Classification Methods for Remotely Sensed Data, Second Edition

by Paul Mather Brandt Tso, Paul Mather

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. The book also includes updated bibliographic references and updated discussions and descriptions of Earth observation missions. 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..

376 pages, Loose Leaf

First published April 1, 2009

Reviews

[Reader · Rating 5 out of 5]

Covering the up to date classification methods and providing a comprehensive references in remote sensing classification fields.