Location-aware technologies and big data are transforming the ways we capture and analyze human activities. This has particularly affected tourism geography, which aims to study tourist activities within the context of space and places. In this study, we argue that the tourism geography of cities can be better understood through the time use of tourists captured by fine-grained human mobility observations. By using a large-scale mobile phone data set collected in three cities in South Korea (Gangneung, Jeonju, and Chuncheon), we develop a computational framework to enable accurate quantification of tourist time use, the visualization of their spatiotemporal activity patterns, and systematic comparisons across cities. The framework consists of several approaches for the extraction and semantic labeling of tourist activities, visual-analytic tools (time use diagram, time–activity diagram) for examining their time use, as well as quantitative measures that facilitate day-to-day comparisons. The feasibility of the framework is demonstrated by performing a comparative analysis in three cities during representative days when tourists tended to show more regular patterns. The framework is also employed to examine tourist time use during special events, using Gangneung during the 2018 Winter Olympics (WO) as an example. The findings are validated by comparing the spatiotemporal patterns with the WO calendar of events. The study provides a new perspective that connects time geography and tourism through the usage of spatiotemporal big data. The computational framework can be applied to compatible data sets to advance time geography, tourism, and urban mobility research.

位置感知技术和大数据正在改变我们捕捉和分析人类活动的方式。这尤其影响了旅游地理学，它旨在研究空间和地方背景下的旅游活动。在这项研究中，我们认为可以通过细粒度的人类流动观察捕获的游客的时间使用来更好地理解城市的旅游地理。通过使用在韩国三个城市（江陵、全州和春川）收集的大规模手机数据集，我们开发了一个计算框架，能够准确量化旅游时间的使用、他们的时空活动模式的可视化以及系统的不同城市的比较。该框架由几种旅游活动的提取和语义标记方法组成，用于检查他们的时间使用情况的视觉分析工具（时间使用图、时间-活动图），以及促进日常比较的定量测量。该框架的可行性通过在三个城市的代表性日子里进行比较分析来证明，这些日子游客往往表现出更规律的模式。该框架还用于检查特殊活动期间的旅游时间使用情况，以 2018 年冬季奥运会 (WO) 期间的江陵为例。通过将时空模式与 WO 事件日历进行比较来验证研究结果。该研究通过使用时空大数据提供了连接时间地理和旅游的新视角。该计算框架可应用于兼容的数据集，以推进时间地理、旅游和城市交通研究。