Spatial-physical analysis of the urban smart growth indicators (case study: districts of Rasht)

Extensive changes in cities and their population has led to population and environmental crises. New strategies including the smart growth have been proposed to overcome this challenge. In fact, the smart growth strategy is an attempt to lead the cities toward sustainable and environmental approach....

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Main Authors: Mehrnaz Molavi, Ali Roshan
Format: Article
Language:English
Published: NR&DI URBAN-INCERC 2018-12-01
Series:Urbanism. Arhitectura. Constructii
Subjects:
Online Access:http://uac.incd.ro/Art/v9n4a02.pdf
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spelling doaj-3629831f0dfe4b5d89be2e23555aacfd2021-05-02T14:39:46ZengNR&DI URBAN-INCERCUrbanism. Arhitectura. Constructii2069-05092069-64692018-12-0194311326Spatial-physical analysis of the urban smart growth indicators (case study: districts of Rasht)Mehrnaz Molavi0Ali Roshan1University of Guilan, IranUniversity of Guilan, IranExtensive changes in cities and their population has led to population and environmental crises. New strategies including the smart growth have been proposed to overcome this challenge. In fact, the smart growth strategy is an attempt to lead the cities toward sustainable and environmental approach. Principles and strategies of smart growth create effective solutions for improving transportation and urban land use. This research investigates the compatibility of the regions and districts of Rasht (A northern city in Iran) with the smart growth criteria in a case study using Shannon analytic model, Holdern Model, and TOPSIS multi-criteria decision making model. The results of the Holdern model analysis indicates a dispersed growth of Rasht and displays its sprawl. Shannon entropy coefficient confirms a horizontal and dispersed growth of the city in its four districts and demonstrates that district 2 has the highest population and building density. The results of TOPSIS multi-criteria decision making model and entropy weighing method present dispersed and unpleasant urban growth and show district 3 has the highest density and compatibility with the urban smart growth criteria, and district 4 has the lowest density and the maximum difference comparing to the urban smart growth criteria.http://uac.incd.ro/Art/v9n4a02.pdfphysical-spatial developmenturban smart growthsprawlRasht
collection DOAJ
language English
format Article
sources DOAJ
author Mehrnaz Molavi
Ali Roshan
spellingShingle Mehrnaz Molavi
Ali Roshan
Spatial-physical analysis of the urban smart growth indicators (case study: districts of Rasht)
Urbanism. Arhitectura. Constructii
physical-spatial development
urban smart growth
sprawl
Rasht
author_facet Mehrnaz Molavi
Ali Roshan
author_sort Mehrnaz Molavi
title Spatial-physical analysis of the urban smart growth indicators (case study: districts of Rasht)
title_short Spatial-physical analysis of the urban smart growth indicators (case study: districts of Rasht)
title_full Spatial-physical analysis of the urban smart growth indicators (case study: districts of Rasht)
title_fullStr Spatial-physical analysis of the urban smart growth indicators (case study: districts of Rasht)
title_full_unstemmed Spatial-physical analysis of the urban smart growth indicators (case study: districts of Rasht)
title_sort spatial-physical analysis of the urban smart growth indicators (case study: districts of rasht)
publisher NR&DI URBAN-INCERC
series Urbanism. Arhitectura. Constructii
issn 2069-0509
2069-6469
publishDate 2018-12-01
description Extensive changes in cities and their population has led to population and environmental crises. New strategies including the smart growth have been proposed to overcome this challenge. In fact, the smart growth strategy is an attempt to lead the cities toward sustainable and environmental approach. Principles and strategies of smart growth create effective solutions for improving transportation and urban land use. This research investigates the compatibility of the regions and districts of Rasht (A northern city in Iran) with the smart growth criteria in a case study using Shannon analytic model, Holdern Model, and TOPSIS multi-criteria decision making model. The results of the Holdern model analysis indicates a dispersed growth of Rasht and displays its sprawl. Shannon entropy coefficient confirms a horizontal and dispersed growth of the city in its four districts and demonstrates that district 2 has the highest population and building density. The results of TOPSIS multi-criteria decision making model and entropy weighing method present dispersed and unpleasant urban growth and show district 3 has the highest density and compatibility with the urban smart growth criteria, and district 4 has the lowest density and the maximum difference comparing to the urban smart growth criteria.
topic physical-spatial development
urban smart growth
sprawl
Rasht
url http://uac.incd.ro/Art/v9n4a02.pdf
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