Conventional urban park categorizations often rely on size, environmental characteristics, and historical background, ignoring visitor characteristics due to a lack of empirical data. This study uses mobile phone data and distance-based cluster analysis to classify eighty-five urban parks in Tokyo, revealing four distinct categories based on visitor behavior, particularly home-park distance and visit frequency. The new categories revealed that proportions of visitor types varied considerably across the sample parks. There also existed notable mismatches between the administrative categories and the newly derived categories. Furthermore, the findings imply that non-uniform park management strategies, not limited by conventional park categories, are needed.
ChenY.LiuX.GaoW.WangR. Y.LiY.TuW.2018. “Emerging Social Media Data on Measuring Urban Park Use.” Urban Forestry & Urban Greening31:130–41. doi:10.1016/j.ufug.2018.02.005.
4.
Committee for the Publication of “Urban Parks in Japan,” ed. 2005. 日本の都市公園: その整備の歴史 [Urban Parks in Japan: The History of Construction and Maintenance]. Tokyo, Japan: Intarakushon/Kankyo Ryokuka Shimbun.
5.
DonahueM. L.KeelerB. L.WoodS. A.FisherD. M.HamsteadZ. A.McPhearsonT.2018. “Using Social Media to Understand Drivers of Urban Park Visitation in the Twin Cities, MN.” Landscape and Urban Planning175:1–10. doi:10.1016/j.landurbplan.2018.02.006.
GuanC.SongJ.KeithM.AkiyamaY.ShibasakiR.SatoT.2020. “Delineating Urban Park Catchment Areas Using Mobile Phone Data: A Case Study of Tokyo.” Computers, Environment and Urban Systems81:101474. doi:10.1016/j.compenvurbsys.2020.101474.
8.
GuanC.ZhouY.2024. “Exploring Environmental Equity and Visitation Disparities in Peri-urban Parks: A Mobile Phone Data-driven Analysis in Tokyo.” Landscape and Urban Planning248:105104. doi:10.1016/j.landurbplan.2024.105104.
9.
IshikawaK.2001. Cities and Green Space. Tokyo, Japan: Iwanami Shoten.
10.
JaungW.CarrascoL. R.2021. “Using Mobile Phone Data to Examine Weather Impacts on Recreational Ecosystem Services in an Urban Protected Area.” Scientific Reports11 (1): 1–11. doi:0.1038/s41598-021-85185-7.
11.
KawabataM.AbeY.2018. “Intra-metropolitan Spatial Patterns of Female Labor Force Participation and Commute Times in Tokyo.” Regional Science and Urban Economics68:291–303. doi:10.1016/j.regsciurbeco.2017.11.003.
12.
KawabataM.ShenQ.2006. “Job Accessibility as an Indicator of Auto-oriented Urban Structure: A Comparison of Boston and Los Angeles with Tokyo.” Environment and Planning B: Planning and Design33 (1): 115–30. doi:10.1068/b31144.
LiF.LiF.LiS.LongY.2020. “Deciphering the Recreational Use of Urban Parks: Experiments Using Multi-source Big Data for All Chinese Cities.” Science of the Total Environment701:134896. doi:10.1016/j.scitotenv.2019.13489.
15.
Loukaitou-SiderisA.Levy-StormsL.ChenL.BrozenM.2016. “Parks for an Aging Population: Needs and Preferences of Low-income Seniors in Los Angeles.” Journal of American Planning Association82 (3): 236–51. doi:10.1080/01944363.2016.1163238.
16.
LyuF.ZhangL.2019. “Using Multi-source Big Data to Understand the Factors Affecting Urban Park Use in Wuhan.” Urban Forestry & Urban Greening43:126367. doi:10.1016/j.ufug.2019.126367.
17.
MerrillN.AtkinsonS.MulvaneyK.MazzottaM.BousquinJ.2020. “Using Data Derived from Cellular Phone Locations to Estimate Visitation to Natural Areas: An Application to Water Recreation in New England, USA.” PLoS ONE15 (4): e0231863. doi:10.1371/journal.pone.0231863.
Park Foundation Park Management Operation Research Center, ed. 2016. 公園管理ガイドブック: 公園管理運営のための必携書 [Park Management Guidebook]. Tokyo: Park Foundation Park Management and Operation Research Center.
20.
PayneL. L.MowenA. J.Orsega-SmithE.2002. “An Examination of Park Preferences and Behaviors among Urban Residents: The Role of Residential Location, Race, and Age.” Leisure Sciences24 (2): 181–98. doi:10.1080/01490400252900149.
21.
RenX.GuanC.WangD.YangJ.ZhangB.KeithM.2022. “Exploring Land Use Functional Variance Using Mobile Phone Derived Human Activity Data in Shanghai.” Environment and Planning B: Urban Analytics and City Science49:2531–47. doi:10.1177/23998083221103261.
22.
SanesiG.ChiarelloF.2006. “Residents and Urban Green Spaces: The Case of Bari.” Urban Forestry & Urban Greening4 (34): 125–34. doi:10.1016/j.ufug.2005.12.001.
23.
SchipperjinJ.EkholmO.StigsdotterU. K.ToftagerM.BentsenP.Kamper-JørgensenF.RandrupT. B.2010. “Factors Influencing the Use of Green Space: Results from a Danish National Representative Survey.” Landscape and Urban Planning95 (3): 130–37. doi:10.1016/j.landurbplan.2009.12.010.
24.
ShinY.2004. Urban Park Policy Development History (都市公園政策形成史: 協働型社会における緑とオープンスペースの原点). Tokyo, Japan: Hosei Daigaku Shuppankyoku.
25.
SongH.ShimC.2021. “Comparing Resident and Tourist Perceptions of an Urban Park: A Latent Profile Analysis of Perceived Place Value.” Journal of Sustainable Tourism29 (7): 1180–92. doi:10.1080/09669582.2021.1872586.
VealA. J.2013. “Open Space Planning Standards in Australia: In Search of Origins.” Australian Planner50 (3): 224–32. doi:10.1080/07293682.2012.739567.
Supplementary Material
Please find the following supplemental material available below.
For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.
For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.
