首页> 外文期刊>Remote Sensing >An Integrated Method Combining Remote Sensing Data and Local Knowledge for the Large-Scale Estimation of Seismic Loss Risks to Buildings in the Context of Rapid Socioeconomic Growth: A Case Study in Tangshan, China
【24h】

An Integrated Method Combining Remote Sensing Data and Local Knowledge for the Large-Scale Estimation of Seismic Loss Risks to Buildings in the Context of Rapid Socioeconomic Growth: A Case Study in Tangshan, China

机译:社会经济快速增长背景下遥感数据与本地知识相结合的建筑地震损失风险的大规模估算的综合方法:以唐山市为例

获取原文
           

摘要

Rapid socioeconomic development in earthquake-prone areas can cause rapid changes in seismic loss risks. These changes make it difficult to ensure that risk reduction strategies are realistic, practical and effective over time. To overcome this difficulty, ongoing changes in risk should be captured timely, definitively, and accurately and then specific and well-timed adjustments of the relevant strategies should be made. However, methods for rapidly characterizing such seismic disaster risks over a large area have not been sufficiently developed. By focusing on building loss risks, this paper presents the development of an integrated method that combines remote sensing data and local knowledge to resolve this problem. This method includes two key interdependent steps. (1) To extract the heights and footprint areas of a large number of buildings accurately and quickly from single high-resolution optical remote sensing images; (2) To estimate the floor areas, identify structural types, develop damage probability matrixes, and determine economic parameters for calculating monetary losses due to seismic damage to the buildings by reviewing building-relevant local knowledge based on these two parameters (i.e., the building heights and footprint areas). This method is demonstrated in the Tangshan area of China. Based on the integrated method, the total floor area of the residential and public office buildings in central Tangshan in 2009 was 3.99% lower than the corresponding area number obtained by a conventional earthquake loss estimation project. Our field-based verification indicated that the mean relative error of the method for estimating the floor areas of the assessed buildings was 2.99%. A simulation of the impacts of the 1976 Ms 7.8 Tangshan earthquake using this method indicated that the total damaged floor area of the residential and public office buildings and the associated direct monetary loses in the study area could have been 8.00 and 28.73 times greater, respectively, than in 1976 if this earthquake had recurred in 2009, which is a strong warning to the local people regarding the increasing challenges they may face.
机译:在地震多发地区,社会经济的快速发展会导致地震损失风险的快速变化。这些变化使得难以确保随着时间的推移降低风险的策略是现实,实用和有效的。为了克服这一困难,应及时,确定,准确地捕捉到不断变化的风险,然后应对相关策略进行具体且及时的调整。然而,尚未充分开发用于在大范围内快速表征这种地震灾难风险的方法。通过关注建筑物损失风险,本文提出了一种结合遥感数据和本地知识来解决此问题的集成方法的开发。该方法包括两个关键的相互依赖的步骤。 (1)从单个高分辨率光学遥感图像中准确快速地提取大量建筑物的高度和占地面积; (2)通过基于这两个参数(例如,建筑物)审查与建筑物相关的当地知识,以估计建筑面积,识别结构类型,建立破坏概率矩阵并确定经济参数,以计算由于建筑物遭受地震破坏而造成的金钱损失高度和占地面积)。该方法在中国唐山地区得到了证明。基于综合方法,2009年唐山市中心的住宅和公共办公楼总建筑面积比常规地震损失估算项目获得的相应建筑面积少3.99%。我们的实地验证表明,用于评估被评估建筑物的建筑面积的方法的平均相对误差为2.99%。使用这种方法对1976年唐山7.8级地震的影响进行的模拟表明,研究区域中住宅和公共办公大楼的总受损地面面积以及相关的直接金钱损失分别可以增加8.00倍和28.73倍,如果地震在2009年再次发生,那将比1976年要大,这是对当地人民面临的日益严峻挑战的强烈警告。

著录项

相似文献

  • 外文文献
  • 中文文献
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号