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地震

地震 ›› 2013, Vol. 33 ›› Issue (2): 79-86.

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高分辨率遥感影像道路震害的快速提取

刘明众1,2, 张景发1, 李成龙1, 刘国林2   

  1. 1.中国地震局地壳应力研究所, 北京 100085;
    2.山东科技大学测绘科学与工程学院, 山东 青岛 266510
  • 收稿日期:2012-12-20 出版日期:2013-04-30 发布日期:2020-09-27
  • 作者简介:刘明众(1986-), 男, 安徽阜阳人, 硕士研究生, 研究方向为GIS与遥感技术在防震减灾中的应用。
  • 基金资助:
    国家高技术研究发展计划(2012AA121304) 和高分光学卫星遥感应急技术研究(E0205/1112/9)

Rapid Extraction of Road Damages from High Resolution Remote Sensing Images

LIU Ming-zhong1,2, ZHANG Jing-fa1, LI Cheng-long1, LIU Guo-lin2   

  1. 1. Institute of Crustal Dynamics, CEA, Beijing 100085, China;
    2. Geomatics College, Shandong University of Science and Technology, Qingdao 266510, China
  • Received:2012-12-20 Online:2013-04-30 Published:2020-09-27

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摘要： 震后及时获取道路受灾信息, 进行交通通行能力分析, 是抗震救灾的关键之一。 传统的利用遥感技术提取震害信息的方法普遍存在效率低的问题, 影响地震应急的时效性。 本文提出针对特定传感器影像的经验训练参数, 结合面向对象分类, 按照预处理、 影像分类、 震害识别这一流程实现道路震害的快速提取。 实验结果表明, 保障提取效果在一定精度范围内的情况下, 提取速度有明显提高, 有较高的实用意义。

关键词: 高分辨率遥感影像, 面向对象, C#与IDL混编, 震害识别

Abstract: After earthquake, it's a key for relief to access timely to road damage information and analyse traffic capacity. However, traditional method of using remote sensing technology to extract damage information has the problems of low efficiency, and affects the timeliness of earthquake emergency. In our daily training, we focus on a class of sensor images and get the most appropriate parameters, and combining the object-oriented classification, we propose a specific process including preprocessing, image classification, rapid road damage identification. Experimental results show that the method can improve obviously the extraction rate in keeping with a good of classification precision. So it is expected that the method will be applied with much practical uses.

Key words: High resolution remote sensing image, Object-oriented classification, Road damage identification

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