applications of computing > Artificial intelligence > Knowledge-based systems / expert systems
LSN:	3-319-73382-6
Barcode:	9783319733821

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