TY - JOUR
T1 - Statistical analysis of building damage from the 2013 super typhoon haiyan and its storm surge in The Philippines
AU - Chaivutitorn, Tanaporn
AU - Tanasakcharoen, Thawalrat
AU - Leelawat, Natt
AU - Tang, Jing
AU - Caro, Carl Vincent C.
AU - Lagmay, Alfredo Mahar Francisco A.
AU - Suppasri, Anawat
AU - Bricker, Jeremy D.
AU - Roeber, Volker
AU - Yi, Carine J.
AU - Imamura, Fumihiko
N1 - Funding Information:
The authors gratefully acknowledge Haruhiro Inoue, Digestive Diseases Center, Showa University Koto-Toyosu Hospital, for advice on the POEM technique, and Noriaki Manabe, Department of Clinical Pathology and Laboratory Medicine, Kawasaki Medical School, for performing HRM.
Publisher Copyright:
© 2020, Fuji Technology Press. All rights reserved.
PY - 2020
Y1 - 2020
N2 - 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 inter-esting 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 ob-tained 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 Hol-land 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.
AB - 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 inter-esting 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 ob-tained 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 Hol-land 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.
KW - Building damage
KW - Statistical analysis
KW - Storm surge
KW - Super Typhoon Haiyan
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U2 - 10.20965/jdr.2020.p0822
DO - 10.20965/jdr.2020.p0822
M3 - Article
AN - SCOPUS:85097513411
VL - 15
SP - 822
EP - 832
JO - Journal of Disaster Research
JF - Journal of Disaster Research
SN - 1881-2473
IS - 7
ER -