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城市建成环境对共享单车出行影响的时空特征——以深圳市为例

Effects of Built Environment on the Spatio-Temporal Trajectories of Shared Bicycles:A Case Study of Shenzhen
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摘要 以深圳市为例,利用共享单车OD等多源数据,从工作日、休息日多时段分析共享单车出行时空特征,并构建基于客观物质空间、主观感知体验的建成环境“5Ds”指标,运用多尺度地理加权回归模型(MGWR)解析不同建成环境对共享单车出行流量影响的时空异质效应。研究表明:1)时间上,工作日和休息日早、晚高峰的共享单车出行流量较其他时段整体显著,且休息日较工作日的峰值时段具有滞后性;空间上,各峰值时段的出行流量高值区域呈“多核集聚、带状延伸”的分异格局;2)各建成环境要素对共享单车出行流量影响的时段差异显著。就业设施密度、围合度及人口密度在各时段均具有高解释度,其影响力整体呈全局显著特征,其余变量则在不同时段存在局部显著效应;3)各时段影响较为显著的变量在空间作用尺度上存在分异。就业设施密度与围合度的影响力在各时段的空间变化最为稳定,街道绿视率与人口密度在不同时段呈现差异化的空间分布特征。 With the rapid development,shared bicycles have gradually become an important part of slow urban traffic in China and have played an important role in satisfying the travel needs and facilitating the transfer of residents.Exploring the spatial and temporal characteristics of the impact of the built environment on shared bike travel is of practical importance to reshape the construction of low-carbon transportation and an urban-friendly cycling environment dominated by slow traffic and public transportation.We analyzed the spatio-temporal characteristics of shared bicycle travel through multi-source big data including Shenzhen's shared bicycle OD data,OSM road network data,Baidu Street View,and POIs and used a multi-scale geographical weighted regression model(MGWR)based on the"5D"index of the built environment to analyze the spatial difference characteristics of the impact of different built environment on shared bicycle flow.The findings of the research indicate that:(1)In terms of time,the shared bicycle flow in the morning and evening peaks of both working and rest days is more significant than that of other periods,and the peak period of the remaining days lags behind that of the working days.(2)In terms of space,the spatial distribution characteristics of the traffic flow of shared bicycles during each peak period exhibit a spatial pattern of"multiple aggregation cores and several extended belts."(3)Significant differences were observed in the impact of various built environmental factors on the flow of shared bicycle travel,among which,employment facility density,enclosure degree and population density had a positive effect in each period;their influences were globally significant;and the remaining factors demonstrated varied characteristics in each period.(4)Factors with significant influence showed different spatial scales in different periods.The spatial changes of employment facility density and enclosure in each period were generally flat;the spatial changes of proximity,density of shopping facilities,and the nearest distance to subway stations in some periods were generally flat;the spatial changes of building continuity and relative walking width were obvious in some periods.Moreover,population density and green vision rate had different spatial characteristics in different periods.This study restores the travel track of shared bicycles,analyzes the spatiotemporal characteristics of shared bicycle travel in multiple periods of working days and rest days and long-term series,and increases micro-built environment factors of subjective perception of people and experience dimension based on existing objective material space environment variables,to explore the spatiotemporal differences of the impact of different built environments on the travel flow of shared bicycles which compensate for the existing shared-bike travel time and space characteristics,build a shortage of environmental impact research,and provide references for the construction of an urban-friendly cycling environment and the creation of a slow walking space.
作者 项振海 李青 洪良 盛杰 班鹏飞 Xiang Zhenhai;Li Qing;Hong Liang;Sheng Jie;Ban Pengfei(Science and Technology,Kunming University,Kunming 650500,China;Guangdong Guodi Planning Technology Co.,Ltd.,Guangzhou 510070,China)
出处 《热带地理》 CSCD 北大核心 2024年第2期236-247,共12页 Tropical Geography
基金 国家自然科学基金项目(51878284) 云南省社科规划社会智库项目(SHZK2023336) 云南省科技厅基础研究专项—面上项目(202201AT070792)。
关键词 共享单车出行 建成环境 出行流量 时空异质性 MGWR模型 深圳市 bike-sharing mobility built environments flow of shared bicycles spatio-temporal heterogeneity MGWR model Shenzhen City
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