Exploring the Nonlinear Relationship between the Built Environment and Active Travel in the Twin Cities

被引：78

作者：

Tao, Tao ^{[1
]}

Wu, Xinyi ^{[1
]}

Cao, Jason ^{[1
]}

Fan, Yingling ^{[1
]}

Das, Kirti ^{[1
]}

Ramaswami, Anu ^{[2
]}

机构：

[1] Univ Minnesota, Humphrey Sch Publ Affairs, 301 19th Ave South, Minneapolis, MN 55455 USA

[2] Princeton Univ, MS Chadha Ctr Global India, Princeton, NJ 08544 USA

来源：

JOURNAL OF PLANNING EDUCATION AND RESEARCH | 2023年 / 43卷 / 03期

基金：

美国国家科学基金会;

关键词：

machine learning; travel behavior; land use; walking; community design; RESIDENTIAL SELF-SELECTION; BOOSTING DECISION TREES; PHYSICAL-ACTIVITY; LAND-USE; URBAN DESIGN; WALKING; NEIGHBORHOOD; TRANSPORT; PARKS; SCALE;

D O I：

10.1177/0739456X20915765

中图分类号：

TU98 [区域规划、城乡规划];

学科分类号：

0814 ; 082803 ; 0833 ;

摘要：

Active travel is important to public health and the environment. Previous studies substantiate built environment influences active travel, but they seldom assess its overall contribution. Most of the studies assume that built environment characteristics have linear associations with active travel. This study uses Gradient Boosting Decision Trees to explore nonlinear relationships between the built environment and active travel in the Twin Cities. Collectively, the built environment has more predictive power for active travel than demographics, and parks, proximity to downtown, and transit access have important influences. The threshold effects of built environment variables help inform planning practice.

引用

页码：637 / 652

页数：16

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