地球信息科学学报 ›› 2020, Vol. 22 ›› Issue (4): 805-815.doi: 10.12082/dqxxkx.2020.190566
收稿日期:
2019-09-30
修回日期:
2019-11-06
出版日期:
2020-04-25
发布日期:
2020-06-10
通讯作者:
杜方叶
E-mail:dufy.18b@igsnrr.ac.cn
作者简介:
王姣娥(1981— ),女,湖南涟源人,博士,研究员,主要从事交通地理与区域发展、城市交通大数据等研究。E-mail:wangjiaoe@163.com
基金资助:
WANG Jiaoe1, DU Fangye1,2,*(), JIN Haitao3, LIU Yu4
Received:
2019-09-30
Revised:
2019-11-06
Online:
2020-04-25
Published:
2020-06-10
Contact:
DU Fangye
E-mail:dufy.18b@igsnrr.ac.cn
Supported by:
摘要:
交通是人们实现出行目的的重要工具和载体,也是研究城市居民出行目的的重要手段。本文试图采用交通出行数据来识别就医活动目的的行程,以深化交通大数据研究的应用领域。在合并交通出行链的基础上,构建了就医活动识别的理论框架和方法体系,提出6大准则:邻近性准则、出行链闭合准则、单一出行目的准则、时间耦合性准则、路径偶发准则。以北京市为例,基于公交车刷卡和出租车GPS数据,明确就医出行的关键参数与阈值,最终甄别出以就医为目的的交通出行链,并对识别结果进行分析与验证。基于交通出行链的就医活动识别研究可以弥补传统研究中病例数据和问卷数据样本量小和难获取的不足,为就医活动研究提供了新的方法体系,也为基于其他交通出行目的识别研究提供理论和方法借鉴。
王姣娥, 杜方叶, 靳海涛, 刘瑜. 基于交通出行链的就医活动识别理论框架与方法体系[J]. 地球信息科学学报, 2020, 22(4): 805-815.DOI:10.12082/dqxxkx.2020.190566
WANG Jiaoe, DU Fangye, JIN Haitao, LIU Yu. Identifying Hospital-seeking Behavior based on Trip Chain Data: Theoretical Framework and Methodological System[J]. Journal of Geo-information Science, 2020, 22(4): 805-815.DOI:10.12082/dqxxkx.2020.190566
表4
就医活动识别结果的统计特征"
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 | 220 | 231.1 | 441 | 959.6 | 21.1 | 16.7 | 18.7 | 13.4 | 138.2 | 56.7 |
三级医院 | 433 | 321.5 | 1520 | 1575.9 | 22.5 | 17.3 | 19.1 | 13.8 | 142.4 | 59.8 |
二级医院 | 271 | 217.7 | 287 | 245.8 | 20.9 | 17.0 | 18.0 | 12.8 | 139.3 | 58.2 |
一级医院 | 114 | 116.1 | 88 | 130.9 | 19.7 | 15.8 | 17.0 | 11.4 | 133.3 | 52.5 |
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