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Hurricane Loss Analysis Based on the Population-Weighted Index
This paper discusses different measures for quantifying regional hurricane loss. The main measures used in the past are normalized percentage loss and dollar value loss. In this research, we show that these measures are useful but may not properly reflect the size of the population influenced by hur...
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Published in: | Frontiers in built environment 2017-08, Vol.3 |
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Main Authors: | , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | This paper discusses different measures for quantifying regional hurricane loss. The main measures used in the past are normalized percentage loss and dollar value loss. In this research, we show that these measures are useful but may not properly reflect the size of the population influenced by hurricanes. A new loss measure is proposed that reflects the hurricane impact on people occupying the structure. For demonstrating the differences among these metrics, regional loss analysis was conducted for Florida. The regional analysis was composed of three modules: the hazard module stochastically modeled the wind occurrence in the region; the vulnerability module utilized vulnerability functions developed in this research to calculate the loss; and the financial module quantified the hurricane loss. In the financial module, we calculated three loss metrics for certain region. The first metric is the average annual loss (AAL) which represents the expected loss per year in percentage. The second is the average annual dollar loss which represents the expected dollar amount loss per year. The third is the average annual population-weighted loss (AAPL)—a new measure proposed in this research. Compared with the AAL, the AAPL reflects the number of people influenced by the hurricane. The advantages of the AAPL are illustrated using three different analysis examples: (1) conventional regional loss analysis, (2) mitigation potential analysis, and (3) forecasted future loss analysis due to the change in population. |
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ISSN: | 2297-3362 2297-3362 |
DOI: | 10.3389/fbuil.2017.00046 |