地理空间数据结合手机信令等多源数据刻画城市居民出行特征

本文提出了以地理空间数据为支撑,结合手机信令、POI等多源数据刻画城市居民出行特征的方法。首先将信令数据与地理信息区块绑定,根据时间特征和地理区块的社会属性,识别居民的基本职住娱信息;然后综合民生POI点、出行特征拓展关键词、图谱等多源数据,运用工作日通勤分析模型和节假日出行特征提取模型,识别用户的通勤距离、通勤方式、日均通勤频次、周均工作时长、节假日出行场景、出行频次、驻留时长等内容,并形成涵盖职住娱信息的出行特征类标签集。以成都市为例,采集连续1个月的手机信令数据和同时期的POI等数据,验证了该方法的可行性,该成果作为反映城市实际人口规模数量和空间分布特征的城市人口地图大数据产品的重要内容,为政府部门、商企用户开展相关分析业务提供数据支撑。

Geospatial data combined with multi-source data such as mobile phone signaling data to depict the travel characteristics of city residents

The paper proposes ways to depict the travel characteristics of city residents combined with multi-source data such as mobile phone signaling and POI.Firstly,binds signaling data to geographical information blocks and identifies the basic job, housing and entertainment information of residents according to time characteristics and social attributes of geographical data. Then,mix POI people's livelihood interest, travel characteristics development keywords such as multiple source data, uses weekday commuting analysis model and holiday travel characteristics extraction model to identify the user's commuting distance, commuting, daily commuting frequency, weekly working hours, holiday travel scene, travel frequency, residence time, and form entertainment information travel characteristics label set. Taking Chengdu as an example, collects a month of mobile phone signaling data and POI data in the same period to verify the feasibility of the method. The results reflect the actual urban population size and spatial distribution characteristics of urban population map of big data products and provide support for government departments, commercial enterprise users to carry out relevant analysis business.