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Can good microscale pedestrian streetscapes enhance the benefits of macroscale accessible urban form? An automated audit approach using Google street view images
被引:24
|作者:
Koo, Bon Woo
[1
,4
]
Guhathakurta, Subhrajit
[1
]
Botchwey, Nisha
[2
]
Hipp, Aaron
[3
]
机构:
[1] Georgia Inst Technol, Coll Design, Sch City & Reg Planning, Atlanta, GA USA
[2] Univ Minnesota, Humphrey Sch Publ Affairs, Minneapolis, MN USA
[3] North Carolina State Univ, Dept Pk Recreat & Tourism Management, Community Hlth & Sustainabil, Raleigh, NC USA
[4] Sch City & Reg Planning, 245 Fourth St NW,Suite 204, Atlanta, GA 30332 USA
关键词:
Walkability;
Accessibility;
Streetscapes;
Google Street View;
Computer vision;
Interaction effects;
PHYSICAL-ACTIVITY;
BUILT ENVIRONMENT;
NEIGHBORHOOD WALKABILITY;
WALK ACCESSIBILITY;
PERCEIVED SAFETY;
CRIME;
DESIGN;
MODEL;
ASSOCIATION;
PERCEPTIONS;
D O I:
10.1016/j.landurbplan.2023.104816
中图分类号:
Q14 [生态学(生物生态学)];
学科分类号:
071012 ;
0713 ;
摘要:
While pedestrian accessibility measures have been widely used interchangeably with walkability, walkability is not just about accessibility. Microscale streetscape factors can provide qualities that pedestrians seek, including safety from crime, traffic safety, and pleasurability. These qualities can encourage walking through direct con-tributions or by enhancing the benefits of macroscale accessibility measures, or both. This study examines the main and interaction effects of microscale streetscape factors measured from street view images using computer vision in Atlanta, Georgia, USA. The correlation analysis showed that many microscale factors have moderate to strong correlations with the pedestrian accessibility measure. Binary logistic regressions demonstrated that safety from crime, pleasurability, and composite microscale index have direct contributions to walking mode choice. Regarding moderating effects, traffic safety, safety from crime, and composite microscale index enhanced the benefits of pedestrian accessibility measure. Policies designed to encourage walking can focus on streetscape features for short term efforts. Important caveats for policymakers in using machine-driven data collection are discussed.
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页数:13
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