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    中国百强科技报刊

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    中国高校百佳科技期刊

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    Volume 46 Issue 4
    Apr.  2021
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    Article Contents
    Lu Zeen, Tian Yugang, Liu Qingwei, Wang Jing, Zhu Ning, Xu Yadong, 2021. Topographical Linear Feature Extraction Method Based on Sentinel-1 and DEM in Areas with High Vegetation Coverage of Nanling. Earth Science, 46(4): 1349-1358. doi: 10.3799/dqkx.2020.351
    Citation: Lu Zeen, Tian Yugang, Liu Qingwei, Wang Jing, Zhu Ning, Xu Yadong, 2021. Topographical Linear Feature Extraction Method Based on Sentinel-1 and DEM in Areas with High Vegetation Coverage of Nanling. Earth Science, 46(4): 1349-1358. doi: 10.3799/dqkx.2020.351

    Topographical Linear Feature Extraction Method Based on Sentinel-1 and DEM in Areas with High Vegetation Coverage of Nanling

    doi: 10.3799/dqkx.2020.351
    • Received Date: 2020-10-06
    • Publish Date: 2021-04-15
    • Geological surveying is challenging in high-altitude mountains with dense vegetation in Nanling because it is inaccessible both for human and material resources. It is necessary to design reasonable field survey routes in advance according to the topographical linear characteristics of the area. Moreover, the topographical linear characteristics can provide the auxiliary information for local tectonic movement. Remotely sensed technology has become an important method for geological research and geological survey due to its macroscopic, multi-scale and multi-level characteristics. However, in areas with high vegetation coverage, optical remote sensing images are difficult to penetrate vegetation, while microwave radar images can do because of its good vegetation penetration. Therefore, the topographical linear feature extraction method based on Sentinel-1 (radar satellite) and DEM data in areas with high vegetation coverage is proposed. This method first uses the likelihood ratio edge detection algorithm to extract the edge features in Sentinel-1 images. Then, the linear features of DEM are enhanced to generate mountain shadow images, and then the main linear features such as ridge lines and valley lines are extracted by Canny edge detection operator. Finally, taking the feature line extracted from DEM as the center, a buffer zone is established and intersected with the result from radar images, and then the local straight line fitting is done by using the Douglas-Puck algorithm to obtain the final topographical linear features in the study area. The results show that the proposed method comprehensively considers the micro-detail information of radar images and the macro-trend information of DEM data, and can remove false edges and noise points while retaining the main topographical linear features, and the extraction effect is good.

       

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