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
Remote Sensing in the Optical and Microwave Regions. Pattern Recognition Principles. Artificial Neural Networks. Support Vector Machines. Methods Based on Fuzzy Set Theory. Decision Trees. Texture Quantization. Modeling Context Using Markov Random Fields. Multisource Classification. Bibliography. Index.