Contribution of TerraSAR-X radar images texture for forest monitoring
Contribution of TerraSAR-X radar images texture for forest monitoring
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TerraSAR-X 雷达图像纹理对森林监测的贡献
DOI：
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发表时间：
2012
期刊：
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通讯作者：
J. Rudant
中科院分区：
文献类型：
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作者：
Hajar Benelcadi;P. Frison;C. Lardeux;Anne Cécile Capel;J. Routier;J. Rudant
本研究旨在评估高空间分辨率影像的纹理分析在热带森林制图中的应用。更准确地说，它评估了空间分辨率为0.5米的TerraSAR-X图像对柬埔寨南部热带森林分类的潜力。特别强调了纹理信息的分析对分类的贡献。后者是通过对哈拉里克语篇结构参数的分析来理解的。保留的分类算法是支持向量机，因为它允许考虑许多参数，这些参数在物理维度上可能是不同的。第一个结果表明，在强度通道中加入Haralick参数可以显著提高分类结果的精度。然而，他们在分类区分方面的表现很大程度上取决于他们所在社区的大小。对变异函数的初步分析可以优化邻域大小的选择。当滑动窗口大小为25×25时，分类效果最好，分类精度提高50%以上。
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 25×25 sliding window size, with a classification accuracy improvement higher than 50% is observed.