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Open AccessArticle

A Study on Storm and Flood Insurance Management Mapping: Case Study of Incheon Metropolitan City

by Insu Lee 1, Junseok Lee 2 and Sungil Ham 1,*
1
Korea Land and Geospatial Informatix Corporation, Wanju-gun, Jeollabuk-do 55365, Korea
2
National Institute of Ecology, Seochon-gun, Jeollabuk-do 33657, Korea
*
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2019, 8(11), 485; https://doi.org/10.3390/ijgi8110485
Received: 26 September 2019 / Revised: 21 October 2019 / Accepted: 28 October 2019 / Published: 29 October 2019
In this research, we have used spatial information analysis techniques and procedures to process storm, flood, and snow damage risks, and apply premium rates to produce a Storm and Flood Insurance Management Map. To calculate risk, we used ArcGIS’s main features to overlay, integrate, and classify data. Moreover, we designed an ArcGIS Model Builder program to process very large amounts of risk data quickly and accurately. Excel’s pivot feature was used to calculate areas and premium rates according to flood depth. In the case of Incheon metropolitan city, the average risk was 2.85 on the 4-level scale, which lies between "alert" and "danger" and corresponds to the 1st of the 4 premium rate grades. In particular, there were high risks and high premium rates in areas around ports, ocean beaches, and beaches connected to rivers. We expect that this insurance management map created using spatial information analysis techniques will provide useful data for scientific natural disaster response and prevention planning, rational insurance rate calculation and application, and promotion of policies, which identify and prevent areas at risk for frequent storm and flood damage. View Full-Text
Keywords: insurance; storm damage; flood damage; snow damage; spatial information insurance; storm damage; flood damage; snow damage; spatial information
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Lee, I.; Lee, J.; Ham, S. A Study on Storm and Flood Insurance Management Mapping: Case Study of Incheon Metropolitan City. ISPRS Int. J. Geo-Inf. 2019, 8, 485.

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