Inferring land use from spatialtemporal taxi ride data
Inferring land use from spatialtemporal taxi ride data
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DOI：
10.1016/j.apgeog.2022.102688
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发表时间：
2022-03-30
影响因子：
4.9
通讯作者：
Kim, Youngchul
中科院分区：
文献类型：
--
作者：
Choi, Junyong;No, Wonjun;Kim, Youngchul
城市空间的不同功能产生出行需求，城市出行反过来影响城市空间。尽管以往的研究局限于交通站点周围的区域，但人类集体流动模式可以揭示土地利用模式和城市结构。本文利用韩国首尔的出租车数据，探讨了城市运动与整个城市土地利用模式之间的关系。这项研究利用了出租车数据集，这些数据集不受路线和车站的限制，并且在空间和时间方面包含更精确的信息。此外，我们使用统计方法验证土地利用和旅行模式之间的联系。为了揭示出行流动模式与土地利用之间的相互作用，采用聚类方法对出租车载客量模式进行分组。每个聚类模式，然后与相应的城市背景进行分析。我们还统计验证了土地利用与格局聚类之间的关系，并显示所获得的7个聚类可以分为4种类型，并与土地利用显着相关。此外，更详细的土地利用可以分类使用出租车乘客模式的时空属性。预计拟议的方法将监测土地利用发展的变化。
Different functions of urban spaces generate travel demand, and urban travel inversely influences urban spaces. Collective human mobility patterns can reveal land use patterns and urban structure although previous studies constrained the area around transportation stations. This paper explores the relationship between urban movements and land use patterns of a whole city using taxi ridership data in Seoul, South Korea. This study takes advantages of taxi datasets that are not bounded by routes and stations and contain more precise information in terms of space and time. In addition, we verify the connection between land use and travel patterns using a statistical method. To reveal the interaction between trip mobility patterns and land use, taxi ridership patterns are grouped by a clustering method. Each clustered pattern is then analyzed with the corresponding urban context. We also statistically verify the relationship between land use and the pattern clusters, and show that the seven obtained clusters can be categorized into four types and were significantly correlated with land use. Furthermore, more detailed land use can be classified using the spatiotemporal properties of taxi ridership patterns. The proposed method is expected to monitor change in land use development.