Understanding community fire risk—A spatial model for targeting fire prevention activities

Higgins, Emma; Taylor, Mark; Jones, Mark; Lisboa, Paulo J. G.

doi:10.1016/j.firesaf.2013.02.006

Cited by 30 publications

(36 citation statements)

References 10 publications

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“…Compared to wildfire, urban fire is virtually a both physical and social process (Jennings, 2013), in the sense that it occurs in built environment and affects individuals and socioeconomic activities in the surrounding neighborhood or communities, usually involving both individual causalities and economic losses. Meanwhile, most of the existing work on urban fires has focused on the cases in developed countries, such as the US (Gaither et al, 2011), the UK (Corcoran et al, 2007a(Corcoran et al, , 2007b(Corcoran et al, , 2011a(Corcoran et al, , 2011bHiggins et al, 2013), Canada (Asgary et al, 2010) and Australia (Corcoran et al, 2011a). So far, few studies have been carried out in developing countries and regions.…”

Section: Introductionmentioning

confidence: 99%

Spatial-Temporal Dynamics of Urban Fire Incidents: A Case Study of Nanjing, China

J.¹,

Zhang²

2016

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Fire and rescue service is one of the fundamental public services provided by government in order to protect people, properties and environment from fires and other disasters, and thus promote a safer living environment. Well understanding spatial-temporal dynamics of fire incidents can offer insights for potential determinants of various fire events and enable better fire risk estimation, assisting future allocation of prevention resources and strategic planning of mitigation programs. Using a 12-year (2002-2013) dataset containing the urban fire events in Nanjing, China, this research explores the spatial-temporal dynamics of urban fire incidents. A range of exploratory spatial data analysis (ESDA) approaches and tools, such as spatial kernel density and co-maps, are employed to examine the spatial, temporal and spatial-temporal variations of the fire events. Particular attention has been paid to two types of fire incidents: residential properties and local facilities, due to their relatively higher occurrence frequencies. The results demonstrated that the amount of urban fire has greatly increased in the last decade and spatial-temporal distribution of fire events vary among different incident types, which implies varying impact of potential influencing factors for further investigation.

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Section: Introductionmentioning

confidence: 99%

Spatial-Temporal Dynamics of Urban Fire Incidents: A Case Study of Nanjing, China

J.¹,

Zhang²

2016

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…Table 1 shows the accidental dwelling fires, injuries and deaths associated with the different community profile groups over the three years between 2010/11 and 2012/13. Table 1 Accidental dwelling fires, fire injuries and fires deaths by community profile group (Higgins et al, 2013). …”

Section: Phase 2 -Socio-economic Group Modelling For Improved Targetimentioning

confidence: 99%

Transforming fire prevention: a case study

Higgins

Taylor

Francis

et al. 2015

Transforming Government: People, Process and Policy

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Purpose:The purpose of the research project was to examine the transformation of fire prevention processes via improved targeting of fire prevention interventions over a four year period.Design / methodology / approach: A four year case study of the transformation of fire prevention processes involving a UK fire and rescue service, local council, NHS primary care trust and a police force was undertaken.Findings: Understanding the socio-economic causal factors underlying unintentional dwelling fires, and the need to work in collaborative partnerships to achieve change in such factors can support more targeted and effective fire prevention activities.Research limitations / implications: Analysis of underlying causal factors and their relationships, together with population segmentation and working in co-ordinated collaborative partnerships can support enhanced fire risk assessment and community safety. This supported more pro-active early intervention fire risk management.Practical implications: Analysis of socio-economic causal factors, and socio-economic groups associated with unintentional dwelling fires can assist in targeting fire prevention activities in a more effective and efficient manner. This enabled the fire and rescue service to target fire prevention to social groups most at risk of dwelling fires and the types of fires (for example, kitchen fires) relevant to the different social groups. Social implications:Collaborative public sector partnerships can achieve change in the socio-economic circumstances of at-risk individuals to support fire prevention. This enables the social and health related factors underlying fire risk to be addressed by the relevant partner health or social services agencies. Originality / value:The detailed analysis of the transformation of fire prevention activities that led to an implemented approach to enhanced community safety. In particular, the analysis and evaluation of the move to collaborative multi-agency partnerships to support and improve fire prevention activities.

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“…K-means clustering was used to identify a set of community profiles from the population within the region (Higgins et al, 2013) Each of the ten identified community profiles had differing levels of dwelling fire incidence, fire related injuries and fire fatalities. Ten population segments were created since, from an operational perspective, this number of population segments was viewed as providing an appropriate level of granularity for fire prevention activities.…”

Section: Enhanced Community Profile Geographical Information System Fmentioning

confidence: 99%

“…The approach utilized k-means cluster analysis of socio-economic indicators within the region studied to provide analysis of the different population segments within the region via the geographical information system (Higgins et al, 2013). …”

Section: Introductionmentioning

confidence: 99%

The evolution of geographical information systems for fire prevention support

Higgins

Taylor

Francis

et al. 2014

Fire Safety Journal

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Geographical information systems (GIS) provide visual map based analysis and reporting of information implemented in map layers. Geographical information systems evolve by incorporating new and enhanced means of analyzing and presenting location based information. In this paper we examine the evolution of a geographical information system for fire prevention support that evolved through transitions of the underlying approach to analysis of dwelling fire risk over a six year period 2007 to 2013. The novel theoretical contribution of this paper is the examination of the evolution of GIS analysis and modelling approaches, and in the specific context of fire and rescue services, the examination of the evolution of a fire prevention support GIS.

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Understanding community fire risk—A spatial model for targeting fire prevention activities

Cited by 30 publications

References 10 publications

Spatial-Temporal Dynamics of Urban Fire Incidents: A Case Study of Nanjing, China

Spatial-Temporal Dynamics of Urban Fire Incidents: A Case Study of Nanjing, China

Transforming fire prevention: a case study

The evolution of geographical information systems for fire prevention support

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