Advanced Remote Sensing,
Edition 2 Terrestrial Information Extraction and Applications
Edited by Shunlin Liang and Jindi Wang

Publication Date: 22 Nov 2019
Description

Advanced Remote Sensing: Terrestrial Information Extraction and Applications, Second Edition, is a thoroughly updated application-based reference that provides a single source on the mathematical concepts necessary for remote sensing data gathering and assimilation. It presents state-of-the-art techniques for estimating land surface variables from a variety of data types, including optical sensors like RADAR and LIDAR. The book provides scientists in a number of different fields, including geography, geophysics, geology, atmospheric science, environmental science, planetary science and ecology with access to critically-important data extraction techniques and their virtually unlimited applications.

While rigorous enough for the most experienced of scientists, the techniques presented are well designed and integrated, making the book’s content intuitive and practical in its implementation.

Key Features

  • Provides a comprehensive overview of many practical methods and algorithms
  • Offers descriptions of the principles and procedures of the state-of-the-art in remote sensing
  • Includes real-world case studies and end-of-chapter exercises
  • Contains thoroughly revised chapters, newly developed applications and updated examples
About the author
Edited by Shunlin Liang, Department of Geography, University of Hong Kong and Jindi Wang, Professor, College of Geography, Beijing Normal University, Beijing, China
Book details
ISBN: 9780128158265
Page Count: 1010
Retail Price : £141.00
  • Schowengerdt, Remote Sensing: Models and Methods for Image Processing, 3e, Academic Press, Sep 2006, 9780123694072, $132.00
  • Mishra, Bio-optical Modeling and Remote Sensing of Inland Waters, Elsevier, May 2017, 9780128046449, $130.00
  • Mackaness, Generalisation of Geographic Information, Elsevier Science, Apr 2007, 9780080453743, $230.00
Audience

Researchers and students in remote sensing, geophysics, geology, geography, planetary science, environmental science