Image Analysis, Classification and Change Detection in Remote Sensing

Name: Image Analysis, Classification and Change Detection in Remote Sensing
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SKU: 9781032475745
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With Algorithms for Python, Fourth Edition

By Morton John Canty

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Summary

Image Analysis, Classification and Change Detection in Remote Sensing: With Algorithms for Python, Fourth Edition by Morton John Canty presents advanced, statistically motivated techniques for digital image analysis of remotely sensed data. This comprehensive guide covers optical/infrared and synthetic aperture radar (SAR) imagery, wavelet transformations, kernel methods for nonlinear classification, and introduces deep learning with feed forward neural networks. New in this edition are sequential change detection algorithms for polarimetric SAR time series, Python-based open source software implementations, Docker containerisation for easy installation, use of Google Earth Engine with cloud programming examples, and TensorFlow deep learning demonstrations. The book combines theory with practical coding examples and exercises, making it a self-contained resource ideal for those interested in cutting-edge remote sensing image analysis.
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Image Analysis, Classification and Change Detection in Remote Sensing

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This text is suitable for advanced students, researchers, and professionals in remote sensing, image processing, and data science, particularly those with an interest in statistical methods, machine learning, and programming in Python for environmental and earth observation applications.

This fourth edition is focused on the development and implementation of statistically motivated, data-driven techniques through a tight interweaving of statistical and machine learning theory with algorithms and computer codes. The material is self-contained and illustrated with many programming examples. It includes Wishart and Python.

Description

Image Analysis, Classification and Change Detection in Remote Sensing: With Algorithms for Python, Fourth Edition, is focused on the development and implementation of statistically motivated, data-driven techniques for digital image analysis of remotely sensed imagery and it features a tight interweaving of statistical and machine learning theory of 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.

New in the Fourth Edition:

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.
Presents easy, platform-independent software installation methods (Docker containerization).
Utilizes freely accessible imagery via the Google Earth Engine and provides many examples of cloud programming (Google Earth Engine API).
Examines deep learning examples including TensorFlow and a sound introduction to neural networks,

Based on the success and the reputation of the previous editions and compared to other textbooks in the market, Professor Canty’s fourth edition differs in the depth and sophistication of the material treated as well as in its consistent use of computer codes to illustrate the methods and algorithms discussed. It 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.

Book Details

INFORMATION

ISBN: 9781032475745

Publisher: Taylor & Francis Ltd

Format: Paperback / softback

Date Published: 21 January 2023

Country: United Kingdom

Imprint: CRC Press

Edition: 4th edition

Audience: General / adult, Tertiary education

DIMENSIONS

Width: 156.0mm

Height: 234.0mm

Weight: 1320g

Pages: 532

Collections

Computing & Technology Education & Reference Engineering, Technology & Agriculture Morton John Canty Science & Nature Uncategorised

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.