Classification Methods for Remotely Sensed Data by Paul

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Synopsis

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.
 

About Paul

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Paul Mather has been Professor of Geographical Information Science at The University of Nottingham, UK since 1988. BA (Cambridge), PhD (Nottingham). Main research interests: multivariate analysis of spatial data ("Computational Methods of Multivariate Analysis in Physical Geography," Chichester, John Wiley, 1976) and digital image processing applied to remotely sensed data, particularly algorithms for classification and pattern recognition ("Classification Methods for Remotely Sensed Data," with B. Tso, London, Taylor and Francis, 2001). Awarded OBE in the Queen's Jubilee Honours in 2002 for 'services to remote sensing and photogrammetry'. Recipient of The Remote Sensing Society's Gold Medal in 1996. Presented with the Back Award of the Royal Geographical Society for 'contributions to remote sensing' in 1992. Winner of the Dearing Award for "Outstanding contribution to the development of teaching and learning," The University of Nottingham, 2003. Invited speaker/lecturer at conferences/courses all over the world (e.g., Japan, Indonesia, India, South Africa, Poland, Hungary, Bulgaria, Spain).
 
Published April 16, 2007 by Taylor & Francis. 352 pages
Genres: Science & Math, Professional & Technical, Nature & Wildlife, Education & Reference. Non-fiction

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