Yan Jinming

Mr. Yan Jinming


Research Focus & Metrics

Academic Career Length

6Years (2021-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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JPJiandong Peng
Jiandong Peng
JQJiaJie Qi
JiaJie Qi
CCChangwei Cui
Changwei Cui
YJYan Jinming
Yan Jinming
QDQi Dai
Qi Dai
HYHong Yang
Hong Yang
The long-distance commute to school caused by urban sprawl and the car-oriented urban construction model are key factors leading to primary/middle school students being picked up by their parents in cars. Encouraging those students to take rail transit can reduce their dependence on cars. This paper uses a stepwise regression based on rail-transit swipe data to explore the influence of the built environment on rail-transit commuting characteristics in Wuhan, and uses a geographically weighted regression (GWR) model to analyze the spatial heterogeneity of significant influencing variables. The study found that: (1) 60% of students are one-way commuters; (2) 88.6% of students travel less than 10 km; (3) the floor area ratio, bus station density and whether the station is a transfer station have an obvious positive effect on the flow of commuters; (4) whether the station is a departure station has a positive effect on the commuting distance, but the mixed degree of land use and road density have a negative effect on the commuting distance. This research can assist cities in formulating built environment optimization measures and related policies to improve school-age children’s use of rail transit. This is important in the development of child-friendly cities.

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YJYan Jinming
Yan Jinming
QWQiuyu Wan
Qiuyu Wan
FJFeng Jingyi
Feng Jingyi
JWJianjun Wang
Jianjun Wang
YHYiwen Hu
Yiwen Hu
XYXuexin Yan
Xuexin Yan
Although many studies have investigated the non-linear relationship between the built environment and rail patronage, it remains unclear whether this influence is equally applicable to primary and secondary school students due to their physiological characteristics and cognitive limitations. This study applies the GBDT model to Wuhan student metro swipe data in order to investigate the relative importance and non-linear association of the built environment on the school-commuting metro ridership. The results show that the variable with the greatest predictive power is the number of living service facilities followed by the number of intersections, and the degree of land-use mixture. All of the built environment variables had non-linear associations with the school-commuting ridership, and the greatest attraction to the school-commuting metro ridership occurred when the number of living service facilities was 500, the number of intersections was 36, and the degree of land-use mixture was 0.8. These findings can help planners to prioritize land-use optimization and the effective range of land-use indicators when developing child-friendly rail transport policies.