Quantitative Remote Sensing: Fundamentals and Environmental Applications - Jay Gao
Sáb Sep 21, 2024 7:55 pm
pdf | 21.65 MB | English| Isbn:9781040154816 | Author: Jay Gao | Year: 2024[/center]
Description:
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
[*]Explains how to retrieve quantitative information on a wide range of environmental parameters from various tailored remote sensing data at the highest accuracy possible.
[*]Manifests the author's decades of teaching and research in quantitative remote sensing and approaches the subject from both theoretical and pragmatic perspectives, informed by the latest research outcomes.
[*]Includes practical and real-life examples to illustrate how the quantitative information on a target can be retrieved from a given type of remote sensing data.
[*]Focuses on the latest developments in the field of quantitative remote sensing.
[*]Introduces sufficient mathematical concepts to reveal how remotely sensed data are converted to quantitative information while providing quality assurance of the retrieved results.
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.
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