Delineating and modeling activity space using geotagged social media data
Delineating and modeling activity space using geotagged social media data
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DOI：
10.1080/15230406.2019.1705187
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发表时间：
2020-02-09
影响因子：
2.5
通讯作者：
Ye, Xinyue
中科院分区：
文献类型：
--
作者：
Hu, Lingqian;Li, Zhenlong;Ye, Xinyue
在空间公平研究中，了解活动空间-人们进行定期户外活动的空间-变得越来越重要。大数据可以促进活动空间的识别和对空间公平的理解。本文以洛杉矶大都市区为例，采用地理标记的Twitter数据，通过两种空间度量来描绘活动空间：第一，用户家庭位置与活动位置之间的平均距离;第二，家庭与活动位置之间的覆盖面积。研究还发现，活动空间的空间尺度与邻里空间特征和社会经济特征之间存在显著的相关性。这项研究丰富了旨在解决活动空间空间公平问题的文献，并展示了大数据在城市社会空间研究中的适用性。
It has become increasingly important in spatial equity studies to understand activity spaces - where people conduct regular out-of-home activities. Big data can advance the identification of activity spaces and the understanding of spatial equity. Using the Los Angeles metropolitan area for the case study, this paper employs geotagged Twitter data to delineate activity spaces with two spatial measures: first, the average distance between users' home location and activity locations; and second, the area covered between home and activity locations. The paper also finds significant relationship between the spatial measures of activity spaces and neighborhood spatial and socioeconomic characteristics. This research enriches the literature that aims to address spatial equity in activity spaces and demonstrates the applicability of big data in urban socio-spatial research.