Sequential SAR Coherence Method for the Monitoring of Buildings in Sarpole-Zahab, Iran
Sequential SAR Coherence Method for the Monitoring of Buildings in Sarpole-Zahab, Iran
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DOI：
10.3390/rs10081255
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发表时间：
2018-08-01
期刊：
影响因子：
5
通讯作者：
Karashi, Jafar
中科院分区：
文献类型：
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作者：
Karimzadeh, Sadra;Matsuoka, Masashi;Karashi, Jafar
在这项研究中，我们使用从Sentinel-1 c波段卫星获取的56张合成孔径雷达（SAR）图像，常规周期为12天（除了一张图像），为2017年11月12日经历7.3级地震的伊朗西部Sarpole-Zahab镇制作了顺序相位相关（顺序相干）地图。基于长序列SAR相干性（LSSC）方法评估了该镇建筑物的震前状况，其中我们考虑了56幅图像中的55幅，以产生具有气候和时间参数的相干性衰减模型。采用短序贯SAR相干性（SSSC）方法，利用3幅后期影像和归一化RGB可视化技术对建筑物的同震状况进行评价。通过考虑建筑物的高度和SSSC结果，还对大约700个随机选择的建筑物（每个类别）进行了完全倒塌和未倒塌的建筑物之间的判别分析。最后，基于判别图和城镇三维矢量图的融合计算碎片的面积和体积。
In this study, we used fifty-six synthetic aperture radar (SAR) images acquired from the Sentinel-1 C-band satellite with a regular period of 12 days (except for one image) to produce sequential phase correlation (sequential coherence) maps for the town of Sarpole-Zahab in western Iran, which experienced a magnitude 7.3 earthquake on 12 November 2017. The preseismic condition of the buildings in the town was assessed based on a long sequential SAR coherence (LSSC) method, in which we considered 55 of the 56 images to produce a coherence decay model with climatic and temporal parameters. The coseismic condition of the buildings was assessed with 3 later images and normalized RGB visualization using the short sequential SAR coherence (SSSC) method. Discriminant analysis between the completely collapsed and uncollapsed buildings was also performed for approximately 700 randomly selected buildings (for each category) by considering the heights of the buildings and the SSSC results. Finally, the area and volume of debris were calculated based on a fusion of a discriminant map and a 3D vector map of the town.