Statistical Analysis of Building Damage from the 2013 Super Typhoon Haiyan and its Storm Surge in the Philippines
Tanaporn Chaivutitorn*1, Thawalrat Tanasakcharoen*2, Natt Leelawat*2,*3,, Jing Tang*3,*4, Carl Vincent C. Caro*5, Alfredo Mahar Francisco A. Lagmay*6, Anawat Suppasri*7, Jeremy D. Bricker*8, Volker Roeber*9, Carine J. Yi*10, and Fumihiko Imamura*7
*1School of Management, National Taiwan University of Science and Technology
43, Sec. 4, Keelung Road, Taipei 106, Taiwan
*2Department of Industrial Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok, Thailand
*3Disaster and Risk Management Information Systems Research Group, Chulalongkorn University, Bangkok, Thailand
*4International School of Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok, Thailand
*5Viosimos Integrated Planning Consultants Inc., Bagumbong Caloocan City, The Philippines
*6University of the Philippines Diliman, Manila, The Philippines
*7International Research Institute of Disaster Science (IRIDeS), Tohoku University, Miyagi, Japan
*8Department of Hydraulic Engineering, Delft University of Technology, Delft, The Netherlands
*9Université de Pau et des Pays de l’Adour, Anglet, France
*10R. Park & Associates Inc., Ontario, Canada
In November 2013, Super Typhoon Haiyan (Yolanda) hit the Philippines. It caused heavy loss of lives and extensive damages to buildings and infrastructure. When collapsed buildings are focused on, it is interesting to find that these buildings did not collapse for the same reasons after the landfall of the typhoon and storm surge. The objective of this study is to develop a statistical model for building damage due to Super Typhoon Haiyan and its storm surge. The data were collected in collaboration with Tanauan Municipality, the Philippines. The data for the inundation map were obtained by field surveys conducted on-site to determine the cause of the damages inferred from satellite data. The maximum wind speed was derived from the Holland parametric hurricane model based on the Japan Meteorological Agency (JMA) typhoon track data and the inundation depth of storm surge was calculated using the MIKE model. Multinomial logistic regression was used to develop a model to identify the significant factors influencing the damage to buildings. The result of this work is expected to be used to prepare urban plans for preventing damage from future storms.
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