DocumentCode :
2146789
Title :
Earthquake-collapsed building extraction from LiDAR and aerophotograph based on OBIA
Author :
Haiyang, Yu ; Gang, Cheng ; Xiaosan, Ge
Author_Institution :
Key Laboratory of Mine Spatial Information Technologies of SBSM, Henan Polytechnic University, Jiaozuo, China
fYear :
2010
fDate :
4-6 Dec. 2010
Firstpage :
2034
Lastpage :
2037
Abstract :
Estimation of damages caused by a large earthquake is a major task in the post disaster mitigation process. To enhance the relief and rescue operation in the affected area it is required to receive rapid, accurate knowledge about the conditions of damaged area. Remote sensing techniques were proved to be useful to detect, identify and monitor the impact and effect of natural disasters in last decades. Recently emerging LiDAR data provide the height of the ground objects, which can be used for extracting the collapsed buildings in a complex urban environment. Using the aerophotographs and the normalized digital surface model (nDSM) extracted from LiDAR data, a method based on OBIA and SVM was developed to extract the earthquake-collapsed building. The test study in Haiti´s capital, Port-au-Prince after 2010 Jan. 12 earthquake shows that the method can extract collapsed buildings with high accuracy.
Keywords :
Buildings; Classification algorithms; Feature extraction; Image segmentation; Laser radar; Remote sensing; Support vector machines; LiDAR; OBIA; SVM; aerophotograph; earthquake-collapsed building extraction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Science and Engineering (ICISE), 2010 2nd International Conference on
Conference_Location :
Hangzhou, China
Print_ISBN :
978-1-4244-7616-9
Type :
conf
DOI :
10.1109/ICISE.2010.5691203
Filename :
5691203
Link To Document :
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