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从灾后机载激光点云自动检测损毁房屋的等高线簇分析方法
Contour Cluster Shape Analysis for Building Damage Detection from Post-earthquake Airborne LiDAR
【摘要】 利用灾后机载激光扫描点云的地震损毁房屋检测方法主要针对平面屋顶房屋,从局部分析屋顶的平面特征,导致只能有效检测屋顶严重破碎的损毁房屋。为此本文提出了一种等高线簇相似分析的地震损毁房屋检测方法,充分挖掘房屋等高线簇蕴含的房屋表面形状丰富的二维和三维信息,利用等高线簇形状相似度的归一化信息熵从整体上综合描述损毁房屋的损毁特征,并利用最大熵模型自动检测损毁房屋。采用2010年4月El Mayor-Cucapah地震断裂带激光点云数据进行了试验,证明本文提出的方法能快速、准确、可靠地检测损毁房屋。
【Abstract】 Detection of the damaged building is the obligatory step prior to evaluate earthquake casualty and economic losses.It’s very difficult to detect damaged buildings accurately based on the assumption that intact roofs appear in laser data as large planar segments whereas collapsed roofs are characterized by many small segments.This paper presents a contour cluster shape similarity analysis algorithm for reliable building damage detection from the post-earthquake airborne LiDAR point cloud.First we evaluate the entropies of shape similarities between all the combinations of two contour lines within a building cluster,which quantitatively describe the shape diversity.Then the maximum entropy model is employed to divide all the clusters into intact and damaged classes.The tests on the LiDAR data at El Mayor-Cucapah earthquake rupture prove the accuracy and reliability of the proposed method.
【Key words】 contour cluster; shape similarity; entropy; damaged building detection; post-earthquake airborne Li-DAR point cloud;
- 【文献出处】 测绘学报 ,Acta Geodaetica et Cartographica Sinica , 编辑部邮箱 ,2015年04期
- 【分类号】P237;P315.9
- 【网络出版时间】2015-05-05 10:39
- 【被引频次】2
- 【下载频次】161