首页> 外文期刊>Computers,environment and urban systems >Estimation of urban crowd flux based on mobile phone location data: A case study of Beijing, China
【24h】

Estimation of urban crowd flux based on mobile phone location data: A case study of Beijing, China

机译:基于手机位置数据的城市人群通量估计:以中国北京为例

获取原文
获取原文并翻译 | 示例
           

摘要

In previous urban planning research, the fine-grained population was considered a crucial factor. However, this population, which is generated from census data, represents only the number of people who live in a region. This static figure cannot indicate the underlying number of people and their temporal variation. Therefore, any decision-making based on the static population may be separated from reality. To overcome this difficulty, in this paper, the urban crowd flux is initially proposed and defined as the number of individuals flowing into or out of a region per unit time interval. Then, the urban crowd flux is estimated using an approach of human trajectory gridding reconstruction based on mobile phone location data. This approach is divided into three steps. First, the trajectory of each individual is extracted from sparse sampling of mobile phone location data after data cleansing. Then, combining with a road network, the trajectory of each individual is reconstructed by network interpolation based on the shortest path algorithm in regular grids. Third, we use the velocities of each user's trajectory record to estimate the urban crowd flux on spatio-temporal grids at each time slice. Finally, urban crowd flux in Beijing, China were estimated using our method and the spatio-temporal characteristics of flux is analyzed.
机译:在以前的城市规划研究中,细粒度的人口被认为是一个关键因素。但是,根据人口普查数据生成的人口仅代表一个地区的居住人数。这个静态数字不能表示潜在的人数和他们的时间变化。因此,任何基于静态人口的决策都可能与现实相分离。为了克服这一困难,本文首先提出了城市人群通量,并将其定义为每单位时间间隔流入或流出某个区域的人数。然后,使用基于移动电话位置数据的人体轨迹网格重构方法估算城市人群通量。此方法分为三个步骤。首先,从数据清洗后的移动电话位置数据的稀疏采样中提取每个人的轨迹。然后,结合道路网络,基于规则网格中的最短路径算法,通过网络插值法重构每个人的轨迹。第三,我们使用每个用户的轨迹记录的速度来估计每个时间片时空网格上的城市人群通量。最后,使用我们的方法估算了中国北京的城市人群通量,并分析了通量的时空特征。

著录项

  • 来源
    《Computers,environment and urban systems》 |2018年第5期|114-123|共10页
  • 作者单位

    Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China;

    Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China;

    Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China;

    Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China;

    Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China;

    Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China;

    Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Crowd flux estimation; Mobile phone location data; Trajectory reconstruction; Urban dynamics;

    机译:人群流量估计;手机位置数据;轨迹重建;城市动态;

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号