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A method to detect earthquake-collapsed buildings from high-resolution satellite images

机译:一种从高分辨率卫星图像中检测地震倒塌建筑物的方法

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摘要

A method is proposed to detect collapsed buildings induced by earthquakes. The method computes quantitative indices of the spectral responses for the city plan objects (buildings), assuming that a building was collapsed if the spectral response is sufficiently heterogeneous. First, the pre-earthquake boundaries of buildings stored in the geographic information system (GIS) vector data are used as a reference for determining the extent of each building in the post-image. Second, an improved active contour model is implemented to extract those homogeneous regions in the building boundaries on the post-earthquake image. Third, the shape similarity index (SSI) between the extracted homogeneous region and the corresponding pre-building boundary is calculated, and the area ratio index (ARI) between the extracted homogeneous pixel areas and the true reference pixel areas is calculated. Finally, the k-means clustering method is implemented to partition buildings into collapsed and undamaged sections based on the SSI and ARI. The experimental results indicate the strong robustness and high effectiveness of the proposed method. It is worth noting that a threshold is not needed to determine whether buildings are collapsed. The method quickly and accurately provides information on collapsed buildings.
机译:提出了一种检测地震引起的倒塌建筑物的方法。该方法计算城市规划对象(建筑物)的光谱响应的定量指标,假设如果光谱响应足够不均匀,则建筑物会倒塌。首先,将存储在地理信息系统(GIS)矢量数据中的建筑物的地震前边界用作确定后图像中每个建筑物的范围的参考。第二,实施了改进的主动轮廓模型,以提取地震后图像上建筑物边界中的那些均质区域。第三,计算提取的均匀区域与对应的预建边界之间的形状相似性指数(SSI),并计算提取的均匀像素区域与真实参考像素区域之间的面积比指数(ARI)。最后,基于SSI和ARI,采用k均值聚类方法将建筑物划分为倒塌和未损坏的部分。实验结果表明,该方法具有较强的鲁棒性和有效性。值得注意的是,不需要阈值来确定建筑物是否倒塌。该方法可以快速,准确地提供倒塌建筑物的信息。

著录项

  • 来源
    《Remote sensing letters》 |2013年第12期|1166-1175|共10页
  • 作者

    WENZHONG SHI; MING HAO;

  • 作者单位

    Joint Research Laboratory on Spatial Information, The Hong Kong PolytechnicUniversity and Wuhan University, Wuhan and Hong Kong, China;

    Jiangsu Key Laboratory of Resources and Environmental Information Engineering,China University of Mining and Technology, Xuzhou, China;

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  • 正文语种 eng
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