Natural Hazards GIS-Based Spatial Modeling Using Data Mining Techniques

Natural Hazards GIS-Based Spatial Modeling Using Data Mining Techniques Hamid Reza Pourghasemi, Mauro Rossi
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. Categories:
Computers – Web Development
Year:
2019
Edition:
1st ed.
Publisher:
Springer International Publishing
Language:
english
Pages:
311
ISBN 10:
3319733834
ISBN 13:
9783319733838
Series:
Advances in Natural and Technological Hazards Research 48
File:
143 MB