Skip to main content
Log in

Correlation Between Fire Attendance Time and Burned Area Based on Fire Statistical Data of Japan and China

  • Published:
Fire Technology Aims and scope Submit manuscript

Abstract

This paper studies the statistical law of fire attendance time and analyzes the correlation between fire attendance time and burned area based on the urban fire statistical data of Japan from 1995 to 2003 and in Jiangxi Province (China) from 2000 to 2010. The frequency of fire attendance time was better modeled by a lognormal distribution, and the probability density function for both Japan and China were formulated. The expectation of the lognormal distribution reflects the average level of fire attendance time. This study is the first to report that the distribution law of the burned area in each fire attendance time observes power function. And they are valid within 12 min of fire attendance time. The larger absolute value of the exponent of the power law function subjects to the larger probability of small-scale fire and the smaller probability of large-scale fire. It decreases as the fire attendance time increases. This indicates that the fire control ability becomes poor with longer fire attendance time.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
Figure 9
Figure 10
Figure 11
Figure 12
Figure 13

Similar content being viewed by others

Abbreviations

t a :

Fire attendance time (FAT), the difference between reach time and detection time in one sample of fire statistical data

x c :

Lognormal distribution expectations

w :

Coefficient of lognormal distribution

R square (R 2):

Fitting relation coefficient

A(t a):

Coefficient of the burned area distribution law

B(t a):

Coefficient of the burned area distribution law

X :

Discrete random variable of the burned area

x i :

The possible values of X, i = 1, 2, 3……2,000

References

  1. Bureau of Fire Protection (2008) Fire protection law of the People’s Republic of China. BFP, China

  2. Badri MA, Mortagy AK, Alsayed CA (1998) A multi-objective model for locating fire stations. Eur J Oper Res 110(2):243–260. doi:10.1016/s0377-2217(97)00247-6

    Article  MATH  Google Scholar 

  3. ReVelle CS, Eiselt HA (2005) Location analysis: a synthesis and survey: invited review. Eur J Oper Res 165:1–19. doi:10.1016/j.ejor.2003.11.032

    Article  MATH  MathSciNet  Google Scholar 

  4. Chuan-liang JIA, Hong CHI, Lei JI (2005) The allocation model of fire resource based on multistage fire protection process. Syst Eng 23:12–15

    Google Scholar 

  5. Ji-ping ZHU, Yong-hua GOU, Guang-xuan LIAO (2002) Optimal path of dispatch in urban fire fighting. Fire Saf Sci 11:201–205

    Google Scholar 

  6. Liu N, Huang B, Chandramouli M (2006) Optimal siting of fire stations using GIS and ANT algorithm. J Comput Civil Eng 20:361–369. doi: 10.1061/(ASCE)0887-3801(2006)20:5(361)

    Article  Google Scholar 

  7. Jun W (2006) Study on the optimizing method and technique of fire station planning. Fire Sci Technol 25:100–102

    Google Scholar 

  8. Sardqvist S, Holmstedt G (2000) Correlation between firefighting operation and fire area: analysis of statistics. Fire Technol 36(2):109–130. doi:10.1023/A:1015450308130

    Article  Google Scholar 

  9. Holborn PG, Nolan PF, Golt J (2004) An analysis of fire sizes, fire growth rates and times between events using data from fire investigations. Fire Saf J 39:481–524. doi:10.1016/j.firesaf.2004.05.002

    Article  Google Scholar 

  10. Challands N (2010) The relationships between fire service response time and fire outcomes. Fire Technol 46:665–676. doi:10.1007/s10694-009-0111-y

    Article  Google Scholar 

  11. Chen PENG, Ji-ping ZHU, Kohyu SATOH, Bing-hua LI (2010) Frequency distribution of the first response time of firefighting. Fire Saf Sci 19(1):33–37

    Google Scholar 

  12. Disaster Prevention Administrative Institute (2010) Handle book of Japan fire report. Tokyo Law, Tokyo

    Google Scholar 

  13. Malamud BD, Morein G, Turcotte DL (1998) Forest fires: an example of self-organized critical behavior. Science 281:1840–1842. doi:10.1126/science.281.5384.1840

    Article  Google Scholar 

  14. Song W, Fan W, Wang B (2001) Self-organized critical of forest fire in China. Ecol Model 45(1):61–68. doi:10.1016/S0304-3800(01)00383-0

    Article  Google Scholar 

  15. Ricotta C et al (1999) The flaming sandpile: self-organized criticality and wildfires. Ecol Model 119(1):73–77. doi:10.1016/S0304-3800(99)00057-5

    Article  Google Scholar 

  16. Schenk K, Drossel B, Clar S, Schwabl F (2000) Finite-size effects in the self-organized critical forest-fire model. Eur Phys J B 15:177–185. doi:10.1007/s100510051113

    Article  Google Scholar 

  17. Wang JH, Xie S, Sun JH (2010) Self-organized criticality judgment and extreme statistics analysis of major urban fires. Chin Sci Bull 56(6):567–572. doi:10.1007/s11434-010-4062-y

    Article  Google Scholar 

  18. Weiguo S, Jian W, Kohyu S, Weicheng F (2006) Three types of power-law distribution of forest fire in Japan. Ecol Model 196:527–532. doi:10.1016/j.ecolmodel.2006.02.033

    Article  Google Scholar 

  19. Weiguo S, Zheng HZ,Wang J, Ma J, Satoh W (2007) Weather-driven indicative of spatiotemporal power laws. Phys Rev E 016109-1–016109-5. doi:10.1103/PhysRevE.75.016109

Download references

Acknowledgments

The author would like to express their thanks to National Research Institute of Fire and Disaster of Japan and Fire Bureau of Jiangxi Province (China) for their support in carrying out all the fire data and the investigators who collected data. This work was sponsored by the National Natural Science Foundation of China under Grants No. 30972380, the Major Research Plan of the National Natural Science Foundation of China under Grants No. 91024027, the National Key Technology R&D Program of China under Grants No. 2011BAK07B01, and the Fundamental Research Funds for the Central Universities under Grants No. WK2320000010.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jiping Zhu.

Appendix

Appendix

Proportion of the data set of all urban fire incidents used at each stage of this analysis (Figures 14 and 15).

Figure 14
figure 14

Proportion of the data set from Japan

Figure 15
figure 15

Proportion of the data set from Jiangxi Province (China)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Lu, L., Peng, C., Zhu, J. et al. Correlation Between Fire Attendance Time and Burned Area Based on Fire Statistical Data of Japan and China. Fire Technol 50, 851–872 (2014). https://doi.org/10.1007/s10694-012-0306-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10694-012-0306-5

Keywords

Navigation