Spatial econometrics analysis of fire occurrence according to type of facilities
- Authors
- Seo, M.S.; Yoo, H.H.
- Issue Date
- 2019
- Publisher
- Korean Society of Surveying
- Keywords
- Facilities; Fire; Multiple regression analysis; OLS regression analysis; Spatial autocorrelation analysis
- Citation
- Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, v.37, no.3, pp.129 - 141
- Indexed
- SCOPUS
KCI
- Journal Title
- Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
- Volume
- 37
- Number
- 3
- Start Page
- 129
- End Page
- 141
- URI
- https://scholarworks.bwise.kr/gnu/handle/sw.gnu/10672
- DOI
- 10.7848/ksgpc.2019.37.3.129
- ISSN
- 1598-4850
- Abstract
- In recent years, fast growing cities in Korea are showing signs of being vulnerable to more disasters as their population and facilities increase and intensify. In particular, fire is one of the most common disasters in Korea's cities, along with traffic accidents. Therefore, in this study, we analyze what type of factors affect the fire that threatens urban people. Fire data were acquired for 10 years, from 2007 to 2017, in Jinju, Korea. Spatial distribution pattern of fire occurrence in Jinju was assessed through the spatial autocorrelation analysis. First, spatial autocorrelation analysis was carried out to grasp the spatial distribution pattern of fire occurrence in Jinju city. In addition, correlation and multiple regression analysis were used to confirm spatial dependency and abnormality among factors. Based on this, OLS (Ordinary Least Square) regression analysis was performed using space weighting considering fire location and spatial location of each facility. As a result, First, LISA (Local Indicator of Spatial Association) analysis of the occurrence of fire in Jinju shows that the most central commercial area are fire department, industrial area, and residential area. Second, the OLS regression model was analyzed by applying spatial weighting, focusing on the most derived factors of multiple regression analysis, by integrating population and social variables and physical variables. As a result, the second kind of neighborhood living facility showed the highest correlation with the fire occurrence, followed by the following in the order of single house, sales facility, first type of neighborhood living facility, and number of households. The results of this study are expected to be useful for analyzing the fire occurrence factors of each facility in urban areas and establishing fire safety measures. ? 2019 Korean Society of Surveying. All rights reserved.
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