Recently, various types of natural damages have been caused by climate change. The term "damage caused by storm and flood" means any disaster caused by typhoon, flood, heavy rainfall, strong wind, wind wave, sea wave, tidal water, heavy snowfall, or other natural phenomena corresponding thereto [1
]. "Storm and flood insurance" refers to insurance that compensates for losses from property damage that occurs due to storm or flood damage [2
]. The Storm and Flood Insurance Act is a regulation for quick and fair compensation of losses from property damage that occurred due to storm and flood damage, and it was created with the goal of providing stabilization of the livelihood of citizens.
Moreover, according to the Countermeasures against Natural Disasters Act Article 2 (Definitions) and Article 21 (Creating and Using Various Disaster Maps), a "disaster map" means the drawings that indicate traces of flooding, flooding forecasts, and disaster-related information, etc. When looking at flood and storm insurance, there are many problems to be solved: (i) throughout the country, the same premium rates have been applied by city, district, neighborhood; (ii) the management of storm and flood damage risk maps and insurance management maps are insufficient and not reasonable; (iii) there is no system for continually and systematically managing a map for Storm and Flood Insurance Management and premium rates; (iv) there is a need for database-powered (GIS) record management that can support a variety of features such as statistical analysis of the map for Storm and Flood Insurance Management and risk maps.
In a domestic study, Shin shin [3
] analyzed the development progress on storm and flood damage in fire insurance and comprehensive homeowner’s insurance by studying natural disaster risk diversification and the government’s role. Lee et al. [4
] examined the risk classification systems for flood insurance in the United States and various European countries, and based on this, they proposed a plan for calculating graded rates by weighting flood areas by flood depth, which could be automatically applied to premium rates according to risk.
The National Emergency Management Agency (NEMA) [5
] performed research on operating a pilot project for calculating storm and flood premium rates by examining methods for calculating storm and flood premium rates. NEMA [6
] also studied a plan for creating a storm and flood management map and developed [7
] the teaching textbook for storm and flood insurance, including an overview of storm and flood insurance and the method of assessment of loss. Lee et al. [8
] suggested a calculation and verification method for the Natural Disaster Insurance Rate.
Overseas, Martini et al. [9
] showed that Atlas of Flood Maps includes examples of flood map data from 19 European countries, the United States, and Japan. This report mentions flood maps and insurance maps. The insurance maps are used for two purposes: for normal users to check if there is a possibility of flooding on their real estate, and for insurance companies to assess the actual risk of flooding. These maps show flood risk information too. This flood risk information is expressed as flood extent probability and the possibility of latent damage.
The insurance maps include CatNet [10
] and others, and the user interface screen of these maps contains flood risk information on European countries such as Belgium, Czech Republic, Germany, Italy, Hungary, Netherlands, Slovakia, and the United Kingdom, as well as Argentina, Israel, and the United States. To supplement this information, Swiss Re developed "Global Flood Zones."
The CatNet web service provides data on floods, earthquakes, tsunamis, storms, landslides, volcanoes, liquefaction, wildfire, climate change, climate data, etc. Figure 1
shows the CatNet web service providing information on flood areas (a) and earthquakes (b).
De Moel et al. [11
] examined the present state of flood risk maps and whether or not they used insurance maps. In Taiwan, Hsu et al. [12
] developed an integrated flood risk assessment model for real estate insurance companies that cover rainfall, flooding, vulnerability, and loss modules. In addition, FEMA [13
] introduced a flood insurance rate map. Shinjuku City [14
] published the flood risk for the city, including the flood range and recommended evacuation shelters based on rainfall characteristics and rainfall amount.
The time range for our research is from January 2015 to March 2016; the spatial range is Incheon metropolitan city; the scope of the study includes the generation of the Storm and Flood Insurance Management Map by combining premium rates with the risk of storm, flood, and snow.
In this research, we have suggested spatial information analysis techniques and procedures to process storm, flood, and snow damage risks and apply premium rates to ultimately produce a Storm and Flood Insurance Management Map.
2. Overview of Storm and Flood Insurance
Storm and Flood insurance was created to supplement the limitations in support systems for private property damage due to natural disasters, to revitalize the business insurance market for storm and flood damage, and to introduce a reward system according to the principle of self-responsibility.
The relevant risks include typhoons, floods, heavy rains, strong winds, wind volume, tsunami, heavy snow, and earthquakes. The relevant facilities are homes (including personal effects), greenhouses (including plastic houses), etc. According to the Building Act Article 2, Section 2
, Items 1 and 2, homes are buildings that are directly being used as residences out of all purpose-built buildings. Greenhouses are structures built for agriculture and forestry from among the "Standard Farming Houses" and "Disaster-resistant Standard Plastic Greenhouses" designated by the Ministry of Agriculture, Food and Rural Affairs.
Insurance products come in three types: storm and flood insurance product I, product II, and product III. Product I is for houses and greenhouses, a fixed payment; product II is for houses and tenant’s assets, a fixed payment; and product III is for apartments or condos, a reward commensurate with actual damages (excess construction). Products I and II are sold by dividing into 70%, 80%, and 90% compensation of the insured amount.
Storm and flood insurance is controlled by the Ministry of Public Safety and Security and supervised by the Financial Services Commission. Business operations are performed by five insurance companies, which are contracted with the Ministry of Public Safety and Security, and these are currently Dongbu Fire Insurance, Hyundai Marine and Fire Insurance, Samsung Fire Insurance, KB Insurance, and NH Property and Casualty Insurance.
below shows the layout of the system of operation that runs the actual insurance business.
3. Test Data Acquisition and Analysis
3.1. Study Area
The experiment region for this research is the Incheon metropolitan city, a city located in the northwest part of South Korea and comprising four administrative districts. Incheon metropolitan city, a famous port city, is one of South Korea’s six largest cities.
3.2. Data classification
To create an insurance management map, basic data and required data are needed. Basic data includes the digital elevation model (DEM), a building database, aerial photographs, etc. The required data are the risk and insurance premium rates. Table 1
shows data, data provider, and data format to build an insurance management map.
shows the basic data used in the Mapping for a Storm and Flood Insurance Management: (a) digital map, (b) satellite image, (c) digital elevation model.
In this research, flood risk (inner water, outer water), storm risk, and snow risk were gathered from other research organizations and through GIS analysis algorithms. Three risks and premium rates were combined on the DEM (10 m x10 m) to create the storm and flood insurance management map.
The flood risk map is produced with inner water and outer water maps. The inner water risk map is made using a digital topography map, and the outer water map is based on the existing flood risk map. Flood risk is graded into four classes by flood depth (m).
The storm risk maps are produced using the probability of failure (PF) maps by applying storm velocity maps to vulnerability functions. Then, storm risk is graded into 4 classes by PF. A storm velocity map is made using the wind velocity data from 70 weather centers that have tracked wind data for more than 20 years (1971–2015).
The snow risk map is produced using PF maps by applying snow depth maps to vulnerability functions (NEMA, 2009). Then, snow risk is graded into four classes by PF. The snow depth map is made using the snow depth data from 68 weather centers tracked during 1960–2015.
3.4. Premium Rate
The items considered when calculating premium rates include the mean damage ratio (MDR), premium rate calculation variables by risk grade, and weight of disaster causes for each grade. The final weight of disaster is calculated by averaging each weight of flood, storm, and snow damage shown in the statistical yearbook of natural disaster (2012–2014), insurance money of storm and flood insurance (2006–2014), and the number of payments of storm and flood insurance (2006–2014). In most districts of Incheon metropolitan city, the average weight of damage is 90–100 (flood), 0–6 (storm), 0–4 (snow), except for Bupyeong-gu, Ongjin-gun, Ganghwa-gun.
shows the main items considered when calculating premium rates. The calculation of the premium rate in this study is based on the previous research [8
], which was performed by the same research team.
This study used GIS analysis techniques to analyze risk and create a Storm and Flood Insurance Management map. The research results led us to the following conclusions.
To produce risks, inner water-, outer water-, storm-, and snow risks were produced based on a 10 m x 10 m digital elevation model grid. The flood risk was used as the standard risk when creating the insurance management maps, and the storm- and snow risks were used as weights for raising or discounting the cost when calculating the premium rates. To create risks, ArcGIS’ Raster calculator, grid classification, and spatial join functions were used, and Excel’s pivot function was used to calculate the flood areas by flood depth and premium rates. To handle an increasing amount of risk and premium rate data for creating the insurance management maps, we used the ArcGIS modeler to design an algorithm for automatically calculating risk and developing its execution program.
In the future, the Storm and Flood Insurance Management map can be used as the key information source for making scientific natural disaster prevention and response policies using regional storm and flood risk maps, for reasonable calculation and application of premium rates, for choosing regular dangerous areas for storm and flood damage, and promoting prevention policies.