Metropolises spatial expansion management with special reference to systems related to environmental values. Tehran metropolis as the case study

Khosravaninezhad, Samaneh; Zadehbagheri, Peyman; Nikdel, Leila

doi:10.1016/j.proeng.2011.11.2055

Cited by 4 publications

(1 citation statement)

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“…In the case of Tehran, the capital of Iran, rapid population growth and its pivotal role in the country's economy have led to numerous challenges [ [64] , [65] , [66] , [67] , [68] , [69] , [70] , [71] , [72] , [73] , [74] , [75] , [76] ]. Among these challenges, spatial inequality and limited access to public facilities, including leisure spaces, pose significant issues for the majority of citizens [ 62 , [77] , [78] , [79] , [80] , [81] , [82] ].…”

Section: Introductionmentioning

confidence: 99%

Spatial analysis of leisure land uses in Tehran: Assessing inequity using the MARCOS method within a GIS framework

Ghasemi,

Behzadfar,

Borhani

2023

Heliyon

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Section: Introductionmentioning

confidence: 99%

Spatial analysis of leisure land uses in Tehran: Assessing inequity using the MARCOS method within a GIS framework

Ghasemi,

Behzadfar,

Borhani

2023

Heliyon

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Enhancing urban livability: Analyzing Tehran through equitable land use distribution

Ghasemi

2024

Journal of Urban Management

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Spatial coordination and industrial pollution of urban agglomerations: Evidence from the Yellow River Basin in China

Hua,

Zhang,

Miao

et al. 2024

Expert Systems

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Population, economy, and other social factors of urban agglomerations in river basins bear the inescapable responsibility for water environmental pollution. This article utilizes data from 53 cities in three regional‐level urban agglomerations in the Yellow River Basin (YRB) from 2006 to 2015 as research samples to analyse the impact of the coupling and coordination of physical space expansion (PSE) and social space structure (SSS) of urban agglomerations on industrial pollution. Multi‐source remote sensing data is used to quantify the physical space expansion of urban agglomerations, while population and economic data are used to measure the social space structure. We analyse the coupling coordination degree and spatiotemporal evolution of the PSE and SSS of urban agglomerations by applying a coupling coordination degree model. Finally, the grey incidence model is used to rank the influencing factors of pollution. The research findings are summarized as follows: (1) Three regional‐level urban agglomerations in the YRB show excessive expansion, with the Shandong Peninsula Urban Agglomeration (SPUA) being the most severe. (2) SPUA and Central Plains Urban Agglomeration (CPUA) exhibit the polycentric SSS, while the Guanzhong Plain Urban Agglomeration (GPUA) shows the monocentric SSS. (3) PSE and SSS of the three urban agglomerations are slightly uncoordinated, but show a trend of easing. The uncoordinated level between SPE and economic distribution in CPUA ranks the highest. (4) SSS exerts the greatest impact on pollution, while the pollution impact of PSE ranks lower. The pollution impact of the coupling coordination degree between SPE and SSS falls between the two. The research results provide a reference for sustainable urban development and planning in countries around the world.

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Metropolises spatial expansion management with special reference to systems related to environmental values. Tehran metropolis as the case study

Cited by 4 publications

References 1 publication

Spatial analysis of leisure land uses in Tehran: Assessing inequity using the MARCOS method within a GIS framework

Spatial analysis of leisure land uses in Tehran: Assessing inequity using the MARCOS method within a GIS framework

Enhancing urban livability: Analyzing Tehran through equitable land use distribution

Spatial coordination and industrial pollution of urban agglomerations: Evidence from the Yellow River Basin in China

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