GIS-based multi-criteria decision analysis for optimal urban emergency facility planning

Abstract

The growing scale of urban fire risks especially in megacities of the world such as Istanbul in Turkey arises largely as a result of the confluence of varied contemporary developmental and demographic trends that include accelerated urbanization, rising urban population, and migration to cities and socio-economic factors such as inequalities. Increasing urban development pressure brings about an expansion in built-up and urban settlement areas, often without adequate and comprehensive urban planning policies and regulations. As a result of increased human activities and interactions, these places are increasingly exposed to fire risk. To improve decision-making, a better comprehension of these relationships and interconnections as part of the complexities of human systems and urban dynamics functioning across different levels, actors, stakeholders, sectors, and disciplines is needed to mitigate fire hazard risk in urban populations. Therefore, recent advances in geospatial sciences have prompted emergency planners and managers to demand vast volumes of geographical data in order to make complex decisions. Diverse stakeholders, multidisciplinary teams, and multiple criteria are all involved in making these complex decision-making procedures. GIS-based Multi-Criteria Decision-Analysis (MCDA) strategies can be used to improve the quality of decision-making by merging spatial data and value judgments to tackle such complex planning issues, which is the fundamental strength of using this approach. In this context, fire risk and emergency planning at the spatial scale of the urban environment is a complicated and interrelated decision-making process requiring many factors and transdisciplinary stakeholder interaction. In this PhD thesis, GIS-based MCDA methods are applied to integrate the decision-makers' preferences with regard to solving such emergency planning problems of mitigating fire impacts and response action improvement by the optimization of new urban emergency and fire station site selection for the case of Istanbul province. The main aim of this thesis is therefore to develop an integrated GIS and MCDA model for effectively planning new urban emergency and fire facilities in Istanbul province, to reduce the fire response times to within five minutes. In order to achieve the main objective, there are ten (10) sub-objectives namely: using MCDA methods such as fuzzy AHP, Entropy-AHP, Best-Worst Method (BWM) and Decision Making Trial and Evaluation Laboratory (DEMATEL) for model construction, comparison and validation of resultant weights; determination of influencing criteria for effective urban emergency facility planning; utilizing the Delphi technique to conduct surveys to capture the preferences of decision-makers (DMs), evaluation of the criteria weights based on pairwise comparisons from relevant experts/DMs using the GIS-based MCDA approaches; identification of the most essential criteria for urban emergency facility site selection from the experts' judgements; using GIS to process, analyse and produce raster suitability maps that identify the most viable areas for locating new urban emergency facilities; prioritization of proposed new fire and urban emergency facilities (from low to high) for planning their construction in a phased manner based on cost and resource limitations; comparison analysis of distinct opinions and preferences of two DM groups in the group decision-making (GDM) process, comprising of fire brigade employees and academic/professional experts; using GIS capabilities to conduct a sensitivity analysis (SA) to test the sensitivity and robustness of the constructed models based on the combination of criteria weights; investigation of the interdependencies and levels of interaction among the various criteria employed in the MCDA modelling process. The thesis is, thus, comprised of three (3) papers addressing these ten sub-objectives. Istanbul province is determined as the case study area and six influencing criteria are identified with their respective weights evaluated, for each paper. In the first paper, a hybrid model of the recently developed BWM integrated with GIS is proposed. In the study, a GDM framework is suggested to support the incorporation of divergent views of two DM groups consisting of academicians and fire brigade practitioners for the emergency facility planning decision problem. Meaningful inferences from the study are made from statistical tests such as one-sample t-test, one-way ANOVA and Tukey's HSD test to analyse the preferences of the expert groups. Further, in this research, a degree of consensus or reliability in the DM process is assessed by a statistical measure called Kendall's coefficient of concordance, W. According to the study, it is revealed that the density of hazardous materials (DHM) and high population density (HPD) are perceived to be the most important by the academician and fire brigade practitioner DM group, respectively. For both DM groups, the distance from earthquake risk (DER) is viewed to be the least important. Resultant raster suitability maps for both DM groups are produced for visualizing the BWM model. In the second paper, the combination of AHP and Entropy methods with GIS is used for evaluating criteria weights both subjectively and objectively. In the study, the validation of the AHP-Entropy model is carried out on the criteria with the strongest influence on the decision outcome and spatially visualized using the One-At-a-Time (OAT) Sensitivity Analysis (SA) method. The study concludes that 28.1% of the case study area, or a third of the total area, is likely to be exposed to the risk of urban fires, necessitating the urgent planning of new urban emergency facilities to ensure adequate fire service coverage and protection. In the third paper, an integrated approach using fuzzy AHP based on a triangular membership function and GIS is implemented. For this case, the resultant fuzzy AHP weights are obtained from surveys of 19 experts and are validated using another MCDA technique, called BWM. Research results identified the most significant criteria in urban fire station site selection as the density of hazardous material facilities (DHM), a high population density (HPD) and proximity to main roads (PMR) with corresponding weights of 33.3%, 24.4% and 15.2%, respectively. By a thorough analysis of the results, a total of 34 new urban fire stations were proposed in addition to the existing 121 fire stations for addressing the increasing demands of fire protection services by minimizing the response time to less than 5 minutes. In addition, a three-level prioritization analysis from low to high was performed on the 34 proposed fire stations to plan their construction in phases based on cost and resource availability. Finally, the DEMATEL method is applied to examine the complex interrelationships and levels of influence among the criteria previously determined for optimally selecting new urban infrastructure for fire and emergency services in Istanbul as well as for model results validation of the BWM, AHP-Entropy and fuzzy AHP techniques applied. In this research, useful insights are generated by constructing an intelligible structural model visually in form of a digraph involving analysis of causal relationships among criteria and their directional influences as well as corresponding degrees of strength. The findings reveal that the high population density (HPD) is the most critical criterion followed by the density of hazardous materials (DHM) criterion in effectively planning new urban facilities for fire and emergency services and thus significantly influence and impact all the other criteria, while the distance to earthquake risk (DER) criterion does not influence any other criteria and consequently not essential in the planning procedure. The DEMATEL model results are used to validate the BWM, AHP-Entropy and fuzzy AHP model results in terms of levels of criteria significance and are therefore shown to be in high correlation. In this regard, these contextual relationships established from this research contribute toward an integrated fire risk mitigation policy formulation for planning new emergency facilities in urban environments through the engagement of all decision-makers across various backgrounds and disciplines.