基于共享单车数据的居民出行热点区域与时空特征分析

Hotspot and Spatio-temporal Feature of Residents' Travel Behavoir Based on Sharing-bikes Data

在大数据时代,基于用户地理位置的服务已被广泛应用于人们的日常生活,其位置信息体现了用户的活动范围、聚集、活动痕迹等内容.采用北京市摩拜单车数据,经数据处理、地图匹配及聚类分析后,以可视化的方式揭示居民出行热点区域与时空特征规律.研究发现,工作日出现早晚骑行高峰,多条地铁线路客流量较大,出行具有明显的潮汐现象,热点区域比休息日更为集中.

In the era of big data,services based on user’s geographical location are widely used in people’s daily lives,and their location information reflects the scope of activities of the user,aggregation,activity traces,and so on.In this article,we used the Mobike data to reveal hotspot and spatio-temporal features and patterns of residents in a visual way after data processing,map matching and cluster analysis.Studies were shown that there were morning and evening riding peaks on the working day,and there were a large number of passengers on the subway lines.There were an obvious tidal phenomena in the trips,and the hot spots were more concentrated than those on the rest day.