Classification Methods for Remotely Sensed Data
Title | Classification Methods for Remotely Sensed Data PDF eBook |
Author | Paul Mather |
Publisher | CRC Press |
Pages | 358 |
Release | 2001-12-06 |
Genre | Technology & Engineering |
ISBN | 9780203303566 |
Remote sensing is an integral part of geography, GIS and cartography, used by academics in the field and professionals in all sorts of occupations. The 1990s saw the development of a range of new methods of classifying remote sensing images and data, both optical imaging and microwave imaging. This comprehensive survey of the various techniques pul
Classification Methods for Remotely Sensed Data, Second Edition
Title | Classification Methods for Remotely Sensed Data, Second Edition PDF eBook |
Author | Brandt Tso |
Publisher | CRC Press |
Pages | 378 |
Release | 2009-05-12 |
Genre | Business & Economics |
ISBN |
Keeping abreast of new developments, this new edition provides a comprehensive and up-to-date review of the entire field of classification methods applied to remotely sensed data. It provides seven fully revised chapters and two new chapters covering support vector machines (SVM) and decision trees.
Classification Methods for Remotely Sensed Data
Title | Classification Methods for Remotely Sensed Data PDF eBook |
Author | Paul Mather |
Publisher | CRC Press |
Pages | 378 |
Release | 2016-04-19 |
Genre | Technology & Engineering |
ISBN | 1420090747 |
Since the publishing of the first edition of Classification Methods for Remotely Sensed Data in 2001, the field of pattern recognition has expanded in many new directions that make use of new technologies to capture data and more powerful computers to mine and process it. What seemed visionary but a decade ago is now being put to use and refined in
Computer Processing of Remotely-Sensed Images
Title | Computer Processing of Remotely-Sensed Images PDF eBook |
Author | Paul M. Mather |
Publisher | John Wiley & Sons |
Pages | 442 |
Release | 2005-12-13 |
Genre | Science |
ISBN | 0470021012 |
Remotely-sensed images of the Earth's surface provide a valuable source of information about the geographical distribution and properties of natural and cultural features. This fully revised and updated edition of a highly regarded textbook deals with the mechanics of processing remotely-senses images. Presented in an accessible manner, the book covers a wide range of image processing and pattern recognition techniques. Features include: New topics on LiDAR data processing, SAR interferometry, the analysis of imaging spectrometer image sets and the use of the wavelet transform. An accompanying CD-ROM with: updated MIPS software, including modules for standard procedures such as image display, filtering, image transforms, graph plotting, import of data from a range of sensors. A set of exercises, including data sets, illustrating the application of discussed methods using the MIPS software. An extensive list of WWW resources including colour illustrations for easy download. For further information, including exercises and latest software information visit the Author's Website at: http://homepage.ntlworld.com/paul.mather/ComputerProcessing3/
Classification Methods for Remotely Sensed Data
Title | Classification Methods for Remotely Sensed Data PDF eBook |
Author | Taskin Kavzoglu |
Publisher | CRC Press |
Pages | 444 |
Release | 2024-09-04 |
Genre | Technology & Engineering |
ISBN | 104009905X |
The third edition of the bestselling Classification Methods for Remotely Sensed Data covers current state-of-the-art machine learning algorithms and developments in the analysis of remotely sensed data. This book is thoroughly updated to meet the needs of readers today and provides six new chapters on deep learning, feature extraction and selection, multisource image fusion, hyperparameter optimization, accuracy assessment with model explainability, and object-based image analysis, which is relatively a new paradigm in image processing and classification. It presents new AI-based analysis tools and metrics together with ongoing debates on accuracy assessment strategies and XAI methods. New in this edition: Provides comprehensive background on the theory of deep learning and its application to remote sensing data. Includes a chapter on hyperparameter optimization techniques to guarantee the highest performance in classification applications. Outlines the latest strategies and accuracy measures in accuracy assessment and summarizes accuracy metrics and assessment strategies. Discusses the methods used for explaining inherent structures and weighing the features of ML and AI algorithms that are critical for explaining the robustness of the models. This book is intended for industry professionals, researchers, academics, and graduate students who want a thorough and up-to-date guide to the many and varied techniques of image classification applied in the fields of geography, geospatial and earth sciences, electronic and computer science, environmental engineering, etc.
Remotely Sensed Data Characterization, Classification, and Accuracies
Title | Remotely Sensed Data Characterization, Classification, and Accuracies PDF eBook |
Author | Ph.D., Prasad S. Thenkabail |
Publisher | CRC Press |
Pages | 698 |
Release | 2015-10-02 |
Genre | Technology & Engineering |
ISBN | 1482217872 |
A volume in the Remote Sensing Handbook series, Remotely Sensed Data Characterization, Classification, and Accuracies documents the scientific and methodological advances that have taken place during the last 50 years. The other two volumes in the series are Land Resources Monitoring, Modeling, and Mapping with Remote Sensing, and Remote Sensing of
Assessing the Accuracy of Remotely Sensed Data
Title | Assessing the Accuracy of Remotely Sensed Data PDF eBook |
Author | Russell G. Congalton |
Publisher | CRC Press |
Pages | 210 |
Release | 2008-12-12 |
Genre | Mathematics |
ISBN | 1420055135 |
Accuracy assessment of maps derived from remotely sensed data has continued to grow since the first edition of this groundbreaking book. As a result, the much-anticipated new edition is significantly expanded and enhanced to reflect growth in the field. The new edition features three new chapters, including: Fuzzy accuracy assessmentPositional accu