Estimation of earthquake casualties using high-resolution remote sensing: a case study of Dujiangyan city in the May 2008 Wenchuan earthquake

From a disaster relief perspective, an immediate and efficient rescue operation after an earthquake can greatly increase the number of survivors. An effective rescue operation depends on two key elements: localisation of the affected areas and estimation of the number of casualties in these areas. Many more studies have been conducted on the localisation of affected areas than on casualty estimation. Consequently, this study develops a model for rapidly estimating the number of casualties using satellite remote sensing (SRS). The model is based on the attributes of damaged buildings, as these buildings cause the greatest harm to inhabitants and they can be detected by SRS. The model uses the damage index (DI) of buildings computed by a numerical damage model derived from SRS images to assess the extent of damage. The DI is then combined with the building’s materials and structure index, which is calculated using information from the local geographic information system, to compute the joint casualty index (JCI). Finally, the number of casualties is estimated by the product of the JCI multiplied by the number of people inside the damaged buildings at the time of the earthquake. The model is then applied to three towns in Dujiangyan City, as these were the areas that most severely affected by the Wenchuan earthquake. Preliminary results showed that there was little difference between the actual and estimated number of casualties. It is recommended that more casualty data should be included in the model to improve the accuracy of estimation.

[1]  K. Jacobsen,et al.  Comparison of Matching Algorithms for DSM Generation in Urban Areas from Ikonos Imagery , 2010 .

[2]  R. Stone An Unpredictably Violent Fault , 2008, Science.

[3]  Yi Zhang,et al.  Emergency medical rescue efforts after a major earthquake: lessons from the 2008 Wenchuan earthquake , 2012, The Lancet.

[4]  M. Jaboyedoff,et al.  Brief communication "Report on the impact of the 27 February 2010 earthquake (Chile, M w 8.8) on rockfalls in the Las Cuevas valley, Argentina" , 2010 .

[5]  Jochen Schwarz,et al.  Comparative Seismic Risk Studies for German Earthquake Regions on the Basis of the European Macroseismic Scale EMS-98 , 2006 .

[6]  M. Mokhtar,et al.  Generating a dengue risk map (DRM) based on environmental factors using remote sensing and GIS technologies , 2007 .

[7]  Robin Spence,et al.  Analytical study on vulnerability functions for casualty estimation in the collapse of adobe buildings induced by earthquake , 2010 .

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

[9]  Lorenzo Bruzzone,et al.  Change detection for earthquake damage assessment in built-up areas using very high resolution optical and SAR imagery , 2010, 2010 IEEE International Geoscience and Remote Sensing Symposium.

[10]  X. Tong,et al.  Building-damage detection using pre- and post-seismic high-resolution satellite stereo imagery: A case study of the May 2008 Wenchuan earthquake , 2012 .

[11]  X. Tong,et al.  Bias-corrected rational polynomial coefficients for high accuracy geo-positioning of QuickBird stereo imagery , 2010 .

[12]  Haruo Hayashi,et al.  Building Damage and Casualties after an Earthquake , 2003 .

[13]  Timo Balz,et al.  Building-damage detection using post-seismic high-resolution SAR satellite data , 2010 .

[14]  Badrinath Roysam,et al.  Image change detection algorithms: a systematic survey , 2005, IEEE Transactions on Image Processing.

[15]  Atilla Ansal Preface to the second decade , 2013, Bulletin of Earthquake Engineering.

[16]  Carlo Atzeni,et al.  Remote monitoring of buildings using a ground-based SAR: Application to cultural heritage survey , 2000 .

[17]  Jochen Schwarz,et al.  Estimation of Human Casualties from Earthquakes in Pakistan—An Engineering Approach , 2011 .

[18]  Zifa Wang A preliminary report on the Great Wenchuan Earthquake , 2008 .

[19]  Michael Batty,et al.  GIS and remote sensing as tools for the simulation of urban land‐use change , 2005 .

[20]  X. Tong,et al.  Use of shadows for detection of earthquake-induced collapsed buildings in high-resolution satellite imagery , 2013 .

[21]  P. Sharma,et al.  Use of GIS and remote sensing for crop diversification — a case study for Punjab state , 2005 .

[22]  Li-Li Xie,et al.  A conception of casualty control based seismic design for buildings , 2007 .

[23]  L. R. Beck,et al.  Perspectives Perspectives Perspectives Perspectives Perspectives Remote Sensing and Human Health: New Sensors and New Opportunities , 2022 .

[24]  A. W. Coburn Factors determining human casualty levels in earthquakes : Motality prediction in building collapse , 1992 .

[25]  Unfallchirurgische Katastrophenhilfe nach dem Erdbeben in Haiti 2010 - Ein Erfahrungsbericht , 2011, Der Unfallchirurg.

[26]  A. Tertulliani,et al.  An application of EMS98 in a medium-sized city: The case of L’Aquila (Central Italy) after the April 6, 2009 Mw 6.3 earthquake , 2011 .

[27]  C. Tao,et al.  A Comprehensive Study of the Rational Function Model for Photogrammetric Processing , 2001 .

[28]  Russell Blong,et al.  A New Damage Index , 2003 .

[29]  Carlo Tomasi,et al.  Depth Discontinuities by Pixel-to-Pixel Stereo , 1999, International Journal of Computer Vision.

[30]  C. Tao,et al.  3D Reconstruction methods based on the rational function model , 2002 .

[31]  Ma Yu-hon Methodologies for assessment of earthquake casualty , 2000 .

[32]  Shigeyuki Okada,et al.  CLASSIFICATIONS OF STRUCTURAL TYPES AND DAMAGE PATTERNS OF BUILDINGS FOR EARTHQUAKE FIELD INVESTIGATION , 1999 .

[33]  José Badal,et al.  Estimation of the Expected Number of Casualties Caused by Strong Earthquakes , 2002 .

[34]  Jing-Fa Zhang,et al.  Change detection of earthquake-damaged buildings on remote sensing image and its application in seismic disaster assessment , 2003, IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477).

[35]  R. Spence,et al.  Estimating shaking-induced casualties and building damage for global earthquake events: a proposed modelling approach , 2013, Bulletin of Earthquake Engineering.

[36]  Erika Upegui,et al.  GeoEye Imagery and Lidar Technology for Small-area Population Estimation: An Epidemiological Viewpoint , 2012 .