Rifan Ardianto, Prem Chhetri. Modeling Spatial-Temporal Dynamics of Urban Residential Fire Risk Using a Markov Chain Technique[J]. International Journal of Disaster Risk Science, 2019, 10(1): 57-73. doi: 10.1007/s13753-018-0209-2
Citation: Rifan Ardianto, Prem Chhetri. Modeling Spatial-Temporal Dynamics of Urban Residential Fire Risk Using a Markov Chain Technique[J]. International Journal of Disaster Risk Science, 2019, 10(1): 57-73. doi: 10.1007/s13753-018-0209-2

Modeling Spatial-Temporal Dynamics of Urban Residential Fire Risk Using a Markov Chain Technique

doi: 10.1007/s13753-018-0209-2
  • Available Online: 2021-04-26
  • This article applies a Markov chain method to compute the probability of residential fire occurrence based on past fire history. Fitted with the fire incidence data gathered over a period of 10 years in Melbourne, Australia, the spatially-integrated fire risk model predicts the likely occurrence of fire incidents using space and time as key model parameters. The mapped probabilities of fire occurrence across Melbourne show a city-centric spatial pattern where inner-city areas are relatively more vulnerable to a fire than outer suburbia. Fire risk reduces in a neighborhood when there is at least one fire in the last 1 month. The results show that the time threshold of reduced fire risk after the fire occurrence is about 2 months. Fire risk increases when there is no fire in the last 1 month within the third-order neighborhood (within 5 km). A fire that occurs within this distance range, however, has no significant effect on reducing fire risk level within the neighborhood. The spatial-temporal dependencies of fire risk provide new empirical evidence useful for fire agencies to effectively plan and implement geo-targeted fire risk interventions and education programs to mitigate potential fire risk in areas where and when they are most needed.
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