Static analysis-based rapid fire-following earthquake risk assessment method using simple building and GIS information

After the occurrences of large-scale earthquakes, secondary damage (e.g., fire following earthquake) can result in tremendous losses of life, properties, and buildings. To reduce these disaster risks, fire following earthquake assessment methods composed of ignition and fire-burned rate estimation models have been utilized. However, previous methods required for large amounts of building and GIS information, and complex modeling and analysis processes, leading to significant time consumption. This paper proposed a static analysis-based rapid fire following earthquake assessment method using simple information and implemented it in Pohang City, South Korea. Based on previous studies, the best-fit model for the ignition rate estimation was selected, and a cluster-based fire-burned rate estimation model was developed using simple building information (e.g., construction year, building occupancy, story, and total floor area) from the public building database (e.g., building registration data). For the fire-burned rate estimation model, fire-resistant structure types were defined using simple building information, and this was utilized to generate clusters of buildings at a regional level by comparing fire-spread distances for each fire-resistant structure type with adjacent distances among the buildings. This proposed method was applied to Pohang City, South Korea, and validated as follows: (1) the selected ignition rate model predicted similar ignition numbers to the actual reported number (actual number of ignitions = 4 vs. predicted number of ignitions = 3), and (2) the fire-burned rate model estimated fire-burned areas with a marginal difference compared to the fire spread simulation (fire-burned area using the proposed model = 13,703.6 m<sup>2</sup> vs. results of fire spread simulation = 16,800.0 m<sup>2</sup>, with an error of approximately 18%).

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Publication Details

Journal
Scientific Reports
Published
2024-09-14
DOI
https://doi.org/10.1038/s41598-024-72363-6
Citations
4
Primary Topic
Fire effects on ecosystems
Type
article
Field-Weighted Citation Impact
1.13
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article

Static analysis-based rapid fire-following earthquake risk assessment method using simple building and GIS information

Jae‐Do Kang, Jiuk Shin, Hye‐Won Kim, Taewook Kang et al.
4 citations
Scientific Reports
Fire effects on ecosystems
1.13
article

Static analysis-based rapid fire-following earthquake risk assessment method using simple building and GIS information

Jae‐Do Kang, Jiuk Shin, Hye‐Won Kim, Taewook Kang, Kihak Lee
article en
4 citations

Abstract

After the occurrences of large-scale earthquakes, secondary damage (e.g., fire following earthquake) can result in tremendous losses of life, properties, and buildings. To reduce these disaster risks, fire following earthquake assessment methods composed of ignition and fire-burned rate estimation models have been utilized. However, previous methods required for large amounts of building and GIS information, and complex modeling and analysis processes, leading to significant time consumption. This paper proposed a static analysis-based rapid fire following earthquake assessment method using simple information and implemented it in Pohang City, South Korea. Based on previous studies, the best-fit model for the ignition rate estimation was selected, and a cluster-based fire-burned rate estimation model was developed using simple building information (e.g., construction year, building occupancy, story, and total floor area) from the public building database (e.g., building registration data). For the fire-burned rate estimation model, fire-resistant structure types were defined using simple building information, and this was utilized to generate clusters of buildings at a regional level by comparing fire-spread distances for each fire-resistant structure type with adjacent distances among the buildings. This proposed method was applied to Pohang City, South Korea, and validated as follows: (1) the selected ignition rate model predicted similar ignition numbers to the actual reported number (actual number of ignitions = 4 vs. predicted number of ignitions = 3), and (2) the fire-burned rate model estimated fire-burned areas with a marginal difference compared to the fire spread simulation (fire-burned area using the proposed model = 13,703.6 m<sup>2</sup> vs. results of fire spread simulation = 16,800.0 m<sup>2</sup>, with an error of approximately 18%).

Scientific ReportsVol. 14(1)
Gyeongsang National University (KR), Sejong University (KR), The Seoul Institute (KR), National Disaster Management Research Institute (KR)
Climate action
Openalex Percentile: Top 23%
Fire effects on ecosystems
1.13
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