This study aims to evaluate the texture analysis of high spatial resolution images for mapping tropical forests. More precisely, it evaluates the potential of TerraSAR-X image, with spatial resolution of 0.5 meter for the classification of tropical forests located in southern Cambodia. In particular, the focus is put on the contribution of the analysis of textural information for classification. This latter is apprehended through the analysis of Haralick textural parameters. The retained algorithm of classification is the Support Vector Machine, as it allows taking into account numerous parameters, which can be heterogeneous with respect to their physical dimension. First results show that the addition of Haralick parameters to intensity channel may improve significantly the accuracy of the classification results. However, their performance for classification discrimination strongly depends on the size of the neighborhood from which they are estimated. Preliminary analysis of variograms allows optimizing the choice of the neighborhood size. Best results are obtained with a 25x25 sliding window size, with a classification accuracy improvement higher than 50% is observed.

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This study evaluates the potential of High Resolution Spotlight TerraSAR-X image for forest type discrimination. Emphasis is put on textural analysis accessible with high resolution radar data. Textural attributes are extracted from GLCM matrices, wavelet, and Fourier Transform (i.e. FOTO method). Their contribution for classification is assessed by their performance through the SVM algorithm.

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