As rail transit stations are the nodes of the transportation network and important spatial areas of the city,it is of great significance to study the street vitality around the rail station for the development of rail TOD and the optimization of the street environment.By collecting multi-source data such as street view images,points of interest and population thermal data,this paper describes the spatial distribution of street vitality around rail stations,and constructs the multi-scale geographical weighted regression model to analyze the influence of the built environment on street vitality.The results indicate that street vitality exhibits a clustering effect,radiating out from the central station;the diversity of POI categories significantly impacts street vitality and shows a positive correlation;the influence of the green view rate on street vitality demonstrates spatial heterogeneity;variables such as the sky view factor do not significantly correlate with vitality,while the impact of motor traffic appears to suppress vitality.These findings can provide important references for the functional layout around rail transit stations and for the improvements of refined street environment.
关键词
街道活力/建成环境/轨道站点/多源数据/多尺度地理加权回归模型
Key words
street vitality/built environment/rail transit/multi-source data/multi-scale geographical weighted regression model
维普
万方数据