technology & engineering > remote sensing & geographic information systems
Quantitative Remote Sensing: Fundamentals and Environmental Applications
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This book provides comprehensive and in-depth explanations of all topics related to quantitative remote sensing and its applications in terrestrial, biospheric, hydrospheric, and atmospheric studies. It elucidates how to retrieve quantitative information on a wide range of environmental parameters from various remote sensing data at the highest accuracy possible and expounds how different aspects of the target of remote sensing can be quantified using diverse analytical methods and level of accuracy. Written in an easy-to-follow language, logically organized, and with step-by-step examples, the book assists readers to deepen their understanding of the theory and cutting-edge research on quantitative remote sensing.
Features
This is a suitable textbook for upper-level undergraduate or postgraduate students and serves as a handy and valuable reference for professionals working in monitoring the environment. By reading this book, readers gain a sound understanding of how to retrieve quantitative information on the environment from diverse remote sensing data using the most appropriate cutting-edge methods and software.
Dr. Jay Gao is an Associate Professor at the Faculty of Science, University of Auckland, New Zealand. He received his BE in photogrammetric engineering from Wuhan Technical University of Surveying and Mapping, China; his MS from the University of Toronto, Canada; and his PhD from the University of Georgia in the U.S. in 1992. Over his academic career, has carried out many research projects on remote sensing, GIS, GPS and their integrated applications in natural resource management and environmental monitoring focused on quantitative remote sensing and integration of geo-computational methods. His recent research is focused on mapping of land covers from satellite imagery using spatial information. He is an Associate Editor of ISPRS Journal of Photogrammetry and Remote Sensing and has published numerous research articles. His textbook Digital Analysis of Remotely Sensed Imagery was published in 2009.
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