Feature based decision methodology for vegetation classification

PolSAR features have great significance in application of vegetation classification, which can explain the scattering mechanism of the vegetation; the decision tree classifier not only can obtain good classification accuracy, but also can adjust the classification results, as well as make full use of PolSAR features to explain the scattering mechanism of the targets because of its simple and hierarchical classifier structure. Since all the classification methods are composed of two parts: feature selection and classifier selection, this paper established a classification method with PolSAR features as selected feature and decision tree as adopted classifier. As decision tree classifier is flexible in discriminant rules, the expected design of the experimental scheme introduces multiple data sources, multiple features and multiple classifiers into the framework of this classification method. In addition, discussion about how to improve the classification accuracy of the specific target has been made. The experiment of AIRSAR-Flevoland data illustrates the feasibility of this method.