THE RESEARCH OF BUILDING EARTHQUAKE DAMAGE OBJECT-ORIENTED CHANGE DETECTION BASED ON ENSEMBLE CLASSIFIER WITH REMOTE SENSING IMAGE

被引:0
|
作者
Zhao Yan [1 ]
Ren Huazhong
Cao Desheng
机构
[1] Peking Univ, Beijing, Peoples R China
来源
IGARSS 2018 - 2018 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM | 2018年
关键词
change detection; Object-oriented; multi-feature joint segmentation; classifier Integration;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
An accurate and quick detection and seismic classification of the building earthquake damage is significant for disaster emergency and rescue. This paper aimed at quickly, precisely and efficiently detecting building damage information. According to the analysis of the problems existing in present research, a technical process for the VHR remote sensing image of the building earthquake damage information object-oriented change detection was proposed for its extraction through different degrees of improvement and innovation for the key technologies. The final building earthquake damage information result was output by accuracy evaluation through using classification evaluation criteria and other indicators. The change detection accuracy of the Yushu small area is 88.45% with the Kappa coefficient was 0.8411. It was proved and verified that the proposed method can make up for the classification deficiency based on the single data source, and realized the complementary advantages among the classifiers, which can improve the classification accuracy.
引用
收藏
页码:4950 / 4953
页数:4
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