Integrated detection and analysis of earthquake disaster information using airborne data

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 m2) 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.

[1]  D. Alexander.  Disease epidemiology and earthquake disaster. The example of Southern Italy after the 23 November 1980 earthquake. , 1982, Social science & medicine.

[2]  G. Grünthal.  European Macroseismic Scale 1998 , 1998 .

[3]  Naoki OGAWA,et al.  PHOTO-INTERPRETATION OF BUILDING DAMAGE DUE TO EARTHQUAKES USING AERIAL PHOTOGRAPHS , 1999 .

[4]  Hajime Mitomi,et al.  Automated damage detection of buildings from aerial television images of the 2001 Gujarat, India earthquake , 2001, IGARSS 2001. Scanning the Present and Resolving the Future. Proceedings. IEEE 2001 International Geoscience and Remote Sensing Symposium (Cat. No.01CH37217).

[5]  Eric Emerson.  Challenging behaviour: Assessment and analysis , 2001 .

[6]  L. Chiroiu,et al.  DAMAGE ASSESSMENT USING HIGH RESOLUTION SATELLITE IMAGERY: APPLICATION TO 2001 BHUJ, INDIA, EARTHQUAKE , 2001 .

[7]  Sanjeeb Bhoi,et al.  Changes observed in land and ocean after Gujarat earthquake of 26 January 2001 using IRS data , 2002 .

[8]  Distributions of landslides triggered by the Chi-chi Earthquake in Central Taiwan on September 21, 1999 [E] : Mountains and slopes(GEOMORPHOLOGICAL ABSTRACTS (2001)From scientific papers published in Japan) , 2002 .

[9]  Norman Kerle,et al.  Post - earthquake damage assessment using satellite and airborne data in the case of the 1999 Kocaeli earthquake, Turkey , 2004 .

[10]  Masashi MATSUOKA,et al.  BUILDING DAMAGE DETECTION OF THE 2003 BAM , IRAN EARTHQUAKE USING QUICKBIRD IMAGES BASED ON OBJECT-BASED CLASSIFICATION , 2004 .

[11]  Mustafa Turker,et al.  Detection of collapsed buildings caused by the 1999 Izmit, Turkey earthquake through digital analysis of post-event aerial photographs , 2004 .

[12]  L. Gusella,et al.  IMAGE CHANGE DETECTION ON URBAN AREA : THE EARTHQUAKE CASE , 2004 .

[13]  M. Turker,et al.  Automatic detection of earthquake‐damaged buildings using DEMs created from pre‐ and post‐earthquake stereo aerial photographs , 2005 .

[14]  Kashmir’s Earthquake Victims: Starvation and exposure to cold threaten hundreds of thousands. , 2005 .

[15]  Masashi Matsuoka,et al.  Detection and Animation of Damage using very High-Resolution Satellite Data following the 2003 Bam, Iran, Earthquake , 2005 .

[16]  M. Matsuoka,et al.  Visual Damage Interpretation of Buildings in Bam City using QuickBird Images following the 2003 Bam, Iran, Earthquake , 2005 .

[17]  Errors from the consumer's perspective: tragedy motivated one woman to take action. , 2005, Journal of infusion nursing : the official publication of the Infusion Nurses Society.

[18]  Saro Lee,et al.  Earthquake-induced landslide-susceptibility mapping using an artificial neural network , 2006 .

[19]  Masahiro Chigira,et al.  Geological and geomorphological characteristics of landslides triggered by the 2004 Mid Niigta prefecture earthquake in Japan , 2006 .

[20]  Ramesh P. Singh,et al.  Anomalous increase of chlorophyll concentrations associated with earthquakes , 2006 .

[21]  Menas Kafatos,et al.  Generic precursors to coastal earthquakes: Inferences from Denali fault earthquake , 2007 .

[22]  Guo Xiao-ning.  A Review on Methods of Extracting Earthquake Damage Information Using Remote Sensing Technology , 2008 .

[23]  Zhang Bao-jun,et al.  Study on Urgent Monitoring and Assessment in Wenchuan Earthquake , 2008 .

[24]  Yongjun Zhang,et al.  Photogrammetry for First Response in Wenchuan Earthquake , 2009 .

[25]  Ning Liu,et al.  Draining Tangjiashan Barrier Lake after Wenchuan Earthquake and the flood propagation after the dam break , 2009 .

[26]  Chunxiang Cao,et al.  Change detection of an earthquake-induced barrier lake based on remote sensing image classification , 2010 .

[27]  Menas Kafatos,et al.  Precursory signals using satellite and ground data associated with the Wenchuan Earthquake of 12 May 2008 , 2010 .

[28]  Guang Liu,et al.  Yushu earthquake synergic analysis using multimodal SAR datasets , 2010 .

[29]  Huili Gong,et al.  Collapsed houses automatic identification based on texture changes of post-earthquake aerial remote sensing image , 2010, 2010 18th International Conference on Geoinformatics.

[30]  Zhang Wenjuan.  Assessment and analysis of collapsing houses by aerial images in the Wenchuan earthquake , 2010, National Remote Sensing Bulletin.

[31]  M. Sintubin,et al.  Assessment of seismically induced damage using LIDAR: The ancient city of Pınara (SW Turkey) as a case study , 2010 .

[32]  Ramesh P. Singh,et al.  Satellite detection of carbon monoxide emission prior to the Gujarat earthquake of 26 January 2001 , 2010 .

[33]  Wang Aihua,et al.  Urgent monitoring and analysis on Yushu Earthquake using remote sensing , 2010 .

[34]  Qifeng Lu,et al.  Estimating Wenchuan Earthquake induced landslides based on remote sensing , 2010 .

[35]  Wei Chen,et al.  Assessment of the degree of building damage caused by the 2010 Yushu, China earthquake using satellite and airborne data , 2011 .

[36]  Xiaoqing Wang,et al.  Extracting damages caused by the 2008 Ms 8.0 Wenchuan earthquake from SAR remote sensing data , 2011 .

[37]  Qiuming Gong,et al.  Spatial distribution of landslides triggered by the 2008 Ms 8.0 Wenchuan earthquake, China , 2011 .

[38]  Tariq M. Nahhas.  A comparison of IBC with 1997 UBC for modal response spectrum analysis in standard-occupancy buildings , 2011 .

[39]  Xu Qiang,et al.  Spatial distribution of large-scale landslides induced by the 5.12 Wenchuan Earthquake , 2011 .

[40]  Chong Xu,et al.  Landslides triggered by slipping-fault-generated earthquake on a plateau: an example of the 14 April 2010, Ms 7.1, Yushu, China earthquake , 2013, Landslides.

[41]  Can Ge,et al.  Source parameters inversion of the 2013 Lushan earthquake by combining teleseismic waveforms and local seismograms , 2013, Science China Earth Sciences.

[42]  Jie Shan,et al.  A comprehensive review of earthquake-induced building damage detection with remote sensing techniques , 2013 .

[43]  Xiong Xiong,et al.  Crustal and upper mantle structure and the deep seismogenic environment in the source regions of the Lushan earthquake and the Wenchuan earthquake , 2013, Science China Earth Sciences.

[44]  Xu Chong.  SPATIAL ANALYSIS OF LANDSLIDES TRIGGERED BY THE 2013 M_S 7. 0 LUSHAN EARTHQUAKE: A CASE STUDY OF A TYPICAL RECTANGLE AREA IN THE NORTHEAST OF TAIPING TOWN , 2013 .

[45]  Ying Wu,et al.  Development of an UAS for post-earthquake disaster surveying and its application in Ms7.0 Lushan Earthquake, Sichuan, China , 2014, Comput. Geosci..

[46]  Nigel MacLennan,et al.  Assessment and Analysis , 2017 .