Analysis of spatial (in)equality of urban facilities in Tehran: an integration of spatial accessibility

Hosseini, ‌Ali; Farhadi, Ebrahim; Hussaini, Fatema; Ahmad, Pourahmad; Akbari, Nooshin Seraj

doi:10.1007/s10668-021-01715-3

Cited by 23 publications

(19 citation statements)

References 75 publications

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“…For achieving sustainable development goals, the government healthcare policies need to be more generalized to promote health status and socioeconomic development because healthcare facilities and services are uneven due to socioeconomic conditions from the grass-root level in developing countries (Mansour, 2016 ). Developing countries should improve their healthcare services (Asare-akuffo et al, 2019 ; Hosseini et al, 2021 ; Miç et al, 2019 ; Mishra et al, 2021 ; Shaw & Sahoo, 2020 ) due to very high population with low GDP, limited and uneven distribution of healthcare facilities (HCF), and infrastructure also, especially in India (Assad, 2019 ). Due to the rapid growth of urban and suburban areas through continuous migration, demand for healthcare facilities (HCF) is increasing simultaneously (Al-Taiar et al, 2010 ; Delamater et al, 2012 ; Lawal & Anyiam, 2019 ; Maleki Rastaghi et al, 2018 ; Shah et al, 2016 ; Waithaka, 2015 ; W. Zhang et al, 2016 ) and for that reason raise the building of new healthcare facilities (HCF) is considered as one of the most important steps to easily accessible, proficient, and the affordable healthcare system by poor people to achieving the Millennium Development Goals of every government (Lawal & Anyiam, 2019 ; Ajala et al, 2017).…”

Section: Literature Reviewmentioning

confidence: 99%

Spatial accessibility modeling to healthcare facilities in the case of health shocks of Midnapore municipality, India

Das

Dutta²,

Roy

et al. 2023

GeoJournal

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This research aims to identify the accessibility of the entire population, especially the slum population to existing healthcare facilities (HCF) as well as the slum neighborhoods having low geographic accessibility, and finally, to provide an analytical model for the people living in areas that are outside the coverage range of existing healthcare facilities (HCF) across the study area. Spatial data has been collected and used based on the road network, elevation, location of HCF, municipal boundary, slum point, and satellite images from various sources. Also, non-spatial data such as socioeconomic variables are collected from questionnaires survey within a particular period. The spatial analysis tool like as near, network analysis, and predictive analysis in the ArcGIS platform was used to examine geographic accessibility. The results of the spatial analysis show that the distribution of public healthcare facility centers in the study area has not been uniformly distributed. Across 84% of areas in the study area have sound spatial accessibility with traveling time coverage is about 12 min. However, 16% of areas have a traveling time of 12 to 30 min under low accessibility with existing slum neighborhoods. Therefore, the low spatial accessibility areas are demanding new healthcare facilities in the study area. The Analytical Hierarchy Process (AHP) is employed to find the most optimal and efficient locational suitability for building new healthcare facility centers. The finding of AHP analysis for site suitability of healthcare facilities revealed five major classes as most suitable (2%), suitable (5%), moderate (35%), poor (54%), and very poor (4%) in the study area. Moreover, the realistic framework of this study helps to measure geographic accessibility and suitability in any geographical area.

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Section: Literature Reviewmentioning

confidence: 99%

Spatial accessibility modeling to healthcare facilities in the case of health shocks of Midnapore municipality, India

Das

Dutta²,

Roy

et al. 2023

GeoJournal

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“…Government policies in developing countries such as Iran 3 tend to emphasize centralization and monopolization in their capitalist economies, which are also influenced by global policies (Habibi et al 2022). In Tehran (the capital of Iran and the largest city in the Middle East, and ranks 16 th among the world's most populous cities; Hosseini et al 2022), the urbanization rate increased from 47% in 1976 to 74% in 2016 (Habibi et al 2022). Although urban trees are vital in improving the urban environment, their potential ecosystem services and economic values are often rarely considered in urban policy-making and planning.…”

Section: Introductionmentioning

confidence: 99%

Assessment of air pollution removal by urban trees based on the i-Tree Eco Model: The case of Tehran, Iran

Rasoolzadeh

Dinan

Esmaeilzadeh

et al. 2023

Preprint

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As the population grows and economic development accelerates, urbanization is also increasing at a fast pace and this has resulted in severe air pollution that poses a significant threat to human health. Air quality issues have become increasingly serious in metropolises like Tehran (Iran) in recent years. Hence, this study aims to estimate the role of Tehran’s urban trees in air pollution removal and evaluate this ecosystem service’s economic value, based on the i-Tree Eco model. This study’s results illustrate that Tehran urban trees produce 160,271.4 tons of oxygen and remove 1286.42 tons of pollutants in 2020. The rate of air pollution removal varies among pollutants which are 134.83, 299.68, 270.32, 0.68, 489.41, and 91.50 t yr− 1 for the CO, NO2, O3, PM2.5, PM10, and SO2, respectively, with an associated monetary value of US$ 1,536,619. This effect is small compared to the amount of pollution emitted in 2020 (0.17%) due to the high emissions rate and low per capita green space in Tehran. Therefore, tree planting should not be considered a single solution to emission reduction but rather a complementary one. The findings could serve as a basis for future replication in other locations and serve as a guide for enhancing urban green spaces to promote sustainable urban development.

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“…Zhou assessed the layout of public service facilities in unit planning using the pedestrian index method in GIS [7] . Hosseini et al used the spatial statistical method and fuzzy logic to assess and analyse the inequality of access to urban welfare facilities and spatial distribution characteristics [8] . Most of the existing studies have focused on one type of community service facilities, and less attention has been paid to the spatial distribution characteristics of multiple types of community service facilities.…”

Section: Introductionmentioning

confidence: 99%

Spatial distribution characteristics of community service facilities in Shangcheng District of Hangzhou, China

Shi,

2023

Sixth International Conference on Computer Information Science and Application Technology (CISAT 2023)

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In the smart city development phase, the construction of community service facilities plays an important role in creating future communities and convenient living circles. With the continuous maturity of big data and GIS spatial analysis technologies, it is possible to make objective quantitative assessment of the construction of community service facilities and provide scientific decisions for future planning and layout. Our objective was to analyze the current spatial distribution characteristics of community service facilities in the Shangcheng District of Hangzhou, Zhejiang Province, China. We processed, counted and visualized the data from POI (Point of Interest) using the nearest-neighbor distance method and kernel density analysis in the ArcGIS platform. The results showed that, in terms of quantitative characteristics, the number of financial and cultural facilities was relatively low, making it difficult to achieve full coverage of residential land. In terms of layout, dining, transportation, shopping, and education facilities were arranged around the residential areas, while cultural, leisure and medical facilities were arranged along the city's primary roads or metro lines. In terms of clustering, the HB (Hubin) section was characterized by high density and large area clusters, indicating a highly developed system of community services and facilities. The GBNT (Genbei New Town) section showed a low-density and point pattern, indicating a poorly backward system of community services and facilities and needs to be improved and optimized.

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Analysis of spatial (in)equality of urban facilities in Tehran: an integration of spatial accessibility

Cited by 23 publications

References 75 publications

Spatial accessibility modeling to healthcare facilities in the case of health shocks of Midnapore municipality, India

Spatial accessibility modeling to healthcare facilities in the case of health shocks of Midnapore municipality, India

Assessment of air pollution removal by urban trees based on the i-Tree Eco Model: The case of Tehran, Iran

Spatial distribution characteristics of community service facilities in Shangcheng District of Hangzhou, China

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