Author: Russell G. Congalton Publisher: CRC Press ISBN: 1420055135 Category : Mathematics Languages : en Pages : 210
Book Description
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
Author: Russell G. Congalton Publisher: CRC Press ISBN: 0429629354 Category : Mathematics Languages : en Pages : 328
Book Description
The past 10 years have brought amazing changes to the technologies used to turn remotely sensed data into maps. As a result, the principles and practices necessary for assessing the accuracy of those maps have also evolved and matured. This third edition of Assessing the Accuracy of Remotely Sensed Data: Principles and Practices is thoroughly updated and includes five new chapters. Now 15 chapters long, this text is the only one of its kind to provide geospatial analysts with the requisite considerations, tools, and theory necessary to conduct successful and efficient map accuracy assessments; and map users with the knowledge to fully understand the assessment process to ensure effective use of maps. See What’s New in the Third Edition: All original chapters have been updated to include new standards, practices, and methodologies. A new chapter on planning accuracy assessments. A new chapter on assessing maps created using object-based technologies. Two case study chapters - one showcasing the assessment of maps created from traditional methods, and one on the assessment of object-based maps. Emphasis on considering and planning for positional accuracy in concert with thematic accuracy. An appendix containing the internationally recognized ASPRS Positional Accuracy Standards. A new final chapter summarizing the key concepts, considerations and lessons learned by the authors in their decades of implementing and evaluating accuracy assessments. Assessing map accuracy is complex; however, the discussions in this book, together with the many figures, tables, and case studies, clearly present the necessary concepts and considerations for conducting an assessment that is both is practical, statistically reliable, and achievable.
Author: Ross S. Lunetta Publisher: CRC Press ISBN: 0203497589 Category : Technology & Engineering Languages : en Pages : 326
Book Description
Based upon a special symposium sponsored by the U.S. Environmental Protection Agency (EPA), Remote Sensing and GIS Accuracy Assessment evaluates the important scientific elements related to the performance of accuracy assessments for remotely sensed data, GIS data analysis, and integration products. Scientists from federal, state, and local governments, academia, and nongovernmental organizations present technical papers which examine sampling issues, reference data collection, edge and boundary effects, error matrix and fuzzy assessments, error budget analysis, and change detection accuracy assessment. This compilation contains 20 chapters that represent important symposium outcomes.
Author: Ph.D., Prasad S. Thenkabail Publisher: CRC Press ISBN: 1482217872 Category : Technology & Engineering Languages : en Pages : 698
Book Description
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
Author: Paul Mather Publisher: CRC Press ISBN: 9781420090741 Category : Technology & Engineering Languages : en Pages : 376
Book Description
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 commercial applications as well as military ones. Keeping abreast of these new developments, Classification Methods for Remotely Sensed Data, Second Edition provides a comprehensive and up-to-date review of the entire field of classification methods applied to remotely sensed data. This second edition provides seven fully revised chapters and two new chapters covering support vector machines (SVM) and decision trees. It includes updated discussions and descriptions of Earth observation missions along with updated bibliographic references. After an introduction to the basics, the text provides a detailed discussion of different approaches to image classification, including maximum likelihood, fuzzy sets, and artificial neural networks. This cutting-edge resource: Presents a number of approaches to solving the problem of allocation of data to one of several classes Covers potential approaches to the use of decision trees Describes developments such as boosting and random forest generation Reviews lopping branches that do not contribute to the effectiveness of the decision trees Complete with detailed comparisons, experimental results, and discussions for each classification method introduced, this book will bolster the work of researchers and developers by giving them access to new developments. It also provides students with a solid foundation in remote sensing data classification methods.
Author: Prasad Thenkabail Publisher: CRC Press ISBN: 1482282674 Category : Technology & Engineering Languages : en Pages : 2304
Book Description
A volume in the three-volume Remote Sensing Handbook series, Remote Sensing of Water Resources, Disasters, and Urban Studies documents the scientific and methodological advances that have taken place during the last 50 years. The other two volumes in the series are Remotely Sensed Data Characterization, Classification, and Accuracies, and Land Reso
Author: Gustau Camps-Valls Publisher: John Wiley & Sons ISBN: 0470749008 Category : Technology & Engineering Languages : en Pages : 434
Book Description
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.
Author: Qihao Weng Publisher: CRC Press ISBN: 1420091816 Category : Technology & Engineering Languages : en Pages : 610
Book Description
Generating a satisfactory classification image from remote sensing data is not a straightforward task. Many factors contribute to this difficulty including the characteristics of a study area, availability of suitable remote sensing data, ancillary and ground reference data, proper use of variables and classification algorithms, and the analyst's e
Author: Russell G. Congalton
Author: Russell G. Congalton
Author: Russell G. Congalton
Author: Mark E. Jensen
Author: Ross S. Lunetta
Author: Ph.D., Prasad S. Thenkabail
Author: Paul Mather
Author: Prasad Thenkabail
Author: Gustau Camps-Valls
Author: Qihao Weng