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Satellite radar and optical remote sensing for earthquake damage detection: results from different case studies

机译:用于地震破坏检测的卫星雷达和光学遥感:来自不同案例研究的结果

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In case of a seismic event, a fast and draft damage map of the hit urban areas can be very useful, in particular when the epicentre of the earthquake is located in remote regions, or the main communication systems are damaged. Our aim is to analyse the capability of remote sensing techniques for damage detection in urban areas and to explore the combined use of radar (SAR) and optical satellite data. Two case studies have been proposed: Izmit (1999; Turkey) and Bam (2003; Iran). Both areas have been affected by strong earthquakes causing heavy and extended damage in the urban settlements close to the epicentre. Different procedures for damage assessment have been successfully tested, either to perform a pixel by pixel classification or to assess damage within homogeneous extended areas. We have compared change detection capabilities of different features extracted from optical and radar data, and analysed the potential of combining measurements at different frequency ranges. Regarding the Izmit case, SAR features alone have reached 70% of correct classification of damaged areas and 5 m panchromatic optical images have given 82%; the fusion of SAR and optical data raised up to 89% of correct pixel-to-pixel classification. The same procedures applied to the Bam test case achieved about 61% of correct classification from SAR alone, 70% from optical data, while data fusion reached 76%. The results of the correlation between satellite remote sensing and ground surveys data have been presented by comparing remotely change detection features averaged within homogeneous blocks of buildings with ground survey data.
机译:在发生地震的情况下,特别是当地震的震中位于偏远地区或主要通信系统受到损坏时,受灾城市地区的快速且草稿的损坏地图可能非常有用。我们的目标是分析遥感技术在城市地区进行损坏检测的能力,并探索雷达(SAR)和光学卫星数据的结合使用。提出了两个案例研究:Izmit(1999;土耳其)和Bam(2003;伊朗)。这两个地区都受到强烈地震的影响,在震中附近的城市定居点造成了严重和长期的破坏。已经成功测试了不同的损伤评估程序,可以按像素分类或评估均匀扩展区域内的损伤。我们比较了从光学和雷达数据中提取的不同特征的变化检测功能,并分析了在不同频率范围内组合测量的潜力。对于伊兹密特一案,仅SAR特征就达到了对受损区域正确分类的70%,而5 m全色光学图像给出了82%。 SAR和光学数据的融合提高了正确像素间像素分类的89%。应用于Bam测试用例的相同程序仅通过SAR就可以实现大约61%的正确分类,通过光学数据可以达到70%,而数据融合达到76%。通过将建筑物同质块内平均的远程变化检测特征与地面测量数据进行比较,提出了卫星遥感与地面测量数据之间相关性的结果。

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