Image Analysis, Classification and Change Detection in Remote Sensing: With Algorithms for Python, Fourth Edition

4th Edition

Morton John Canty

CRC Press
April 2, 2019 Forthcoming
Textbook - 508 Pages - 153 Color Illustrations
ISBN 9781138613225 - CAT# K389347

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The text is focused on the development and implementation of statistically motivated, data-driven techniques for digital image analysis of remotely sensed imagery and features a tight interweaving of statistical and machine learning theory with algorithms with computer codes. It develops statistical methods for the analysis of optical/infrared and synthetic aperture radar (SAR) imagery, including wavelet transformations, kernel methods for nonlinear classification, as well as an introduction to deep learning in the context of feed forward neural networks. The material is self-contained and illustrated with many programming examples, all of which can be conveniently run in a web browser.

Each chapter concludes with exercises complementing or extending the material in the text. Numerous examples of programming the Google Earth Engine and TensorFlow APIs are given. New in the fourth edition is an in-depth treatment of a recent sequential change detection algorithm for polarimetric SAR image time series. The accompanying software consists of Python (open source) versions of all of the main image analysis algorithms, thus accessible to all readers with a computer and an Internet connection.


  • Includes open source software and tools
  • Presents easy, platform-independent software installation methods (Docker containerization)
  • Concepts and algorithms are illustrated in Jupyter notebooks
  • Utilizes freely accessible imagery via the Google Earth Engine
  • Examines deep learning examples including a sound introduction to neural networks
  • Provides many examples of cloud programming (Google Earth Engine API)


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