Extraction of metamorphic minerals by multi-scale segmentation combined with random forest
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摘要: 为提高遥感影像变质矿物提取精度，提升变质带的识别效果，以甘肃北山ASTER影像为研究区，结合了比值运算、多尺度分割、随机森林分类法进行变质矿物提取。首先，通过矿物特征性光谱特征构造比值运算公式、进行影像增强；然后，对增强影像进行基于光谱及变差函数的多尺度分割；接着，采用随机森林法提取目标矿物；最后，通过野外勘查、采样、薄片鉴定进行精度评价。结果表明，黑云母、白云母、角闪石在ASTER影像上具有鉴定性特征，提取精度分别为85.4088%、84.7640%、85.7308%；其他含量较少的变质矿物提取精度可达到60%以上。多尺度分割能充分利用矿物的丛集特征；变差函数纹理能增强形态特征对矿物的区分能力；随机森林分类法对矿物混合引起的噪声不敏感、提取结果稳定。Abstract: To improve the extraction accuracy of metamorphic minerals from remote sensing images and further improve the recognition effect of metamorphic zones, we combines ratio operation, multi-scale segmentation and random forest classification to extract metamorphic mineral information from Aster images in Beishan area in Gansu Province. Initially, the image is enhanced by the ratio formula of the characteristic spectral structure of the target mineral; then, the image is segmented by multi-scale based on the spectrum and variogram; finally, the accuracy is evaluated by the thin film identification results of the field exploration samples after the target mineral is extracted by random forest. The results show that biotite, muscovite and amphibole have identification characteristics on ASTER image, and the extraction accuracy is 85.4088%, 84.7640% and 85.7308% respectively; the extraction accuracy of other metamorphic minerals with less content can reach more than 60%. Multi-scale segmentation can make full use of the clustering features of minerals; variogram texture can enhance the ability of morphological features to distinguish minerals; random forest is not sensitive to noise and the extraction results are stable.
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Key words:
- variogram /
- multiscale segmentation /
- aster /
- mineral extraction /
- random forest
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