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Time-scaling properties of city fires

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  • Telesca, Luciano
  • Song, Weiguo

Abstract

Time-scaling scale-invariant approaches have been used to feature the temporal distribution of city fire sequences recorded in the city of AnShan (China). Our findings reveal that the point process of the city fires is a fractal process with a high degree of time-clusterization of the events. The time-clustering phenomenon is visible for timescales larger than few hours. Furthermore, the fire process tends to be less time-clusterized with the increase of the loss. The application of multifractal detrended fluctuation analysis to the series of city-fires has revealed that the sequence is dynamically heterogeneous due to the different long-range time correlation properties for small and large interevent fluctuations.

Suggested Citation

  • Telesca, Luciano & Song, Weiguo, 2011. "Time-scaling properties of city fires," Chaos, Solitons & Fractals, Elsevier, vol. 44(7), pages 558-568.
    • Handle: RePEc:eee:chsofr:v:44:y:2011:i:7:p:558-568
    DOI: 10.1016/j.chaos.2011.05.001
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    References listed on IDEAS

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    1. Luciano Telesca, 2007. "Time-clustering of natural hazards," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 40(3), pages 593-601, March.
    2. Telesca, Luciano & Lovallo, Michele & Lapenna, Vincenzo & Macchiato, Maria, 2007. "Long-range correlations in two-dimensional spatio-temporal seismic fluctuations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 377(1), pages 279-284.
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    4. Zheng, Hongyang & Song, Weiguo & Wang, Jian, 2008. "Detrended fluctuation analysis of forest fires and related weather parameters," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(8), pages 2091-2099.
    5. Zheng, Hongyang & Song, Weiguo & Satoh, Kohyu, 2010. "Detecting long-range correlations in fire sequences with Detrended fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(4), pages 837-842.
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    7. Telesca, Luciano & Lovallo, Michele, 2007. "Non-random components in aircraft accidents time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 381(C), pages 407-410.
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    10. Havlin, S. & Buldyrev, S.V. & Bunde, A. & Goldberger, A.L. & Ivanov, P.Ch. & Peng, C.-K. & Stanley, H.E., 1999. "Scaling in nature: from DNA through heartbeats to weather," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 273(1), pages 46-69.
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    2. Yuan, Ying & Zhuang, Xin-tian & Liu, Zhi-ying & Huang, Wei-qiang, 2012. "Time-clustering behavior of sharp fluctuation sequences in Chinese stock markets," Chaos, Solitons & Fractals, Elsevier, vol. 45(6), pages 838-845.
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    4. Yuan, Ying & Zhuang, Xin-tian & Liu, Zhi-ying & Huang, Wei-qiang, 2014. "Analysis of the temporal properties of price shock sequences in crude oil markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 394(C), pages 235-246.

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