{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T17:14:51Z","timestamp":1771521291023,"version":"3.50.1"},"reference-count":41,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2022,11,24]],"date-time":"2022-11-24T00:00:00Z","timestamp":1669248000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Central Guided Local Development of Science and Technology Project of Fujian, Fujian, China","award":["2020L3005"],"award-info":[{"award-number":["2020L3005"]}]},{"name":"Central Guided Local Development of Science and Technology Project of Fujian, Fujian, China","award":["2021H6004"],"award-info":[{"award-number":["2021H6004"]}]},{"name":"Central Guided Local Development of Science and Technology Project of Fujian, Fujian, China","award":["41801373"],"award-info":[{"award-number":["41801373"]}]},{"name":"Fujian Cooperation Project between Universities and Enterprises, Fujian, China","award":["2020L3005"],"award-info":[{"award-number":["2020L3005"]}]},{"name":"Fujian Cooperation Project between Universities and Enterprises, Fujian, China","award":["2021H6004"],"award-info":[{"award-number":["2021H6004"]}]},{"name":"Fujian Cooperation Project between Universities and Enterprises, Fujian, China","award":["41801373"],"award-info":[{"award-number":["41801373"]}]},{"name":"National Natural Science Foundation of China","award":["2020L3005"],"award-info":[{"award-number":["2020L3005"]}]},{"name":"National Natural Science Foundation of China","award":["2021H6004"],"award-info":[{"award-number":["2021H6004"]}]},{"name":"National Natural Science Foundation of China","award":["41801373"],"award-info":[{"award-number":["41801373"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>Taxi travel flow patterns and their interday stability play an important role in the planning of urban transportation and public service facilities. Existing studies pay little attention to the stability of the travel flow patterns between days, and it is difficult to consider the impact of dynamic changes in daily travel demand analysis when supporting related decision making. Taxi trajectory data have been widely used in urban taxi travel-pattern analysis. This paper uses the taxi datasets of Shenzhen and New York to analyze and compare the interday stability of the taxi travel spatial structure and the flow volume based on the improved Levenshtein algorithm and geographic flow theory. The results show that (1) interday differences in taxi travel flow are obvious in both spatial structure and flow volume, high-frequency origin\u2013destination (OD) trips are relatively stable; (2) the ODs between the central urban area and surrounding areas exhibit high traffic volume and high interday stability, and the ODs starting or ending at an airport exhibit high traffic stability; (3) one week\u2019s data can describe 86% of the overall travel structure and 84% of travel flow in Shenzhen, and one week\u2019s New York data can describe 73% of travel structure and 76% of travel flow. There are differences in the travel patterns of people in different cities, and the representativeness of datasets in different cities will be different. These findings can help to better understand the outcomes of taxi travel patterns derived from a relatively short period of data to avoid potential misuse in related decision making.<\/jats:p>","DOI":"10.3390\/ijgi11120590","type":"journal-article","created":{"date-parts":[[2022,11,25]],"date-time":"2022-11-25T03:00:13Z","timestamp":1669345213000},"page":"590","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Interday Stability of Taxi Travel Flow in Urban Areas"],"prefix":"10.3390","volume":"11","author":[{"given":"Ping","family":"Tu","sequence":"first","affiliation":[{"name":"Academy of Digital China (Fujian), Fuzhou University, Fuzhou 350108, China"},{"name":"Key Laboratory of Spatial Data Mining and Information Sharing of Ministry of Education, Fuzhou University, Fuzhou 350002, China"},{"name":"National Engineering Research Centre of Geospatial Information Technology, Fuzhou University, Fuzhou 350002, China"}]},{"given":"Wei","family":"Yao","sequence":"additional","affiliation":[{"name":"Academy of Digital China (Fujian), Fuzhou University, Fuzhou 350108, China"},{"name":"Key Laboratory of Spatial Data Mining and Information Sharing of Ministry of Education, Fuzhou University, Fuzhou 350002, China"},{"name":"National Engineering Research Centre of Geospatial Information Technology, Fuzhou University, Fuzhou 350002, China"}]},{"given":"Zhiyuan","family":"Zhao","sequence":"additional","affiliation":[{"name":"Academy of Digital China (Fujian), Fuzhou University, Fuzhou 350108, China"},{"name":"Key Laboratory of Spatial Data Mining and Information Sharing of Ministry of Education, Fuzhou University, Fuzhou 350002, China"},{"name":"National Engineering Research Centre of Geospatial Information Technology, Fuzhou University, Fuzhou 350002, China"}]},{"given":"Pengzhou","family":"Wang","sequence":"additional","affiliation":[{"name":"Academy of Digital China (Fujian), Fuzhou University, Fuzhou 350108, China"},{"name":"Key Laboratory of Spatial Data Mining and Information Sharing of Ministry of Education, Fuzhou University, Fuzhou 350002, China"},{"name":"National Engineering Research Centre of Geospatial Information Technology, Fuzhou University, Fuzhou 350002, China"}]},{"given":"Sheng","family":"Wu","sequence":"additional","affiliation":[{"name":"Academy of Digital China (Fujian), Fuzhou University, Fuzhou 350108, China"},{"name":"Key Laboratory of Spatial Data Mining and Information Sharing of Ministry of Education, Fuzhou University, Fuzhou 350002, China"},{"name":"National Engineering Research Centre of Geospatial Information Technology, Fuzhou University, Fuzhou 350002, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1651-878X","authenticated-orcid":false,"given":"Zhixiang","family":"Fang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, Wuhan 430079, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,11,24]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"272","DOI":"10.1257\/app.20190655","article-title":"Uber versus taxi: A driver\u2019s eye view","volume":"13","author":"Angrist","year":"2021","journal-title":"Am. Econ. J. Appl. Econ."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"103118","DOI":"10.1016\/j.jtrangeo.2021.103118","article-title":"Exploring the spatial impacts of human activities on urban traffic crashes using multi-source big data","volume":"94","author":"Bao","year":"2021","journal-title":"J. Transp. Geogr."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"103370","DOI":"10.1016\/j.trc.2021.103370","article-title":"A DBSCAN-based framework to mine travel patterns from origin-destination matrices: Proof-of-concept on proxy static OD from Brisbane","volume":"131","author":"Behara","year":"2021","journal-title":"Transp. Res. Part C Emerg. Technol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"513","DOI":"10.1016\/j.trc.2020.01.005","article-title":"A novel approach for the structural comparison of origin-destination matrices: Levenshtein distance","volume":"111","author":"Behara","year":"2020","journal-title":"Transp. Res. Part C Emerg. Technol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"590","DOI":"10.1016\/j.physa.2016.03.047","article-title":"Understanding taxi travel patterns","volume":"457","author":"Cai","year":"2016","journal-title":"Phys. A Stat. Mech. its Appl."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1016\/j.tranpol.2020.04.001","article-title":"Taxi hailing choice behavior and economic benefit analysis of emission reduction based on multi-mode travel big data","volume":"97","author":"Chen","year":"2020","journal-title":"Transp. Policy"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"317","DOI":"10.1111\/tgis.12849","article-title":"Recurrent origin\u2013destination network for exploration of human periodic collective dynamics","volume":"26","author":"Chen","year":"2022","journal-title":"Trans. GIS"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Cheng, T., and Adepeju, M. (2014). Modifiable Temporal Unit Problem (MTUP) and Its Effect on Space-Time Cluster Detection. PLoS ONE, 9.","DOI":"10.1371\/journal.pone.0100465"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Correa, D., Xie, K., and Ozbay, K. (2017, January 8\u201312). Exploring the Taxi and Uber Demand in New York City: An Empirical Analysis and Spatial Modeling. Proceedings of the 96th Annual Meeting of the Transportation Research Board, Washington, DC, USA.","DOI":"10.2139\/ssrn.4229042"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"7687852","DOI":"10.1155\/2018\/7687852","article-title":"Understanding the Effect of an E-Hailing App Subsidy War on Taxicab Operation Zones","volume":"2018","author":"Fang","year":"2018","journal-title":"J. Adv. Transp."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"485","DOI":"10.1007\/s10707-019-00390-x","article-title":"Geographical and temporal huff model calibration using taxi trajectory data","volume":"25","author":"Gong","year":"2021","journal-title":"GeoInformatica"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"411","DOI":"10.1111\/j.1467-9671.2012.01344.x","article-title":"Discovering Spatial Patterns in Origin-Destination Mobility Data","volume":"16","author":"Guo","year":"2012","journal-title":"Trans. GIS"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Guo, X., Xu, Z., Zhang, J., Lu, J., and Zhang, H. (2020). An OD Flow Clustering Method Based on Vector Constraints: A Case Study for Beijing Taxi Origin-Destination Data. ISPRS Int. J. Geo-Inf., 9.","DOI":"10.3390\/ijgi9020128"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"735","DOI":"10.1111\/tgis.12879","article-title":"Mining crowdsourced trajectory and geo-tagged data for spatial-semantic road map construction","volume":"26","author":"Huang","year":"2022","journal-title":"Trans. GIS"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"785","DOI":"10.1016\/j.physa.2018.09.123","article-title":"Understanding bike sharing travel patterns: An analysis of trip data from eight cities","volume":"515","author":"Kou","year":"2019","journal-title":"Phys. A Stat. Mech. Appl."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"487","DOI":"10.1016\/j.tranpol.2021.07.003","article-title":"A robust analysis of the impacts of the stay-at-home policy on taxi and Citi Bike usage: A case study of Manhattan","volume":"110","author":"Lei","year":"2021","journal-title":"Transp. Policy"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"102974","DOI":"10.1016\/j.jtrangeo.2021.102974","article-title":"Inferring the trip purposes and uncovering spatio-temporal activity patterns from dockless shared bike dataset in Shenzhen, China","volume":"91","author":"Li","year":"2021","journal-title":"J. Transp. Geogr."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"103076","DOI":"10.1016\/j.jtrangeo.2021.103076","article-title":"Beyond absolute space: An exploration of relative and relational space in Shanghai using taxi trajectory data","volume":"93","author":"Li","year":"2021","journal-title":"J. Transp. Geogr."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1007\/s11704-011-1192-6","article-title":"Prediction of urban human mobility using large-scale taxi traces and its applications","volume":"6","author":"Li","year":"2012","journal-title":"Front. Comput. Sci."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1016\/j.jtrangeo.2015.01.016","article-title":"Revealing travel patterns and city structure with taxi trip data","volume":"43","author":"Liu","year":"2015","journal-title":"J. Transp. Geogr."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"101592","DOI":"10.1016\/j.compenvurbsys.2020.101592","article-title":"Identifying and understanding road-constrained areas of interest (AOIs) through spatiotemporal taxi GPS data: A case study in New York City","volume":"86","author":"Liu","year":"2021","journal-title":"Comput. Environ. Urban Syst."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1016\/j.landurbplan.2012.02.012","article-title":"Urban land uses and traffic \u2018source-sink areas\u2019: Evidence from GPS-enabled taxi data in Shanghai","volume":"106","author":"Liu","year":"2012","journal-title":"Landsc. Urban Plan."},{"key":"ref_23","first-page":"1","article-title":"Research on the big data of traditional taxi and online car-hailing: A systematic review","volume":"8","author":"Lyu","year":"2021","journal-title":"J. Traffic Transp. Eng."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"103438","DOI":"10.1016\/j.cities.2021.103438","article-title":"Transit\u2019s downward spiral: Assessing the social-justice implications of ride-hailing platforms and COVID-19 for public transportation in the US","volume":"120","author":"Monahan","year":"2022","journal-title":"Cities"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1145\/375360.375365","article-title":"A guided tour to approximate string matching","volume":"33","author":"Navarro","year":"2001","journal-title":"ACM Comput. Surv."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1007\/s13198-021-01130-x","article-title":"New York City taxi trip duration prediction using MLP and XGBoost","volume":"13","author":"Poongodi","year":"2022","journal-title":"Int. J. Syst. Assur. Eng. Manag."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"41149","DOI":"10.1007\/s11356-021-13556-8","article-title":"COVID-19 outbreak, lockdown, and air quality: Fresh insights from New York City","volume":"28","author":"Shehzad","year":"2021","journal-title":"Environ. Sci. Pollut. Res."},{"key":"ref_28","unstructured":"Shenzhen Transportation Bureau (2021). Passenger Flow Volume of Public Transport."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"689","DOI":"10.1080\/13658816.2020.1749277","article-title":"L-function of geographical flows","volume":"35","author":"Shu","year":"2021","journal-title":"Int. J. Geogr. Inf. Sci."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1016\/j.jtrangeo.2018.04.013","article-title":"Spatial variations in urban public ridership derived from GPS trajectories and smart card data","volume":"69","author":"Tu","year":"2018","journal-title":"J. Transp. Geogr."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Kumar, T.M.V. (2022). International Collaborative Research: \u201cSmart Global Mega Cities\u201d and Conclusions of Cities Case Studies Tokyo, New York, Mumbai, Hong Kong-Shenzhen, and Kolkata. Smart Global Megacities, Springer.","DOI":"10.1007\/978-981-16-2019-5_10"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1051","DOI":"10.1007\/s11116-017-9787-x","article-title":"New potential for multimodal connection: Exploring the relationship between taxi and transit in New York City (NYC)","volume":"46","author":"Wang","year":"2019","journal-title":"Transportation"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"555","DOI":"10.1016\/j.jenvman.2018.02.026","article-title":"System dynamics model of taxi management in metropolises: Economic and environmental implications for Beijing","volume":"213","author":"Wang","year":"2018","journal-title":"J. Environ. Manag."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1080\/13658816.2014.944527","article-title":"A novel approach for generating routable road maps from vehicle GPS traces","volume":"29","author":"Wang","year":"2015","journal-title":"Int. J. Geogr. Inf. Sci."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"8008","DOI":"10.1109\/JSTARS.2021.3102320","article-title":"A Guided Deep Learning Approach for Joint Road Extraction and Intersection Detection from RS Images and Taxi Trajectories","volume":"14","author":"Li","year":"2021","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"278","DOI":"10.1111\/tgis.12851","article-title":"Road intersection identification from crowdsourced big trace data using Mask-RCNN","volume":"26","author":"Yang","year":"2022","journal-title":"Trans. GIS"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/2821507","article-title":"Identifying Region-Wide Functions Using Urban Taxicab Trajectories","volume":"15","author":"Zhang","year":"2016","journal-title":"ACM Trans. Embed. Comput. Syst."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"2840","DOI":"10.1111\/tgis.12817","article-title":"A multilayer mobility network approach to inferring urban structures using shared mobility and taxi data","volume":"25","author":"Zhang","year":"2021","journal-title":"Trans. GIS"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"72","DOI":"10.1016\/j.jtrangeo.2017.04.009","article-title":"Revealing intra-urban travel patterns and service ranges from taxi trajectories","volume":"61","author":"Zhang","year":"2017","journal-title":"J. Transp. Geogr."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Liu, J., Qian, X., Qiu, A., and Zhang, F. (2017). An Automatic Road Network Construction Method Using Massive GPS Trajectory Data. ISPRS Int. J. Geo-Inf., 6.","DOI":"10.3390\/ijgi6120400"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1016\/j.compenvurbsys.2015.03.001","article-title":"Functionally critical locations in an urban transportation network: Identification and space\u2013time analysis using taxi trajectories","volume":"52","author":"Zhou","year":"2015","journal-title":"Comput. Environ. Urban Syst."}],"container-title":["ISPRS International Journal of Geo-Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2220-9964\/11\/12\/590\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T01:26:14Z","timestamp":1760145974000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2220-9964\/11\/12\/590"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,11,24]]},"references-count":41,"journal-issue":{"issue":"12","published-online":{"date-parts":[[2022,12]]}},"alternative-id":["ijgi11120590"],"URL":"https:\/\/doi.org\/10.3390\/ijgi11120590","relation":{},"ISSN":["2220-9964"],"issn-type":[{"value":"2220-9964","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,11,24]]}}}