Sanchez-Hernandez, Carolina and Boyd, Doreen S. and Foody, Giles M. (2007) One-class classification for monitoring a specific land cover class: SVDD classification of fenland. IEEE Transactions

Remote sensing is a major source of land cover information. Commonly, interest focuses on a single land cover class. Although a conventional multi-class classifier may be used to provide a map depicting the class of interest the analysis is not focused on that class and may be sub-optimal in terms of the accuracy of its classification. With a conventional classifier, considerable effort is directed on the classes that are not of interest. Here, it is suggested that a one-class classification approach could be appropriate when interest focuses on a specific class. This is illustrated with the classification of fenland, a habitat of considerable conservation value, from Landsat ETM+ imagery. A range of one-class classifiers are evaluated but attention focuses on the support vector data description (SVDD). The SVDD was used to classify fenland with an accuracy of 97.5% and 93.6% from the user’s and producer’s perspectives respectively. This classification was trained upon only the fenland class and was substantially more accurate in fen classification than a conventional multi-class maximum likelihood classification provided with the same amount of training data,