Modeling Spatial–Temporal Dynamics of Urban Residential Fire Risk Using a Markov Chain Technique
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摘要
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 last1 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.
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 last1 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.
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 last1 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.
引文
ABS(Australian Bureau of Statistics).2016.Australian demographic statistics,Mar 2018.http://www.abs.gov.au/ausstats/abs@.nsf/mf/3101.0.Accessed 2 Mar 2018.
Bai,J.,and P.Wang.2011.Conditional Markov chain and its application in economic time series analysis.Journal of Applied Econometrics 26(5):715-734.
Billingsley,P.1961.Statistical methods in Markov chains.The Annals of Mathematical Statistics 32(1):12-40.
Blum,E.H.1970.Fire service:Challenge to modern management.New York:Rand Institute.
Castan?eda,L.B.,V.Arunachalam,and S.Dharmaraja.2012.Introduction to probability and stochastic processes with applications.Hoboken,NJ:Wiley.
Ceyhan,E.,K.Ertug?ay,and S.Du¨zgu¨n.2013.Exploratory and inferential methods for spatio-temporal analysis of residential fire clustering in urban areas.Fire Safety Journal 58:226-239.
Cheng,H.,and G.V.Hadjisophocleous.2009.The modeling of fire spread in buildings by Bayesian network.Fire Safety Journal44(6):901-908.
Cheng,H.,and G.V.Hadjisophocleous.2011.Dynamic modeling of fire spread in building.Fire Safety Journal 46(4):211-224.
Chhetri,P.,J.Corcoran,R.J.Stimson,and R.Inbakaran.2010.Modelling potential socio-economic determinants of building fires in south east Queensland.Geographical Research 48(1):75-85.
Ching,W.K.,and M.Ng.2006.Markov chains:Models,algorithms and applications.Boston,MA:Springer.
Chuvieco,E.,I.Aguado,M.Yebra,H.Nieto,J.Salas,M.P.Mart?′n,L.Vilar,J.Mart?′nez,et al.2010.Development of a framework for fire risk assessment using remote sensing and geographic information system technologies.Ecological Modelling 221(1):46-58.
C?inlar,E.2011.Probability and stochastics.New York:Springer.
Clark,A.,J.Smith,and C.Conroy.2015.Domestic fire risk:Anarrative review of social science literature and implications for further research.Journal of Risk Research 18(9):1113-1129.
Clode,D.2010.Coping with fire:Psycological preparedness for bushfires.A report prepared for the Country Fire Authority.https://doi.org/10.13140/2.1.1384.8643.
Corcoran,J.,and G.Higgs.2013.Special issue on spatial analytical approaches in urban fire management.Fire Safety Journal62(A):1-2.
Corcoran,J.,G.Higgs,and T.Anderson.2013.Examining the use of a geodemographic classification in an exploratory analysis of variations in fire incidence in South Wales,UK.Fire Safety Journal 62(A):37-48.
Corcoran,J.,G.Higgs,C.Brunsdon,and A.Ware.2007a.The use of comaps to explore the spatial and temporal dynamics of fire incidents:A case study in South Wales,United Kingdom.The Professional Geographer 59(4):521-536.
Corcoran,J.,G.Higgs,C.Brunsdon,and A.Ware.2007b.The use of spatial analytical techniques to explore patterns of fire incidence:A South Wales case study.Computers,Environment and Urban Systems 31(6):623-647.
Corcoran,J.,G.Higgs,and A.Higginson.2011.Fire incidence in metropolitan areas:A comparative study of Brisbane(Australia)and Cardiff(United Kingdom).Applied Geography 31(1):65-75.
Dittmar,H.,and G.Ohland.2012.The new transit town:Best practices in transit-oriented development.Washington,DC:Island Press.
Duncanson,M.,A.Woodward,and P.Reid.2002.Socioeconomic deprivation and fatal unintentional domestic fire incidents in New Zealand 1993-1998.Fire Safety Journal 37(2):165-179.
Goodsman,R.W.,F.Mason,and A.Blythe.1987.Housing factors and fires in two metropolitan boroughs.Fire Safety Journal12(1):37-50.
Hagerstrand,T.1968.Innovation diffusion as a spatial process.Chicago:University of Chicago Press.
Hanea,D.,and B,Ale.2009.Risk of human fatality in building fires:A decision tool using Bayesian networks.Fire Safety Journal44(5):704-710.
Iosifescu,M.,N.Limnios,and G.Opris?an.2010.Introduction to stochastic models.Hoboken,NJ:Wiley.
Jennings,C.R.2013.Social and economic characteristics as determinants of residential fire risk in urban neighborhoods:A review of the literature.Fire Safety Journal 62(A):13-19.
Leth,P.,M.Gregersen,and S.Sabroe.1998.Fatal residential fire accidents in the municipality of Copenhagen,1991-1996.Preventive Medicine 27(3):444-451.
Lin,Y.S.2005.Estimations of the probability of fire occurrences in buildings.Fire Safety Journal 40(8):728-735.
Ma,F.A.2015.Information communication.San Rafael,California:Morgan&Claypool Publishers.
Matellini,D.B,A.D.Wall,I.D.Jenkinson,J.Wang,and R.Pritchard.2013.Modelling dwelling fire development and occupancy escape using Bayesian network.Reliability Engineering&System Safety 114:75-91.
McGee,T.K.,B.L.McFarlane,and J.Varghese.2009.An examination of the influence of hazard experience on wildfire risk perceptions and adoption of mitigation measures.Society and Natural Resources 22(4):308-323.
Pinsky,M.,and S.Karlin.2011.An introduction to stochastic modeling,4th edn.Boston:Academic Press.
Plough,A.,and S.Krimsky.1987.The emergence of risk communication studies:Social and political context.Science,Technology,and Human Values 12(3/4):4-10.
Pries,L.2005.Configurations of geographic and societal spaces:Asociological proposal between‘methodological nationalism’and the‘spaces of flows’.Global Networks 5(2):167-190.
Reed,M.,A.C.Evely,G.Cundill,I.R.A.Fazey,J.Glass,A.Laing,J.Newig,B.Parrish,et al.2010.What is social learning?Ecology and Society 15(4):response 1.
Rhodes,A.,and S.Reinholtd.1998.Beyond technology:A holistic approach to reducing residential fire fatalities.Australian Journal of Emergency Management 13(1):39.
Rogers,E.M.1962.Diffusion of innovations.New York:Free Press.
Rohde,D.,J.Corcoran,and P.Chhetri.2010.Spatial forecasting of residential urban fires:A bayesian approach.Computers,Environment and Urban Systems 34(1):58-69.
Scherer,C.W.,and H.Cho.2003.A social network contagion theory of risk perception.Risk Analysis 23(2):261-267.
Searle,G.,S.Darchen,and S.Huston.2014.Positive and negative factors for transit oriented development:Case studies from Brisbane,Melbourne and Sydney.Urban Policy and Research32(4):437-457.
Simonsen,K.1996.What kind of space in what kind of social theory?Progress in Human Geography 20(4):494-512.
Spatenkova′,O.,and K,Virrantaus.2013.Discovering spatio-temporal relationships in the distribution of building fires.Fire Safety Journal 62(A):49-63.
Wuschke,K.,J.Clare,and L.Garis.2013.Temporal and geographic clustering of residential structure fires:A theoretical platform for targeted fire prevention.Fire Safety Journal 62(A):3-12.
Xin,J.,and C.Huang.2013.Fire risk analysis of residential buildings based on scenario clusters and its application in fire risk management.Fire Safety Journal 62(A):72-78.
Bai,J.,and P.Wang.2011.Conditional Markov chain and its application in economic time series analysis.Journal of Applied Econometrics 26(5):715-734.
Billingsley,P.1961.Statistical methods in Markov chains.The Annals of Mathematical Statistics 32(1):12-40.
Blum,E.H.1970.Fire service:Challenge to modern management.New York:Rand Institute.
Castan?eda,L.B.,V.Arunachalam,and S.Dharmaraja.2012.Introduction to probability and stochastic processes with applications.Hoboken,NJ:Wiley.
Ceyhan,E.,K.Ertug?ay,and S.Du¨zgu¨n.2013.Exploratory and inferential methods for spatio-temporal analysis of residential fire clustering in urban areas.Fire Safety Journal 58:226-239.
Cheng,H.,and G.V.Hadjisophocleous.2009.The modeling of fire spread in buildings by Bayesian network.Fire Safety Journal44(6):901-908.
Cheng,H.,and G.V.Hadjisophocleous.2011.Dynamic modeling of fire spread in building.Fire Safety Journal 46(4):211-224.
Chhetri,P.,J.Corcoran,R.J.Stimson,and R.Inbakaran.2010.Modelling potential socio-economic determinants of building fires in south east Queensland.Geographical Research 48(1):75-85.
Ching,W.K.,and M.Ng.2006.Markov chains:Models,algorithms and applications.Boston,MA:Springer.
Chuvieco,E.,I.Aguado,M.Yebra,H.Nieto,J.Salas,M.P.Mart?′n,L.Vilar,J.Mart?′nez,et al.2010.Development of a framework for fire risk assessment using remote sensing and geographic information system technologies.Ecological Modelling 221(1):46-58.
C?inlar,E.2011.Probability and stochastics.New York:Springer.
Clark,A.,J.Smith,and C.Conroy.2015.Domestic fire risk:Anarrative review of social science literature and implications for further research.Journal of Risk Research 18(9):1113-1129.
Clode,D.2010.Coping with fire:Psycological preparedness for bushfires.A report prepared for the Country Fire Authority.https://doi.org/10.13140/2.1.1384.8643.
Corcoran,J.,and G.Higgs.2013.Special issue on spatial analytical approaches in urban fire management.Fire Safety Journal62(A):1-2.
Corcoran,J.,G.Higgs,and T.Anderson.2013.Examining the use of a geodemographic classification in an exploratory analysis of variations in fire incidence in South Wales,UK.Fire Safety Journal 62(A):37-48.
Corcoran,J.,G.Higgs,C.Brunsdon,and A.Ware.2007a.The use of comaps to explore the spatial and temporal dynamics of fire incidents:A case study in South Wales,United Kingdom.The Professional Geographer 59(4):521-536.
Corcoran,J.,G.Higgs,C.Brunsdon,and A.Ware.2007b.The use of spatial analytical techniques to explore patterns of fire incidence:A South Wales case study.Computers,Environment and Urban Systems 31(6):623-647.
Corcoran,J.,G.Higgs,and A.Higginson.2011.Fire incidence in metropolitan areas:A comparative study of Brisbane(Australia)and Cardiff(United Kingdom).Applied Geography 31(1):65-75.
Dittmar,H.,and G.Ohland.2012.The new transit town:Best practices in transit-oriented development.Washington,DC:Island Press.
Duncanson,M.,A.Woodward,and P.Reid.2002.Socioeconomic deprivation and fatal unintentional domestic fire incidents in New Zealand 1993-1998.Fire Safety Journal 37(2):165-179.
Goodsman,R.W.,F.Mason,and A.Blythe.1987.Housing factors and fires in two metropolitan boroughs.Fire Safety Journal12(1):37-50.
Hagerstrand,T.1968.Innovation diffusion as a spatial process.Chicago:University of Chicago Press.
Hanea,D.,and B,Ale.2009.Risk of human fatality in building fires:A decision tool using Bayesian networks.Fire Safety Journal44(5):704-710.
Iosifescu,M.,N.Limnios,and G.Opris?an.2010.Introduction to stochastic models.Hoboken,NJ:Wiley.
Jennings,C.R.2013.Social and economic characteristics as determinants of residential fire risk in urban neighborhoods:A review of the literature.Fire Safety Journal 62(A):13-19.
Leth,P.,M.Gregersen,and S.Sabroe.1998.Fatal residential fire accidents in the municipality of Copenhagen,1991-1996.Preventive Medicine 27(3):444-451.
Lin,Y.S.2005.Estimations of the probability of fire occurrences in buildings.Fire Safety Journal 40(8):728-735.
Ma,F.A.2015.Information communication.San Rafael,California:Morgan&Claypool Publishers.
Matellini,D.B,A.D.Wall,I.D.Jenkinson,J.Wang,and R.Pritchard.2013.Modelling dwelling fire development and occupancy escape using Bayesian network.Reliability Engineering&System Safety 114:75-91.
McGee,T.K.,B.L.McFarlane,and J.Varghese.2009.An examination of the influence of hazard experience on wildfire risk perceptions and adoption of mitigation measures.Society and Natural Resources 22(4):308-323.
Pinsky,M.,and S.Karlin.2011.An introduction to stochastic modeling,4th edn.Boston:Academic Press.
Plough,A.,and S.Krimsky.1987.The emergence of risk communication studies:Social and political context.Science,Technology,and Human Values 12(3/4):4-10.
Pries,L.2005.Configurations of geographic and societal spaces:Asociological proposal between‘methodological nationalism’and the‘spaces of flows’.Global Networks 5(2):167-190.
Reed,M.,A.C.Evely,G.Cundill,I.R.A.Fazey,J.Glass,A.Laing,J.Newig,B.Parrish,et al.2010.What is social learning?Ecology and Society 15(4):response 1.
Rhodes,A.,and S.Reinholtd.1998.Beyond technology:A holistic approach to reducing residential fire fatalities.Australian Journal of Emergency Management 13(1):39.
Rogers,E.M.1962.Diffusion of innovations.New York:Free Press.
Rohde,D.,J.Corcoran,and P.Chhetri.2010.Spatial forecasting of residential urban fires:A bayesian approach.Computers,Environment and Urban Systems 34(1):58-69.
Scherer,C.W.,and H.Cho.2003.A social network contagion theory of risk perception.Risk Analysis 23(2):261-267.
Searle,G.,S.Darchen,and S.Huston.2014.Positive and negative factors for transit oriented development:Case studies from Brisbane,Melbourne and Sydney.Urban Policy and Research32(4):437-457.
Simonsen,K.1996.What kind of space in what kind of social theory?Progress in Human Geography 20(4):494-512.
Spatenkova′,O.,and K,Virrantaus.2013.Discovering spatio-temporal relationships in the distribution of building fires.Fire Safety Journal 62(A):49-63.
Wuschke,K.,J.Clare,and L.Garis.2013.Temporal and geographic clustering of residential structure fires:A theoretical platform for targeted fire prevention.Fire Safety Journal 62(A):3-12.
Xin,J.,and C.Huang.2013.Fire risk analysis of residential buildings based on scenario clusters and its application in fire risk management.Fire Safety Journal 62(A):72-78.