• Journal of Geo-information Science
  • Vol. 22, Issue 4, 805 (2020)
Jiaoe WANG1、1, Fangye DU1、1、2、2、*, Haitao JIN3、3, and Yu LIU4、4
Author Affiliations
  • 1Key Laboratory of Regional Sustainable Development Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
  • 1中国科学院地理科学与资源研究所 中国科学院区域可持续发展分析与模拟重点实验室,北京 100101
  • 2College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
  • 2中国科学院大学资源与环境学院,北京 100049
  • 3School of Computer, Beijing Information Science and Technology University, Beijing 100085, China
  • 3北京信息科技大学计算机学院,北京 100085
  • 4School of Electronics Engineering and Computer Science, Peking University, Beijing 100871, China
  • 4北京大学遥感与地理信息系统研究所,北京 100871
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    DOI: 10.12082/dqxxkx.2020.190566 Cite this Article
    Jiaoe WANG, Fangye DU, Haitao JIN, Yu LIU. Identifying Hospital-seeking Behavior based on Trip Chain Data: Theoretical Framework and Methodological System[J]. Journal of Geo-information Science, 2020, 22(4): 805 Copy Citation Text show less
    Sketch of space-time path of hospital-seeking behavior
    Fig. 1. Sketch of space-time path of hospital-seeking behavior
    Theorical framework for detecting hospital-seeking behavior
    Fig. 2. Theorical framework for detecting hospital-seeking behavior
    Methodology for detecting hospital-seeking behavior from smart card data
    Fig. 3. Methodology for detecting hospital-seeking behavior from smart card data
    Methodology for detecting hospital-seeking behavior from taxi GPS data
    Fig. 4. Methodology for detecting hospital-seeking behavior from taxi GPS data
    Spatial distribution of hospitals within Beijing's sixth ring road in 2017
    Fig. 5. Spatial distribution of hospitals within Beijing's sixth ring road in 2017
    Threshold of transit time
    Fig. 6. Threshold of transit time
    Relationship between interval time and the number of bus passengers
    Fig. 7. Relationship between interval time and the number of bus passengers
    Flowchart of detecting hospital-seeking behavior with smart card data
    Fig. 8. Flowchart of detecting hospital-seeking behavior with smart card data
    Changes in the number of drop-off and pick-up points by the distance to hospital entrances
    Fig. 9. Changes in the number of drop-off and pick-up points by the distance to hospital entrances
    Distribution of patients' arrival time
    Fig. 10. Distribution of patients' arrival time
    个体编号上车点位置上车时间下车点位置下车时间
    公交IC卡刷卡数据
    出租车GPS数据
    Table 1. Data structure of smart card data and taxi GPS data
    卡号上车站点站点经度/°E站点纬度/°N上车时间下车站点站点经度/°E站点纬度/°N下车时间
    0002酒仙桥116.48939.9682017-06-0510:44:00首钢医院116.204E39.927N2017-06-0511:42:00
    Table 2. Sample of smart card data records
    IDO点经度/°EO点纬度/°ND点经度/°ED点纬度/°N
    0000012116.52339.852116.54239.921
    Table 3. Table of taxi OD data
    就医者数量/人交通出行时间/min就医时长/min
    公交车出租车公交车出租车公交车
    均值标准差均值标准差均值标准差均值标准差均值标准差
    所有医院220231.1441959.621.116.718.713.4138.256.7
    三级医院433321.515201575.922.517.319.113.8142.459.8
    二级医院271217.7287245.820.917.018.012.8139.358.2
    一级医院114116.188130.919.715.817.011.4133.352.5
    Table 4. Statistics of hospital-seeking behavior
    Jiaoe WANG, Fangye DU, Haitao JIN, Yu LIU. Identifying Hospital-seeking Behavior based on Trip Chain Data: Theoretical Framework and Methodological System[J]. Journal of Geo-information Science, 2020, 22(4): 805
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