DOI QR코드

DOI QR Code

Spatial Econometrics Analysis of Fire Occurrence According to Type of Facilities

시설물 유형에 따른 화재 발생의 공간 계량 분석

  • Seo, Min Song (BK21+, Dept. of Urban Engineering, Gyeongsang National University) ;
  • Yoo, Hwan Hee (BK21+, ERI, Dept. of Urban Engineering, Gyeongsang National University)
  • Received : 2019.05.24
  • Accepted : 2019.06.27
  • Published : 2019.06.30

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.

최근 급속도로 성장하는 도시에는 많은 인구와 시설물들이 증가하고 집중이 심화함에 따라 재해와 재난에 취약함을 나타낸다. 특히, 화재는 우리나라의 도시 내에서 교통사고와 더불어 가장 많이 발생하는 재해 중 하나로 많은 인명 및 재산피해를 준다. 따라서 본 연구에서는 화재 발생에 대한 영향요인을 분석하기 위해 진주시를 대상으로 2007년부터 2017년까지 10년간 화재데이터를 취득하였다. 먼저 공간 자기 상관성 분석을 시행하여 진주시 화재 발생의 공간 분포 패턴을 파악한 후, 상관관계 및 다중 회귀 분석을 통해 인문 사회 요인과 물리적 요인 간의 공간적 종속성 및 비정상성을 확인하였고 이를 토대로 화재 발생 위치와 각 요인별 위치를 고려하여 공간 가중치를 활용한 OLS 회귀 분석을 실시하였다. 그 결과로 첫째, 진주시 화재 발생의 LISA분석 결과 화재 발생 빈도가 높은 용도지역은 중심상업지역, 공업지역, 주거지역 순으로 나타났다. 둘째, 인구 사회적 변수 및 물리적 변수를 통합하여 다중회귀분석의 최종 모형으로 도출된 요인들을 중심으로 공간가중치를 적용하여 OLS회귀모형을 분석한 결과 제2종 근린생활시설이 화재 발생과 가장 높은 상관성을 보였으며 다음으로 단독주택, 판매시설, 제1종 근린생활시설, 가구수의 순으로 상관성이 있는 것으로 분석되었다. 이러한 연구 결과를 통해 도시 지역의 시설물별 화재 발생 요인을 분석하고 화재 안전대책을 수립하는데 유용한 자료로 활용될 것으로 예상된다.

Keywords

GCRHBD_2019_v37n3_129_f0001.png 이미지

Fig. 1. Fire situation of Jinju city(2007-2017)

GCRHBD_2019_v37n3_129_f0002.png 이미지

Fig. 2. Global Moran's I Index

GCRHBD_2019_v37n3_129_f0003.png 이미지

Fig. 3. Jinju city LISA analysis index

GCRHBD_2019_v37n3_129_f0004.png 이미지

Fig. 4. Normal distribution histogram of residuals

GCRHBD_2019_v37n3_129_f0005.png 이미지

Fig. 5. Normal P-P chart of standardization residuals

GCRHBD_2019_v37n3_129_f0006.png 이미지

Fig. 6. Scatter plot of residuals and forecasts

Table 1. Number of Each Census Output Area

GCRHBD_2019_v37n3_129_t0001.png 이미지

Table 2. Number of facilities in Jinju city

GCRHBD_2019_v37n3_129_t0002.png 이미지

Table 3. Human and social variables

GCRHBD_2019_v37n3_129_t0003.png 이미지

Table 4. Physical variables

GCRHBD_2019_v37n3_129_t0004.png 이미지

Table 5. Correlation coefficient between fire occurrence and human and social variables

GCRHBD_2019_v37n3_129_t0005.png 이미지

Table 6. Correlation coefficient between fire occurrence and Physical variables

GCRHBD_2019_v37n3_129_t0006.png 이미지

Table 7. Human·Social·Physical variable regression analysis model summary

GCRHBD_2019_v37n3_129_t0007.png 이미지

Table 8. Human·Social·Physical variable regression analysis model summary

GCRHBD_2019_v37n3_129_t0008.png 이미지

Table 9. OLS analysis result

GCRHBD_2019_v37n3_129_t0009.png 이미지

References

  1. Bae, G.H. (2016), Spatial Distribution Analysis and Risk Evaluation of Fire Occurrence in Jinju-si, Gyeongsang National University, Jinju, Korea, 62p.
  2. Baller, R.D., Anselin L., Messener S.F., Deane, G., and Hawkins, D.F. (2001), Strutural Covariates of U.S County Homicide Rates : Incorporating Spatial Effects, Criminologh, Vol. 39, No. 3, pp. 561-588. https://doi.org/10.1111/j.1745-9125.2001.tb00933.x
  3. Jeo, A.L. (2017), A Study on Factors Affecting Women's Space Utilization Through Floating Population Analysis, Master's thesis, Gachon University, Gachon, Korea, 95p.
  4. James, P., Lesage, R., and Kelley, P. (2008), Spatial Econometric Modeling of Origi-Destination Flows, Journal of Regional Science, Vol. 48, No. 5, pp. 941-967. https://doi.org/10.1111/j.1467-9787.2008.00573.x
  5. Kim, H.J. (2009), A Study on Spatial Characteristics in Fire Outbreak Using GIS, Master' s thesis, Korea National University of Education, Chongju, Korea, 90p.
  6. Kim, M.I., Kwak, H.B., Lee, W.K., Won, M.S., and Koo, K.S. (2011), Study on Regional Spatial Autocorrelation of Forest Fire Occurrence in Korea, The Korean Society for Geospatial Information System, Vol. 19, No. 2, pp. 29-37. (in Korean with English abstract)
  7. Kang, Y.O. and Park, M.R. (2005), Guidelines for the Construction of Vulnerability Map of Fire in Seoul, Conference of Korean Society for Geospatial Information System, Korean Society for Geospatial Information System, 14 October, Seoul, Korea, pp. 195-200.
  8. Kim, J.T. and Um, J.S. (2007), The Urban Fire Prediction Mapping Technique based on GIS Spatial Statistics, Fire Science and Engineering, Vol. 21, No. 2, pp. 14-25. (in Korean with English abstract)
  9. Lee, S.Y. (2010), A Study on Spatial Distribution in Fire, Emergency, Rescue Outbreaks Using GIS and Dispatch System Analysis, Master' s thesis, Korea National University of Education, Chongju, Korea, 109p.
  10. Lee, H.Y. and No, S.C. (2013), Advanced Statistical Analysis, Munu, Korea.
  11. Shin, J.D., Jeong, S.H., Kim, M.S., and Kim, H.J. (2012), Analysis of Fire Risk with Building Use Type Using Statistical Data, Korean Seociety of Hazard Mitigation, Vol. 12, No. 4, pp. 107-114. (in Korean with English abstract)
  12. Yeon, G.H. (2016), The Analysis about Distributive Characteristics and Influential factors of Urban Fires -Focusing on Cheongju city-, Master's thesis, Chungbuk National University, Chungbuk, Korea, 134p.