文翔, 毕熙荣, 向魏. 基于SVM多源遥感影像的面向对象倒塌建筑物提取研究[J]. 华北地震科学, 2015, 33(3): 11-17. DOI: 10.3969/j.issn.1003-1375.2015.03.003
引用本文: 文翔, 毕熙荣, 向魏. 基于SVM多源遥感影像的面向对象倒塌建筑物提取研究[J]. 华北地震科学, 2015, 33(3): 11-17. DOI: 10.3969/j.issn.1003-1375.2015.03.003
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WEN Xiang, BI Xi-rong, XIANG Wei. Object-Oriented Collapsed Building Extraction From Multi-Source Remote Sensing Imagery Based On SVM[J]. North China Earthquake Sciences, 2015, 33(3): 11-17. DOI: 10.3969/j.issn.1003-1375.2015.03.003
Citation: WEN Xiang, BI Xi-rong, XIANG Wei. Object-Oriented Collapsed Building Extraction From Multi-Source Remote Sensing Imagery Based On SVM[J]. North China Earthquake Sciences, 2015, 33(3): 11-17. DOI: 10.3969/j.issn.1003-1375.2015.03.003
shu

基于SVM多源遥感影像的面向对象倒塌建筑物提取研究

Object-Oriented Collapsed Building Extraction From Multi-Source Remote Sensing Imagery Based On SVM

    摘要
  • 摘要: 快速准确地获取倒塌建筑物信息能为震后救灾工作提供支持。采用玉树灾区LiDAR数据和高分辨率Quickbird遥感数据，通过对研究区内LiDAR数据进行预处理，使用面向对象分类与SVM技术相结合的方法对震后倒塌建筑物信息进行提取，提取总精度达到82.21%。

     

    Abstract: Obtaining collapsed building information rapidly and accurately can provide vital support for the disaster-relief work after the earthquake. In this paper, the LiDAR data and remote sensing data are adopted in the Yushu disaster area, and the LiDAR data is preprocessed in the study area. Then developing a method based on Object-Oriented and SVM for extracting the earthquake-caused collapsed building, the overall accuracy can reach 82.12% in the research.

     

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