上海市精细时空尺度人口分布估计与特征分析

城市人口实时分布与动态变化特征是城市规划与综合治理的重要依据。受数据获取手段的局限性,准确地获取城市人口的实时分布状况一直是技术瓶颈,而移动通讯技术的迅速普及为这一问题的解决提供了技术途径。本文基于移动通讯信令的连续轨迹数据,实现了城市精细尺度人口分布时空估算的方法流程,并以上海市为研究区,对城市人口分布特征及时空移动过程进行了量化分析。研究表明：① 在数据方面,基于移动通讯信令数据估算城市人口分布的方式样本覆盖广、时空精度高、时效性较强且支持时空尺度灵活多变的应用研究需求,能够定量地描述城市人口分布时空动态特征且能推算城市真实人口规模;② 在人口分布时空特征方面,上海市在全市尺度上,各时段人口空间分布较为稳定且差异较小,而在中心城区日间人口较夜间人口呈现更为显著的空间集聚特征;③ 在人口移动时空特征方面,城市功能承载区与其它区域之间人口移动很少,早晚高峰期各城市功能承载区之间人口移动均体现为中心城区与其它新城之间的移动,且2个方向移动人数较为平衡;各城市功能承载区内均有超过半数的人口全天仅在其所在城区内部活动。本文的研究成果可为上海城市规划、应急管理、交通出行等提供更精准的科学依据。

Fine-grained Population Estimation and Distribution Characteristics in Shanghai

Urban population distribution and its dynamic changes have been playing a key role in urban planning and management. Currently, the wide use of information communication technology （ICT） provides an opportunity to support fine-scale studies by acquiring accurate individual positioning data. By extracting regular individual trajectories from a mobile communication signaling dataset, this study established an estimation procedure of urban population distribution and quantitatively analyzed spatiotemporal characteristics of population distribution and migration in Shanghai. The results indicated that, firstly, mobile communication signaling data had the ability to describe the dynamic characteristics of urban population and to estimate the real population size of a city in a quantitative and relatively an authentic way by taking its advantages of wide sample coverage, high spatial resolution, good timeliness and multiple spatiotemporal scales. Secondly, population distribution of Shanghai on the whole is stable all day long. Comparatively, population at the daytime showed a more remarkable spatial agglomeration phenomenon than population at night. Thirdly, the population migration between urban functional areas and other areas is rare. During the rush hour in the morning and evening, the population migration was mainly depicted as a relatively equally both-way movements between central urban area and other new urban functional areas. Within each functional area, more than half of its population is not moving out. In conclusion, this study can be useful for urban planning, emergency management and public traveling information services.