DocumentCode
2143498
Title
Extracting damaged building information from single remote sensing images of post-earthquake
Author
Xinjian, Shan ; Jiahang, Liu ; Jingyuan, Yin
Author_Institution
Inst. of Geol., China Seismological Bur., Beijing
Volume
7
fYear
2004
fDate
20-24 Sept. 2004
Firstpage
4496
Abstract
In the high resolution images, undamaged buildings take on natural texture features, but to the damaged or extensive damaged buildings, there are always some low grayscale blocks because of their coarsely damaged section. By using such statistical information as the number of holes in every region, or the ratio between the area of the region and the holes´, et al., damaged buildings can be separated from undamaged buildings, thus automatic detection of damaged buildings can be reached. Based on these characteristics, in this work, a new method to detect the damage buildings automatically by using region structure and statistic information of the texture is presented. Also, in order to test its validity, 1-meter-resolution iKonos merged image of Bhuj earthquake, India, 2001, and grayscale aerial photos of Tangshan earthquake, China, 1976, are selected as two examples to detect the damaged buildings automatically. Satisfactory results are obtained
Keywords
disasters; earthquakes; feature extraction; geophysical signal processing; geophysical techniques; image recognition; image resolution; image texture; remote sensing; statistical analysis; AD 1976; AD 2001; Bhuj earthquake; China; India; Tangshan earthquake; automatic detection; coarsely damaged section; damaged building information extraction; extensive damaged buildings; grayscale aerial photos; high resolution images; iKonos merged image; image texture feature; remote sensing images; statistical information; texture region structure; undamaged buildings; Buildings; Data mining; Earthquakes; Gray-scale; Image recognition; Image resolution; Remote sensing; Satellites; Seismology; Statistics;
fLanguage
English
Publisher
ieee
Conference_Titel
Geoscience and Remote Sensing Symposium, 2004. IGARSS '04. Proceedings. 2004 IEEE International
Conference_Location
Anchorage, AK
Print_ISBN
0-7803-8742-2
Type
conf
DOI
10.1109/IGARSS.2004.1370151
Filename
1370151
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