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SMARTer growth neighborhood design manual : application to existing neighborhoods Ovi, Md Firoz Mahmood
Abstract
Urbanization is putting immense pressure on global infrastructure. Uncontrolled rapid urbanization and motorization of cities are one of the main causes of Urban Sprawl. This sprawl alters the structure and pattern of cities, making it socially, economically, and environmentally unsustainable. Urban Sprawl is associated with traffic fatalities, physical inactivity, obesity, and increased GHG emissions. Urban planners and engineers are researching new methods to eliminate the negative impacts of urban sprawl. SMARTer Growth (SG) Neighborhood design or previously know as Fused Grid (FG) Neighborhood Design has been identified as a reliable planning technique that can effectively fight urban sprawl while making neighborhoods more sustainable and liveable. Macro-level collision prediction models were developed in this study to evaluate the traffic safety condition of the neighborhoods under study. SG was introduced to evaluate two existing neighborhoods, and macro-level collision prediction models were applied to assess the traffic safety of the existing neighborhoods and the retrofitted designs. The comparison between the existing neighborhoods and the retrofitted designs showed a 62% reduction in the total number of collisions for the retrofit design of Capri-Landmark, Kelowna, BC, Canada, and 56% reduction in the total number of collisions for the retrofit design for Gulshan, Dhaka, Bangladesh. Additionally, the suite of tools toward SMARTer Growth (SG) Neighborhood Design Manual was applied to evaluate these retrofitted designs. Based on the evaluation, the health outcomes and quality of life of the residents in the proposed retrofit designs were discussed.
Item Metadata
Title |
SMARTer growth neighborhood design manual : application to existing neighborhoods
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Creator | |
Publisher |
University of British Columbia
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Date Issued |
2020
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Description |
Urbanization is putting immense pressure on global infrastructure. Uncontrolled rapid urbanization and motorization of cities are one of the main causes of Urban Sprawl. This sprawl alters the structure and pattern of cities, making it socially, economically, and environmentally unsustainable. Urban Sprawl is associated with traffic fatalities, physical inactivity, obesity, and increased GHG emissions. Urban planners and engineers are researching new methods to eliminate the negative impacts of urban sprawl. SMARTer Growth (SG) Neighborhood design or previously know as Fused Grid (FG) Neighborhood Design has been identified as a reliable planning technique that can effectively fight urban sprawl while making neighborhoods more sustainable and liveable. Macro-level collision prediction models were developed in this study to evaluate the traffic safety condition of the neighborhoods under study. SG was introduced to evaluate two existing neighborhoods, and macro-level collision prediction models were applied to assess the traffic safety of the existing neighborhoods and the retrofitted designs. The comparison between the existing neighborhoods and the retrofitted designs showed a 62% reduction in the total number of collisions for the retrofit design of Capri-Landmark, Kelowna, BC, Canada, and 56% reduction in the total number of collisions for the retrofit design for Gulshan, Dhaka, Bangladesh. Additionally, the suite of tools toward SMARTer Growth (SG) Neighborhood Design Manual was applied to evaluate these retrofitted designs. Based on the evaluation, the health outcomes and quality of life of the residents in the proposed retrofit designs were discussed.
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Genre | |
Type | |
Language |
eng
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Date Available |
2020-02-24
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Provider |
Vancouver : University of British Columbia Library
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Rights |
Attribution-NonCommercial-NoDerivatives 4.0 International
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DOI |
10.14288/1.0388694
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URI | |
Degree | |
Program | |
Affiliation | |
Degree Grantor |
University of British Columbia
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Graduation Date |
2020-05
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Campus | |
Scholarly Level |
Graduate
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Rights URI | |
Aggregated Source Repository |
DSpace
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Item Citations and Data
Rights
Attribution-NonCommercial-NoDerivatives 4.0 International