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  • Land-Use Modification based on Transit-Oriented Development adjacent to Historical Context (Case Study: Qazvin City)

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عنوان URL للمقالة


رقم المقالة : SOIJ-2104-1416 (R1) زيارة : 268 الصفحة: 67 - 79

10.22094/soij.2021.1929092.1416

20.1001.1.23456450.2021.10.3.5.8

نوع المخطوط: ابحاث

Land-Use Modification based on Transit-Oriented Development adjacent to Historical Context (Case Study: Qazvin City)

الموضوعات : Space Ontology International Journal

Hamid Mirzahossein 1 , Amir Abbas Rassafi 2 , Kaveh Sadeghi 3 , Pooyan Najafi 4

1 - Department of Civil-Transportation Planning, Imam Khomeini International University, Qazvin, Iran
2 - Department of Civil-Transportation Planning, Imam Khomeini International University, Qazvin, Iran
3 - Department of Civil-Transportation Planning, Imam Khomeini International University, Qazvin, Iran
4 - Department of Civil-Transportation Planning, Imam Khomeini International University, Qazvin, Iran

تاريخ الإرسال : 15 الثلاثاء , رمضان, 1442 تاريخ التأكيد : 14 الخميس , ذو القعدة, 1442 تاريخ الإصدار : 24 الأربعاء , محرم, 1443

الکلمات المفتاحية: Genetic Algorithm (GA), Qazvin, Transit-Oriented Development (TOD), Historical Areas,

ملخص المقالة :

Nowadays, improving public transport alone is not enough to solve urban traffic congestion, and a proper land-use planning scheme should accompany it. One of the approaches to solve this problem is mutual interaction between land-use and transportation called Transit-Oriented Development (TOD). Since Qazvin, as a historical city that was Iran's medieval capital in the Safavid dynasty (1555-1598), was selected as a pilot to implement TOD by the Ministry of Roads and Urban Development (MRUD), knowing the various aspects of this issue is essential. This paper presents the best-generated plan for land use modification around the concerned TOD stations adjacent to Qazvin city's historical areas. In this regard, a mathematical model with four objectives is developed to preserve historical context and signify optimized mixed-use using the Genetic Algorithm (GA) based on Python programming. First, maximize the density of commercial, residential, and mixed land use. Secondly, minimize the TOD skyline border to preserve the zone's historical identity. Thirdly, minimize land-use changes as much as possible to save the regions' context, and finally, increase the density of the land use allocation based on the TOD rules. In station 6, the most change related to residential decreased by about 30 percent, but at station 19, the most remarkable change related to commercial decreased about 10 percent.

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