DocumentCode :
2090963
Title :
Automated damage detection of buildings from aerial television images of the 2001 Gujarat, India earthquake
Author :
Mitomi, Hajime ; Saita, Jun ; Matsuoka, Masashi ; Yamazaki, Fumio
Author_Institution :
Earthquake Disaster Mitigation Res. Center, Hyogo, Japan
Volume :
1
fYear :
2001
fDate :
2001
Firstpage :
147
Abstract :
A severe earthquake, which heavily affected Gujarat Province in western India, occurred on 26 January 2001. Using aerial television images taken with a digital video camera from a light plane in the reconnaissance survey carried out by one of the authors, automated detection of areas with building damage, based on both the multi level slice method and the maximum likelihood classifier, was attempted. Areas of building damage were defined based on six image characteristics derived from color indices and edge elements. The resulting estimated distributions of areas of building damage were in good agreement with the actual situation, although we found that it was difficult to use the same threshold values and training data for all the images because of differences in some factors, such as the influence of sunshine and built environment in the two methods
Keywords :
disasters; earthquakes; edge detection; geography; image classification; maximum likelihood estimation; remote sensing; video signal processing; 26 January 2001; AD 2001 01 26; Gujarat; India; aerial television images; automated damage detection; buildings; built environment; color indices; digital video; edge elements; image characteristics; maximum likelihood classifier; multi level slice method; severe earthquake; sunshine; Digital cameras; Ear; Earthquakes; Image edge detection; Maximum likelihood detection; Maximum likelihood estimation; Pixel; Reconnaissance; Remote monitoring; TV;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium, 2001. IGARSS '01. IEEE 2001 International
Conference_Location :
Sydney, NSW
Print_ISBN :
0-7803-7031-7
Type :
conf
DOI :
10.1109/IGARSS.2001.976085
Filename :
976085
Link To Document :
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