Image Analysis, Classification and Change Detection in Remote Sensing: With Algorithms for Python, Fourth Edition, 4th Edition (Hardback) book cover

Image Analysis, Classification and Change Detection in Remote Sensing

With Algorithms for Python, Fourth Edition, 4th Edition

By Morton John Canty

CRC Press

508 pages | 153 Color Illus.

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Hardback: 9781138613225
pub: 2019-03-14
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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)

Table of Contents

Images, Arrays, and Matrices. Image Statistics. Transformations. Filters, Kernels and Fields. Image Enhancement and Correction. Supervised Classification Part 1. Supervised Classification Part 2. Unsupervised Classification. Change Detection. Mathematical Tools. Efficient Neural Network Training Algorithms. Software

About the Author

Morton John Canty is a senior research scientist in the Institute for Bio- and Geosciences at the Juelich Research Center in Germany, now semi-retired. He received his PhD in Nuclear Physics in 1969 at the University of Manitoba, Canada and, after post-doctoral positions in Bonn, Groningen and Marburg, began work in Juelich in 1979. There, his principal interests have been the development of statistical and gametheoretical models for the verification of international treaties and the use of remote sensing data for monitoring global treaty compliance. He has served on numerous advisory bodies to the German federal government and to the International Atomic Energy Agency in Vienna and was a coordinator within the European Network of Excellence on Global Monitoring for Security and Stability, funded by the European Commission. Morton Canty is the author of three monographs in the German language: on the subject of non-linear dynamics (Chaos und Systeme, Vieweg, 1995), neural networks for classification of remote sensing data (Fernerkundung mit neuronalen Netzen, Expert, 1999) and algorithmic game theory (Konfliktl¨osungen mit Mathematica, Springer 2000). The latter text has appeared in a revised English version (Resolving Conflicts withMathematica, Academic Press, 2003). He is co-author of a monograph on mathematical methods for treaty verification (Compliance Quantified, Cambridge University Press, 1996). He has published many papers on the subjects of experimental nuclear physics, nuclear safeguards, applied game theory and remote sensing. He has lectured on nonlinear dynamical growth models and remote sensing digital image analysis to students at both the graduate and undergraduate level at Universities in Bonn, Berlin, Freiberg/Saxony and Rome.

Subject Categories

BISAC Subject Codes/Headings:
MATHEMATICS / Arithmetic
SCIENCE / Earth Sciences / General
SCIENCE / Environmental Science
TECHNOLOGY & ENGINEERING / Remote Sensing & Geographic Information Systems