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This book examines the remote sensing technology used to gather information on 12 types of natural hazards in the terrestrial sphere, biosphere, hydrosphere, and atmosphere. It clarifies how to yield spatial and quantitative data on a natural hazard, including its spatial distribution, severity, causes, and the likelihood of occurrence.
List of contents
Preface. Acknowledgments. About the Author. List of Acronyms. Introduction. Earthquakes. Landslides. Land Degradation. Land Desertification. Land Subsidence. Droughts. Dust Storms. Hurricanes and Tornados. Floods. Wild and Coalmine Fires. Volcanoes. Avalanches. Index.
About the author
Jay Gao used to be an associate professor affiliated with the School of Environment, University of Auckland. He received his Bachelor of Engineering degree in the field of photogrammetry and remote sensing from the Wuhan Technical University of Survey and Mapping in 1984. Four years later he obtained his MSc in geography from University of Toronto, Canada, and his PhD in geography from University of Georgia in the US in 1992. Upon graduation he became a faculty member of the current university. His research interest spreads widely among different disciplines of geoinformatics, including remote sensing, digital image analysis, and spatial analysis and modelling. Over his academic career he has completed numerous projects on the applications of remote sensing to the management of natural resources and the studies of natural hazards using remote sensing and GIS. So far he has published nearly 200 papers in international journals, authored two books, and edited several more. His solely authored book on Digital Analysis of Remotely Sensed Data was published by McGraw-Hill in 2009, and his second book on The Fundamentals of Spatial Analysis and Modelling was published by CRC Press in 2021.
Summary
This book examines the remote sensing technology used to gather information on 12 types of natural hazards in the terrestrial sphere, biosphere, hydrosphere, and atmosphere. It clarifies how to yield spatial and quantitative data on a natural hazard, including its spatial distribution, severity, causes, and the likelihood of occurrence.
