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The increasing occurrence of natural disasters and their related damage have led to a growing demand for models that predict financial loss. Although considerable research on the financial losses related to natural disasters has found significant predictors, there has been a lack of comprehensive study that addresses the relationship among vulnerabilities, natural disasters, and the economic losses of individual buildings. This study identifies the vulnerability indicators for hurricanes to establish a metric to predict the related financial loss. We classify hurricane-prone areas by highlighting the spatial distribution of losses and vulnerabilities. This study used a Geographical Information System (GIS) to combine and produce spatial data and a multiple regression method to establish a wind damage prediction model. As the dependent variable, we used the value of the Texas Windstorm Insurance Association (TWIA) claim payout divided by the appraised values of the buildings to predict real economic loss. As independent variables, we selected a hurricane indicator and built environment vulnerability indicators. The model we developed can be used by government agencies and insurance companies to predict hurricane wind damage.

As the need for environmental certification systems grows, Leadership in Energy and Environmental Design for New Construction (LEED-NC) is being widely adopted in the US to evaluate the environmental performance of buildings. However, no research has been conducted to investigate its economic impact on appraised land value. The objectives of this study are to quantify the impact of the LEED-NC Credit Alternative Transportation: Public Transportation Access (PTA) in the sustainable sites category on appraised land value and to develop a regression model that predicts the appraised unit value of parcels. San Francisco County was chosen because of its well-organized transportation systems. First, a LEED-NC map was created to identify PTA-qualified parcels. Second, sample parcels were randomly selected. Last, Pearson's correlation analysis, one-way ANOVA, and multiple linear regression analysis were sequentially performed. The results of this study indicated that the LEED PTA criteria are significant factors associated with an increase in the appraised unit value of parcels within San Francisco County. The findings of this study can encourage real-estate developers to site their projects according to the LEED-NC PTA criteria. [ABSTRACT FROM AUTHOR]