作者:Cao, CX (Cao, Chunxiang)[ 1,2 ] ; Liu, D (Liu, Di)[ 1,3 ] ; Singh, RP (Singh, Ramesh P.)[ 4 ] ; Zheng, S (Zheng, Sheng)[ 1,3 ] ; Tian, R (Tian, Rong)[ 1,3 ] ; Tian, HJ (Tian, Haijing)[ 1,3 ]

GEOMATICS NATURAL HAZARDS & RISK

卷: 7  期: 3  页: 1099-1128

DOI: 10.1080/19475705.2015.1020887

出版年: MAY 3 2016

摘要

The primary goal of this paper is to discuss an integrated approach to efficiently obtaining earthquake damage information. We developed a framework to rapidly obtain earthquake damage information using post-earthquake airborne optical images. The framework is a standard process that includes data selection, preprocessing, damage factor identification, damage factor evaluation and the development of an earthquake damage information map. We can obtain damage information on severely affected regions using this framework, which will aid in planning rescue and rehabilitation efforts following disasters. We used the integrated approach to obtain damage information using the Lushan earthquake (magnitude 7.0, 20 April 2013) as a case study. The result were as follows: (1) 644 collapsed buildings and 4599 damaged buildings accounted for 13.90% and 96.24%, respectively, of the total number of buildings in the study area; (2) 334 landslides (total area of 691,674.5 m(2)) were detected and were found at greater probabilities at elevations of 1400-1500 m and higher slope; (3) no secondary disasters, such as barrier lakes, were detected; (4) 15 damaged sections (total of 306 m) were detected in the lifelines, and road sections that are at a high risk of damage (total of 2.4 km) were identified; and (5) key structures, including Yuxi River Dam and three bridges, were intact. Integrating the earthquake damage factor information generated a comprehensive Lushan earthquake damage information map. The integrated approach was proven to be effective using the Lushan earthquake as a case study and can be applied to assess earthquake damage to facilitate efficient rescue efforts.

通讯作者地址: Cao, CX (通讯作者)

       Inst Remote Sensing & Digital Earth Chinese Acad, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China.

通讯作者地址: Cao, CX (通讯作者)

       Ctr Applicat Spatial Informat Technol Publ Hlth, Beijing 100101, Peoples R China.

地址:

[ 1 ] Inst Remote Sensing & Digital Earth Chinese Acad, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China

[ 2 ] Ctr Applicat Spatial Informat Technol Publ Hlth, Beijing 100101, Peoples R China

[ 3 ] Univ Chinese Acad Sci, Beijing 100049, Peoples R China

[ 4 ] Chapman Univ, Sch Earth & Environm Sci, Schmid Coll Sci & Technol, Orange, CA 02866 USA