城市设计策略中感知环境可步行性与目的性和话语性步行的关联

IF 1.6 4区 工程技术 Q4 TRANSPORTATION
Hsu-Sheng Hsieh, Min-Ta Chuang
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引用次数: 5

摘要

建筑环境与步行行为之间的关系已经得到了广泛的探索。然而,很少有研究将步行作为交通工具和步行作为活动进行区分,或者将城市设计工具应用于基于环境步行协会的步行能力改善。因此,本研究构建了感知环境可步行性因素,以取代个体之间变化的未识别物理环境,并使用因素分析和结构方程建模,检验了它们与步行到目的地(目的性步行)和步行作为活动(话语性步行)的关联。结果表明,住宅密度、土地利用组合多样性和行人/交通安全与有目的的步行有关,而美学和犯罪安全与散漫的步行有关。土地利用混合通道和街道连通性是两种步行模式的共同相关性。本研究还探讨了如何应用城市设计工具,包括土地使用规划、分区控制和城市设计指南,以基于环境步行协会来塑造可步行的环境。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Association of perceived environment walkability with purposive and discursive walking for urban design strategies
The relationship between the built environment and walking behavior has been explored extensively. However, little research has been done to either differentiate between walking for transport and walking as activity or that applies urban design tools to walkability improvement based on environment-walking associations. Therefore, this study constructed perceived environment walkability factors to replace unidentified physical environments that varied among individuals and examined their associations with walking to a destination (purposive walking) and walking as activity (discursive walking), using factor analysis and structural equation modeling. Results suggest that residential density, land-use mix diversity, and pedestrian/traffic safety were associated with purposive walking while aesthetics and crime safety were associated with discursive walking. Land-use mix access and street connectivity were common correlates of both walking patterns. This study also explored how to apply urban design tools, including land-use plans, zoning control, and urban design guidelines, to shape a walkable environment based on the environment-walking associations.
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来源期刊
CiteScore
3.40
自引率
5.30%
发文量
34
审稿时长
30 weeks
期刊介绍: The Journal of Transport and Land Usepublishes original interdisciplinary papers on the interaction of transport and land use. Domains include: engineering, planning, modeling, behavior, economics, geography, regional science, sociology, architecture and design, network science, and complex systems. Papers reporting innovative methodologies, original data, and new empirical findings are especially encouraged.
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