Classification Methods For Remotely Sensed Data
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Classification Methods For Remotely Sensed Data
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Author : Paul Mather
language : en
Publisher: CRC Press
Release Date : 2001-12-06
Classification Methods For Remotely Sensed Data written by Paul Mather and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001-12-06 with Technology & Engineering categories.
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
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Author : Brandt Tso
language : en
Publisher: CRC Press
Release Date : 2009-05-12
Classification Methods For Remotely Sensed Data Second Edition written by Brandt Tso and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-05-12 with Business & Economics categories.
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
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Author : Taskin Kavzoglu
language : en
Publisher: CRC Press
Release Date : 2024-09-04
Classification Methods For Remotely Sensed Data written by Taskin Kavzoglu and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-04 with Technology & Engineering categories.
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.
Classification Methods For Remotely Sensed Data
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Author : Paul Mather
language : en
Publisher: CRC Press
Release Date : 2016-04-19
Classification Methods For Remotely Sensed Data written by Paul Mather and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-04-19 with Technology & Engineering categories.
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
Remotely Sensed Data Characterization Classification And Accuracies
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Author : Ph.D., Prasad S. Thenkabail
language : en
Publisher: CRC Press
Release Date : 2015-10-02
Remotely Sensed Data Characterization Classification And Accuracies written by Ph.D., Prasad S. Thenkabail and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-10-02 with Technology & Engineering categories.
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 Water Resources, Disasters, and Urban Studies. This volume demonstrates the experience, utility, methods, and models used in studying a wide array of remotely sensed data characterization, classification, and accuracies for terrestrial applications. Leading experts on global geographic coverage, study areas, and array of satellite and sensors contribute to this unique handbook. This theoretical as well as highly practical book represents a thorough history of advancement in the field over last 50 years, bringing us to where we are now, and highlighting future possibilities. Highlights include: Fundamental and advanced topics in remote-sensing satellites and sensors Remote sensing data calibration, normalization, harmonization, and synthesis Optical, Radar, LiDAR, thermal, hyperspectral, and other satellite sensors, normalization of remotely sensed data, and data degradations Digital image processing, urban image classification, and image classification methods in land use\land cover, cropland, change detection studies Enhanced vegetation indices and standardization of vegetation indices Object-based image analysis (OBIA) and geospatial data integration LiDAR data processing and applications Geoprocessing, GIS, and GIScience GNSS applications Crowdsourcing and cloud computing Google Earth for Earth Sciences Map accuracies Remote-sensing law or space law, and a host of other topics.
Kernel Methods For Remote Sensing Data Analysis
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Author : Gustau Camps-Valls
language : en
Publisher: John Wiley & Sons
Release Date : 2009-09-03
Kernel Methods For Remote Sensing Data Analysis written by Gustau Camps-Valls and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-09-03 with Technology & Engineering categories.
Kernel methods have long been established as effective techniques in the framework of machine learning and pattern recognition, and have now become the standard approach to many remote sensing applications. With algorithms that combine statistics and geometry, kernel methods have proven successful across many different domains related to the analysis of images of the Earth acquired from airborne and satellite sensors, including natural resource control, detection and monitoring of anthropic infrastructures (e.g. urban areas), agriculture inventorying, disaster prevention and damage assessment, and anomaly and target detection. Presenting the theoretical foundations of kernel methods (KMs) relevant to the remote sensing domain, this book serves as a practical guide to the design and implementation of these methods. Five distinct parts present state-of-the-art research related to remote sensing based on the recent advances in kernel methods, analysing the related methodological and practical challenges: Part I introduces the key concepts of machine learning for remote sensing, and the theoretical and practical foundations of kernel methods. Part II explores supervised image classification including Super Vector Machines (SVMs), kernel discriminant analysis, multi-temporal image classification, target detection with kernels, and Support Vector Data Description (SVDD) algorithms for anomaly detection. Part III looks at semi-supervised classification with transductive SVM approaches for hyperspectral image classification and kernel mean data classification. Part IV examines regression and model inversion, including the concept of a kernel unmixing algorithm for hyperspectral imagery, the theory and methods for quantitative remote sensing inverse problems with kernel-based equations, kernel-based BRDF (Bidirectional Reflectance Distribution Function), and temperature retrieval KMs. Part V deals with kernel-based feature extraction and provides a review of the principles of several multivariate analysis methods and their kernel extensions. This book is aimed at engineers, scientists and researchers involved in remote sensing data processing, and also those working within machine learning and pattern recognition.
Advanced Image Processing Techniques For Remotely Sensed Hyperspectral Data
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Author : Pramod K. Varshney
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-09
Advanced Image Processing Techniques For Remotely Sensed Hyperspectral Data written by Pramod K. Varshney and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-09 with Science categories.
The first of its kind, this book reviews image processing tools and techniques including Independent Component Analysis, Mutual Information, Markov Random Field Models and Support Vector Machines. The book also explores a number of experimental examples based on a variety of remote sensors. The book will be useful to people involved in hyperspectral imaging research, as well as by remote-sensing data like geologists, hydrologists, environmental scientists, civil engineers and computer scientists.
Information Processing For Remote Sensing
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Author : Chi-hau Chen
language : en
Publisher: World Scientific
Release Date : 1999
Information Processing For Remote Sensing written by Chi-hau Chen and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with Computers categories.
This book provides the most comprehensive study of information processing techniques and issues in remote sensing. Topics covered include image and signal processing, pattern recognition and feature extraction for remote sensing, neural networks and wavelet transforms in remote sensing, remote sensing of ocean and coastal environment, SAR image filtering and segmentation, knowledge-based systems, software and hardware issues, data compression, change detection, etc. Emphasis is placed on environmental issues of remote sensing.With 58 color illustrations.
Processing Of Remote Sensing Data
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Author : ColetteM. Girard
language : en
Publisher: Routledge
Release Date : 2018-04-27
Processing Of Remote Sensing Data written by ColetteM. Girard and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-04-27 with Technology & Engineering categories.
Containing useful information sources for the management of natural resources, this comprehensive text covers a large range of spatial resolutions and spectral characteristics. The book deals with the data sources and their physical interpretation, as well as processing techniques, such as visual interpretation and automated classifications, textural and structural processing and photogrammetry. There is a section on accuracy assessment and various applications relating to crops, grasslands, soils, landscapes, mines and coasts. The CD-ROM contains software and image data sets explaining the statistical methods of reference and contains a light version of the TeraVue software enabling the reader to compute the different processing spatial data.
Computer Processing Of Remotely Sensed Images
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Author : Paul M. Mather
language : en
Publisher: John Wiley & Sons
Release Date : 2022-04-11
Computer Processing Of Remotely Sensed Images written by Paul M. Mather and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-04-11 with Technology & Engineering categories.
Computer Processing of Remotely-Sensed Images A thorough introduction to computer processing of remotely-sensed images, processing methods, and applications Remote sensing is a crucial form of measurement that allows for the gauging of an object or space without direct physical contact, allowing for the assessment and recording of a target under conditions which would normally render access difficult or impossible. This is done through the analysis and interpretation of electromagnetic radiation (EMR) that is reflected or emitted by an object, surveyed and recorded by an observer or instrument that is not in contact with the target. This methodology is particularly of importance in Earth observation by remote sensing, wherein airborne or satellite-borne instruments of EMR provide data on the planet’s land, seas, ice, and atmosphere. This permits scientists to establish relationships between the measurements and the nature and distribution of phenomena on the Earth’s surface or within the atmosphere. Still relying on a visual and conceptual approach to the material, the fifth edition of this successful textbook provides students with methods of computer processing of remotely sensed data and introduces them to environmental applications which make use of remotely-sensed images. The new edition’s content has been rearranged to be more clearly focused on image processing methods and applications in remote sensing with new examples, including material on the Copernicus missions, microsatellites and recently launched SAR satellites, as well as time series analysis methods. The fifth edition of Computer Processing of Remotely-Sensed Images also contains: A cohesive presentation of the fundamental components of Earth observation remote sensing that is easy to understand and highly digestible Largely non-technical language providing insights into more advanced topics that may be too difficult for a non-mathematician to understand Illustrations and example boxes throughout the book to illustrate concepts, as well as revised examples that reflect the latest information References and links to the most up-to-date online and open access sources used by students Computer Processing of Remotely-Sensed Images is a highly insightful textbook for advanced undergraduates and postgraduate students taking courses in remote sensing and GIS in Geography, Geology, and Earth & Environmental Science departments.