Predicting the hurricane damage ratio of commercial buildings by claim payout from Hurricane Ike
J. M. Kim1, P. K. Woods1, Y. J. Park2, T. H. Kim3, J. S. Choi4, and K. Son51Texas A&M University, Department of Construction Science, College Station, Texas, USA 2Korea Military Academy, Department of Construction Engineering and Environmental Sciences, Seoul, Republic of Korea 3Mokpo National University, Department of Architectural Engineering, Mokpo, Republic of Korea 4Dongguk University – Seoul Campus, Department of Architectural Engineering, Seoul, Republic of Korea 5University of Ulsan, School of Architecture, Ulsan, Republic of Korea
Received: 27 May 2013 – Accepted for review: 18 Jun 2013 – Discussion started: 23 Jul 2013
Abstract. The increasing occurrence of natural disaster events and related damages have led to a growing demand for models that predict financial loss. Although considerable research has studied the financial losses related to natural disaster events, and has found significant predictors, there has not yet been a comprehensive study that addresses the relationship among the vulnerabilities, natural disasters, and economic losses of the individual buildings. This study identified hurricanes and their vulnerability indicators in order to establish a metric to predict the related financial loss. We identify hurricane-prone areas by imaging the spatial distribution of the losses and vulnerabilities. This study utilized a Geographical Information System (GIS) to combine and produce spatial data, as well as a multiple linear regression method, to establish a hurricane damage prediction model. As the dependent variable, we utilized the following ratio to predict the real pecuniary loss: the value of the Texas Windstorm Insurance Association (TWIA) claim payout divided by the appraised values of the buildings. As independent variables, we selected the hurricane indicators and vulnerability indicators of the built environment and the geographical features. The developed statistical model and results can be used as important guidelines by insurance companies, government agencies, and emergency planners for predicting hurricane damage.
Kim, J. M., Woods, P. K., Park, Y. J., Kim, T. H., Choi, J. S., and Son, K.: Predicting the hurricane damage ratio of commercial buildings by claim payout from Hurricane Ike, Nat. Hazards Earth Syst. Sci. Discuss., 1, 3449-3483, doi:10.5194/nhessd-1-3449-2013, 2013.