黄土地震滑坡卫星影像识别方法
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常晁瑜(1990-),男,博士研究生,讲师,主要从事岩土工程抗震研究。E-mail:changchaoyu@126.com。

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国家自然科学基金项目(U1939209);宁夏自然科学基金项目(2021AAC03486);河北省高等学校科学研究计划(QN2021309);中国地震局建筑物破坏机理与防御重点实验室开放基金(FZ201209)


A satellite image recognition method for loess seismic landslides
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    摘要:

    为获得详细的地震滑坡数据和分布特征,揭示黄土地震滑坡的成灾模式和防治措施,需要对黄土地区地震滑坡进行详细的编录,利用卫星影像的识别方法是重要的手段之一。通过总结黄土地震滑坡特有的空间分布特征、平面形态特征、地震滑坡发育特征和伴生水文特征,归纳利用卫星影像识别黄土地震滑坡的7种识别标志。利用该方法,研究通渭地区黄土地震滑坡的空间分布与规律,结果表明:黄土地震滑坡卫星影像识别方法获得的滑坡与野外现场调查结果相近;通渭地区滑坡拥有缓坡发育、低角度、中远滑距、大体积、方向性明显等特点。

    Abstract:

    To obtain the disaster mode and prevention measures of loess seismic landslide, detailed landslide data and distribution characteristics were needed, so the recognition method using satellite images is the basis for cataloging the loess seismic landslides. By summarizing the spatial distribution characteristics, plane morphological characteristics, development characteristics, and associated hydrological characteristics of loess seismic landslides, seven kinds of identification marks for loess seismic landslides using satellite images were summarized in this paper. The spatial distribution regularity of loess landslides in Tongwei area were studied by the proposed method. The results show that the loess landslides obtained by the satellite image recognition method are similar to the field investigation results. The landslides in Tongwei area are characterized by gentle slope development, low angle, medium and long distance, large volume, and obvious direction.

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常晁瑜,杨顺,薄景山,段玉石,乔峰.黄土地震滑坡卫星影像识别方法[J].地震工程学报,2022,44(4):811-818. CHANG Chaoyu, YANG Shun, BO Jingshan, DUAN Yushi, QIAO Feng. A satellite image recognition method for loess seismic landslides[J]. China Earthquake Engineering Journal,2022,44(4):811-818.

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  • 在线发布日期: 2022-08-04