基于移动信令数据的城市热点识别方法

Urban hotspots identification method based on mobile signaling data

城市热点的识别对于探索解决引导性的人群疏散、规避交通拥堵等问题提供新途径,并为基于位置服务(location based services,LBS)如商铺选址、旅游导航等提供重要的科学参考,具有重要的应用价值。随着个人手机终端的普及与发展,手机已经成为研究用户行为特征的一种理想的探测器。提出了将手机信令数据融合兴趣点(point of interest,POI)数据来挖掘城市的热点区域并进行功能类型标定,重点通过手机信令数据研究人流的出行行为和在蜂窝的驻留时长情况来识别活跃蜂窝,并进一步通过基于密度的聚类算法判别热点区域。选取了重庆市较场口一定范围区域作为研究区域,数据来源于重庆某移动运营商提供的用户手机信令数据,通过实验实例验证分析,证明了该方法可快速识别出城市热点区域,并具有较高的准确性。

The identification of urban hotspots provides a new approach to solve the problem of guiding people to evacuate, avoiding traffic congestion and other issues, and offers a scientific reference for location-based services (LBS) such as shop location, tourism navigation and so on, and has important application value. With the popularization and development of personal mobile terminals, mobile phones have become an ideal detector for studying user behavior characteristics. In this paper, mobile signaling data is integrated with point of interest (POI) data to mine hot spots in cities and perform function type calibration. The focus is on mobile signaling data to study the travel behavior of human traffic and the resident duration in the cell to identify the active cell and to further identify the hot spot area by the density-based clustering algorithm. This paper chooses a certain area of Chongqing Municipality as a research area, and the data comes from user mobile signaling data provided by a mobile operator in Chongqing. The experimental verification shows that this method can quickly identify hot spots in cities with higher accuracy.