首页> 外文期刊>International journal of remote sensing >Detection of building damage caused by Van Earthquake using image and Digital Surface Model (DSM) difference
【24h】

Detection of building damage caused by Van Earthquake using image and Digital Surface Model (DSM) difference

机译:使用图像和数字表面模型(DSM)差异检测范袭造成的建筑损坏

获取原文
获取原文并翻译 | 示例
           

摘要

An earthquake occurred at Van City on 23 October 2011 at 13:41 local time with the local magnitude (ML) 6.7 and moment magnitude (Mw) 7.0. Approximately seventeen thousand buildings collapsed or were damaged, and 644 people died because of the main earthquake and its aftershocks. One hundred and fifty-two aerial images of the earthquake area covering 1,296 km(2) were taken with an UltraCam X large format digital aerial camera with 30 cm ground sample distance (GSD) just one day after the earthquake on 24 October 2011. This study attempted to detect damaged buildings automatically with the help of pre and post-earthquake aerial images. With the image and digital surface model (DSM), different methods are used for damage detection, but it was seen that these methods are not satisfactory. So, a novel approach that uses the geometric characteristics of buildings, i.e. area and area to perimeter ratios, was introduced to improve the results. The results show that 'Area/Perimeter' approach improves the damage detection accuracy considerably.
机译:在2011年10月23日在van City发生了地震,在本地时间上午13:41,局部幅度(ml)6.7和时刻幅度(MW)7.0。大约七千建筑物崩溃或损坏,而644人因主要的地震和余震而死亡。覆盖1,296公里(2)的地震面积的一百五十二个空中图像用Ultracam X大型数字空中摄像头,在2011年10月24日的地震后的一天,只有30厘米的地面样品距离(GSD)。这个研究试图在地震前和后地震空中图像的帮助下自动检测受损的建筑物。通过图像和数字表面模型(DSM),不同的方法用于损坏检测,但有人看出这些方法并不令人满意。因此,引入了一种使用建筑物的几何特征的新方法,即面积与周边比率,以改善结果。结果表明,“面积/周边”方法显着提高了损坏检测精度。

著录项

  • 来源
    《International journal of remote sensing》 |2019年第10期|3772-3786|共15页
  • 作者

    Erdogan Mustafa; Yilmaz Altan;

  • 作者单位

    Gen Command Mapping Photogrammetry Dept Ankara Turkey;

    Gen Command Mapping Photogrammetry Dept Ankara Turkey;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

相似文献

  • 外文文献
  • 中文文献
  • 专利
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