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

Image Analysis, Classification, and Change Detection in Remote Sensing: With Algorithms for Python, Fourth Edition, is a book that focuses on the development and implementation of statistical motivated, data-driven techniques for digital image analysis of remotely sensed imagery. It covers wavelet transformations, kernel methods for nonlinear classification, and deep learning in the context of feed forward neural networks. The fourth edition includes an in-depth treatment of a recent sequential change detection algorithm for polarimetric SAR image time series, Python (open source) versions of all of the main image analysis algorithms, easy, platform-independent software installation methods, and examples of cloud programming. 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.

Format: Hardback
Length: 508 pages
Publication date: 19 March 2019
Publisher: Taylor & Francis Ltd

Image Analysis, Classification, and Change Detection in Remote Sensing: With Algorithms for Python, Fourth Edition, is a comprehensive guide focused on developing and implementing data-driven techniques for analyzing digital images obtained from remote sensing. This edition delves into a tight interweaving of statistical and machine learning theory with computer codes, enabling the exploration of various image analysis approaches. It offers comprehensive statistical methods for analyzing optical/infrared and synthetic aperture radar (SAR) imagery, encompassing wavelet transformations, kernel methods for nonlinear classification, and an introduction to deep learning within the context of feedforward neural networks.

New in the Fourth Edition:

An in-depth exploration of a recent sequential change detection algorithm specifically designed for polarimetric SAR image time series.

The inclusion of Python (open source) versions of all primary image analysis algorithms, providing users with readily accessible software tools.

The presentation of easy, platform-independent software installation methods through Docker containerization.

Access to freely accessible imagery through the Google Earth Engine, along with numerous examples of cloud programming utilizing the Google Earth Engine API.

Examination of deep learning examples, including TensorFlow, and a solid introduction to neural networks, making this edition particularly valuable for students and professionals in the field.

In comparison to other textbooks in the market, Professor Cantys fourth edition stands out for its exceptional depth and sophistication in the material covered. It consistently employs computer codes to illustrate the methods and algorithms discussed, making it highly practical and accessible. The book is self-contained and extensively illustrated with programming examples, all of which can be conveniently executed within a web browser. Each chapter concludes with exercises that complement or extend the material, enhancing the learning experience.

In summary, Image Analysis, Classification, and Change Detection in Remote Sensing: With Algorithms for Python, Fourth Edition, is an essential resource for anyone seeking to advance their knowledge and skills in remote sensing image analysis. With its comprehensive coverage, practical examples, and user-friendly approach, this textbook is an invaluable tool for researchers, scientists, and practitioners in the field.

Weight: 1062g
Dimension: 238 x 164 x 31 (mm)
ISBN-13: 9781138613225
Edition number: 4 New edition