| 基于面向对象分类的稀土开采区遥感信息提取方法研究 |
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| 关键词:ion-absorbed rare earth ore object-oriented classification image segmentation feature extraction accuracy |
| 基金项目:中国地质调查局项目“华南重点矿集区稀有稀散和稀土矿产调查项目”(编号: DD20160056);“川西甲基卡大型锂矿资源基地综合调查评价”(编号: DD20160055) |
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| 摘要: |
| Object-oriented Classification for the Extraction of Remote Sensing Information in Rare Earth Mining Areas |
| Ion-absorbed rare earth is a valuable mineral resource, and using remote sensing image classification technology to extract rare earth mining area can accurately realize monitoring of Rare Earth Mining; nevertheless, it is difficult to ensure the extraction accuracy only by taking advantage of the spectral information. In this paper, object-oriented classification of IKONOS image was carried out to extract rare earth mining area of Xunwu in Jiangxi Province. In consideration of different characteristics of the rare earth mining area, edge segmentation algorithm was used to segment the image, and the terrain information, spectral information and geometric information were used to establish rule set in order to extract the feature. Finally, object-oriented classification was implemented by membership function method, and compared with traditional spectral angle mapping. The result indicates that extraction accuracy of the rare earth mining area is 92.49% and the Kappa coefficient is 0.857 6 by using the object-oriented classification method. Compared with the traditional supervised classification method, the extraction has been greatly improved. |
| DAI Jing-jing,WU Ya-nan,WANG Deng-hong,LING Tian-yu,WANG Jun-hua.2018.Object-oriented Classification for the Extraction of Remote Sensing Information in Rare Earth Mining Areas[J].Acta Geoscientica Sinica,39(1):111-118. |
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