Measuring Spatial Accessibility to Healthcare Facilities in Isfahan Metropolitan Area in Iran

Rabiei-Dastjerdi, Hamidreza; Mohammadi, S.; Samouei, R.; Kazemi, M.; Matthews, S.; McArdle, Gavin; Homayouni, S.; Kiani, B.; Sadeghi, R.

doi:10.5194/isprs-annals-x-4-w1-2022-623-2023

Cited by 4 publications

(1 citation statement)

References 38 publications

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“…The appropriation of the system by researchers in these areas favors the understanding and elaboration of public policies that allow for reductions in social vulnerabilities [84], the equitable distribution of public infrastructure in cities [85], improvements in public healthcare services [86], making better decisions in custody hearings [87], promoting the digital maturation of companies, achieving opportunities and avoiding market threats [88], and improving accessibility to healthcare facilities [89], among others.…”

Section: Discussionmentioning

confidence: 99%

Fuzzy-Set-Based Multi-Attribute Decision-Making, Its Computing Implementation, and Applications

Ferreira,

Ribeiro,

Schuffner

et al. 2024

Axioms

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This paper reflects the results of research analyzing models of multi-attribute decision-making based on fuzzy preference relations. Questions of constructing the corresponding multi-attribute models to deal with quantitative information concomitantly with qualitative information based on experts’ knowledge are considered. Human preferences may be represented within the fuzzy preference relations and by applying diverse other preference formats. Considering this, so-called transformation functions reduce any preference format to fuzzy preference relations. This paper’s results can be applied independently or as part of a general approach to solving a wide class of problems with fuzzy coefficients, as well as within the framework of a general scheme of multi-criteria decision-making under conditions of uncertainty. The considered techniques for fuzzy preference modeling are directed at assessing, comparing, choosing, prioritizing, and/or ordering alternatives. These techniques have served to develop a computing system for multi-attribute decision-making. It has been implemented in the C# programming language, utilizing the “.NET” framework. The computing system allows one to represent decision-makers’ preferences in one of five preference formats. These formats and quantitative estimates are reduced to nonreciprocal fuzzy preference relations, providing homogeneous preference information for decision procedures. This paper’s results have a general character and were applied to analyze power engineering problems.

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Section: Discussionmentioning

confidence: 99%

Fuzzy-Set-Based Multi-Attribute Decision-Making, Its Computing Implementation, and Applications

Ferreira,

Ribeiro,

Schuffner

et al. 2024

Axioms

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Towards designing a comprehensive composite index for social vulnerability to natural hazards in the big data era: potential challenges and partial solutions

Rabiei-Dastjerdi,

Brereton,

O’Neill

2024

Nat Hazards

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This study provides a practical definition and framework to measure social vulnerability to natural hazards, addressing gaps in the literature after three decades of Susan Cutter's Place-Based Model. The current social vulnerability index, designed based on available data such as census data, is limited in capturing all aspects of social vulnerability and spatial inequalities. This research explored and proposed a new theoretical perspective and methodological framework for designing a comprehensive index for social vulnerability to natural disasters using emerging big data, which is practical and feasible and can be applied to social vulnerability studies in general and social vulnerability to natural hazards in particular. This research first defines constructs of social vulnerability to natural hazards, including (1) socioeconomic status or conditions, (2) physical infrastructure or accessibility to facilities and services, (3) ecological-environmental conditions, (4) access to security facilities and crime rate, (5) technological inequalities, (6) health conditions of the citizens, and (7) susceptibility. Then, it proposes potential solutions for developing a comprehensive composite index under ideal conditions without (big) data limitations, using the US and the UK as case examples. These solutions are not just theoretical but also practical and feasible, instilling confidence in their implementation. This research offers valuable insights for researchers and policymakers in diverse sectors, supporting the design of effective disaster risk reduction strategies and intervention programs.

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Reducing urban energy consumption and carbon emissions: a novel GIS-based model for sustainable spatial accessibility to local services and resources

Rahmati,

Rabiei-Dastjerdi,

Bibri

et al. 2024

Comput.Urban Sci.

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This study explores the complex interconnections among global population growth, energy consumption, CO2 production, and disparities in service access through the lens of a single case study. Rapid population growth in many major cities has created significant challenges related to equitable access to services and socio-economic development, thereby impacting both their energy consumption patterns and environmental impacts. The case investigated in this study, like many other cases in developing countries, exhibits differences in service provision, infrastructure development, and energy usage, particularly between the northern and southern regions, which significantly affect the quality of life, environmental sustainability, and economic development. Previous efforts to narrow these geographic disparities have yielded limited success and exhibited several shortcomings. By employing a GIS Analytical Network Process method, this study examines service accessibility patterns in a single-case city, with a particular emphasis on green spaces, food services, and educational facilities and services. This GIS-based approach seeks to achieve sustainable levels of access to multiple land uses by evaluating their accessibility and identifying areas of overlap between them. The study endeavors to increase access and density of service standards when planning the placement of new facilities based on these standards in new locations. The method developed in this study represents a critical stride toward achieving these key objectives. The findings reveal that only 47% of city population blocks enjoy high service accessibility, while 40% have moderate accessibility, and 2.6% experience poor accessibility. These insights are of significant value to urban planners, researchers, and policymakers striving to reduce energy shortages and promote sustainable energy and transportation strategies to mitigate environmental impact in urban areas.

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Measuring Spatial Accessibility to Healthcare Facilities in Isfahan Metropolitan Area in Iran

Cited by 4 publications

References 38 publications

Fuzzy-Set-Based Multi-Attribute Decision-Making, Its Computing Implementation, and Applications

Fuzzy-Set-Based Multi-Attribute Decision-Making, Its Computing Implementation, and Applications

Towards designing a comprehensive composite index for social vulnerability to natural hazards in the big data era: potential challenges and partial solutions

Reducing urban energy consumption and carbon emissions: a novel GIS-based model for sustainable spatial accessibility to local services and resources

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