{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,7]],"date-time":"2026-04-07T22:44:33Z","timestamp":1775601873584,"version":"3.50.1"},"reference-count":46,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2019,1,23]],"date-time":"2019-01-23T00:00:00Z","timestamp":1548201600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the National Key R&amp;D Program of China","award":["2017YFB0503604, 2016YFE0200400"],"award-info":[{"award-number":["2017YFB0503604, 2016YFE0200400"]}]},{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["Nos. 41671442, 41571430, 41271442"],"award-info":[{"award-number":["Nos. 41671442, 41571430, 41271442"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"the Joint Foundation of Ministry of Education of China","award":["6141A02022341"],"award-info":[{"award-number":["6141A02022341"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The design of urban clusters has played an important role in urban planning, but realizing the construction of these urban plans is quite a long process. Hence, how the progress is evaluated is significant for urban managers in the process of urban construction. Traditional methods for detecting urban clusters are inaccurate since the raw data is generally collected from small sample questionnaires of resident trips rather than large-scale studies. Spatiotemporal big data provides a new lens for understanding urban clusters in a natural and fine-grained way. In this article, we propose a novel method for Detecting and Evaluating Urban Clusters (DEUC) with taxi trajectories and Sina Weibo check-in data. Firstly, DEUC applies an agglomerative hierarchical clustering method to detect urban clusters based on the similarities in the daily travel space of urban residents. Secondly, DEUC infers resident demands for land-use functions using a na\u00efve Bayes\u2019 theorem, and three indicators are adopted to assess the rationality of land-use functions in the detected clusters\u2014namely, cross-regional travel index, commuting direction index, and fulfilled demand index. Thirdly, DEUC evaluates the progress of urban cluster construction by calculating a proposed conformance indicator. In the case study, we applied our method to detect and analyze urban clusters in Wuhan, China in the years 2009, 2014, and 2015. The results suggest the effectiveness of the proposed method, which can provide a scientific basis for urban construction.<\/jats:p>","DOI":"10.3390\/s19030461","type":"journal-article","created":{"date-parts":[[2019,1,24]],"date-time":"2019-01-24T03:52:32Z","timestamp":1548301952000},"page":"461","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":22,"title":["Detecting and Evaluating Urban Clusters with Spatiotemporal Big Data"],"prefix":"10.3390","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3523-8994","authenticated-orcid":false,"given":"Luliang","family":"Tang","sequence":"first","affiliation":[{"name":"State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, Wuhan 430079, China"}]},{"given":"Jie","family":"Gao","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, Wuhan 430079, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1760-0865","authenticated-orcid":false,"given":"Chang","family":"Ren","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, Wuhan 430079, China"}]},{"given":"Xia","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Urban Design, Wuhan University, Wuhan 430070, China"}]},{"given":"Xue","family":"Yang","sequence":"additional","affiliation":[{"name":"Faculty of Information Engineering, China University of Geosciences, Wuhan 430074, China"}]},{"given":"Zihan","family":"Kan","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":[[2019,1,23]]},"reference":[{"key":"ref_1","first-page":"4","article-title":"Analysis on the Impact of Urban Clustered Land Use on Resident Travel Spatial Distribution\u2014A Case Study of Changzhou City","volume":"2016","author":"Hu","year":"2016","journal-title":"Urban Roads Bridges Flood Control"},{"key":"ref_2","first-page":"70","article-title":"Analysis on the Change Tendency of Group City\u2019s Residential Trip Characteristics","volume":"6","author":"Li","year":"2008","journal-title":"J. Trans. Syst. Eng. Inf. Technol."},{"key":"ref_3","first-page":"86","article-title":"Analysis the car trip characteristics of clustered city","volume":"3","author":"Wan","year":"2007","journal-title":"Urban Plan. Forum"},{"key":"ref_4","first-page":"92","article-title":"Group City\u2019s Resident Trip Time Consume Characteristic","volume":"32","author":"Fang","year":"2005","journal-title":"J. Trans. Eng. Inf."},{"key":"ref_5","unstructured":"Zou, D. (2011). Introduction to Urban Planning, China Architecture & Building Press."},{"key":"ref_6","first-page":"489","article-title":"Another Tale of Two Cities: Understanding Human Activity Space Using Actively Tracked Cellphone Location Data","volume":"106","author":"Xu","year":"2016","journal-title":"Ann. Am. Assoc. Geogr."},{"key":"ref_7","first-page":"861","article-title":"Research Progress and Prospects of the Researches on Urban Land Use Structure in China","volume":"29","author":"Lu","year":"2010","journal-title":"Prog. Geogr."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1717","DOI":"10.1080\/13658816.2015.1119279","article-title":"A network kernel density estimation for linear features in space\u2013time analysis of big trace data","volume":"30","author":"Tang","year":"2016","journal-title":"Int. J. Geogr. Inf. Sci."},{"key":"ref_9","first-page":"1871","article-title":"Integrating multi-source big data to infer building functions","volume":"31","author":"Niu","year":"2017","journal-title":"Int. J. Geogr. Inf. Sci."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"8710402","DOI":"10.1155\/2018\/8710402","article-title":"Supervised land use inference from mobility patterns","volume":"2018","author":"Caceres","year":"2018","journal-title":"J. Adv. Trans."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"597","DOI":"10.1007\/s11116-015-9598-x","article-title":"Discovering urban activity patterns in cell phone data","volume":"42","author":"Widhalm","year":"2015","journal-title":"Transportation"},{"key":"ref_12","unstructured":"Soto, V. (July, January 28). Automated land use identification using cell-phone records. Proceedings of the 6th ACM International Workshop on Mobiarch, New York, NY, USA."},{"key":"ref_13","first-page":"665","article-title":"Research on Human Mobility in Big Data Era","volume":"16","author":"Lu","year":"2014","journal-title":"J. Geo-Inf. Sci."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"2331","DOI":"10.1080\/13658816.2017.1356464","article-title":"Coupling mobile phone and social media data: A new approach to understanding urban functions and diurnal patterns","volume":"31","author":"Tu","year":"2017","journal-title":"Int. J. Geogr. Inf. Sci."},{"key":"ref_15","first-page":"34","article-title":"Spatiotemporal characterization of user behaviors based on micro-blog data mining","volume":"41","author":"Liang","year":"2016","journal-title":"Sci. Surv. Map."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Encalada, L., Boavida-Portugal, I., Cardoso Ferreira, C., and Rocha, J. (2017). Identifying Tourist Places of Interest Based on Digital Imprints: Towards a Sustainable Smart City. Sustainability, 9.","DOI":"10.3390\/su9122317"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Kuo, C., Chan, T., Fan, I., and Zipf, A. (2018). Efficient Method for POI\/ROI Discovery Using Flickr Geotagged Photos. ISPRS Int. J. Geo-Inf., 7.","DOI":"10.3390\/ijgi7030121"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"720","DOI":"10.1080\/13658816.2014.977905","article-title":"Crowdsourcing urban form and function","volume":"29","author":"Crooks","year":"2015","journal-title":"Int. J. Geogr. Inf. Sci."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"3033","DOI":"10.3390\/s90403033","article-title":"Sensing human activity: GPS tracking","volume":"9","author":"Spek","year":"2009","journal-title":"Sensors"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1018","DOI":"10.1126\/science.1177170","article-title":"Limits of predictability in human mobility","volume":"327","author":"Song","year":"2010","journal-title":"Science"},{"key":"ref_21","first-page":"938","article-title":"A review on the classification, patterns and applied research of human mobility trajectory","volume":"33","author":"Li","year":"2014","journal-title":"Prog. Geogr."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"641","DOI":"10.1111\/tgis.12056","article-title":"Applied urban modeling: New types of spatial data provide a catalyst for new models","volume":"17","author":"Jin","year":"2013","journal-title":"Trans. GIS"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"274","DOI":"10.1177\/2043820613513390","article-title":"Big data, smart cities and city planning","volume":"3","author":"Batty","year":"2013","journal-title":"Dialogues Hum. Geogr."},{"key":"ref_24","first-page":"1136","article-title":"A Review on the Application Research of Trajectory Data Mining in Urban Cities","volume":"17","author":"Mou","year":"2015","journal-title":"J. Geo-Inf. Sci."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1109\/MPRV.2009.62","article-title":"Eigenplaces: Segmenting space through digital signatures","volume":"9","author":"Calabrese","year":"2009","journal-title":"IEEE Pervasive Comput."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"649","DOI":"10.1080\/17445647.2015.1060177","article-title":"Analytical material for planning in Olomouc, Czech Republic","volume":"12","author":"Burian","year":"2016","journal-title":"J. Maps"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"2881","DOI":"10.3390\/S7112881","article-title":"Tempo-spatial patterns of land use changes and urban development in globalizing China: A study of Beijing","volume":"7","author":"Xie","year":"2007","journal-title":"Sensors"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1988","DOI":"10.1080\/13658816.2014.913794","article-title":"A new insight into land use classification based on aggregated mobile phone data","volume":"28","author":"Pei","year":"2013","journal-title":"Int. J. Geogr. Inf. Sci."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"103","DOI":"10.1080\/15230406.2015.1014424","article-title":"Inferring trip purposes and uncovering travel patterns from taxi trajectory data","volume":"43","author":"Gong","year":"2015","journal-title":"Cartogr. Geogr. Inf. Sci."},{"key":"ref_30","unstructured":"Soto, V., and Fr\u00edas-Mart\u00ednez, E. (2011, January 12\u201315). Robust Land Use Characterization of Urban Lanscapes using Cell Phone Data. Proceedings of the First Workshop on Pervasive Urban Applications, San Francisco, CA, USA."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Frias-Martinez, V., Soto, V., Hohwald, H., and Frias-Martinez, E. (2013, January 3\u20135). Characterizing Urban Landscapes Using Geolocated Tweets. Proceedings of the IEEE International Conference on Privacy, Security, Risk and Trust, Amsterdam, The Netherlands.","DOI":"10.1109\/SocialCom-PASSAT.2012.19"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Toole, J.L., Ulm, M., Gonz\u00e1lez, M.C., and Bauer, D. (2012, January 12). Inferring land use from mobile phone activity. Proceedings of the ACM SIGKDD International Workshop on Urban Computing, Beijing, China.","DOI":"10.1145\/2346496.2346498"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1016\/j.landurbplan.2016.12.001","article-title":"Delineating urban functional areas with building-level social media data: A dynamic time warping (DTW) distance based k-medoids method","volume":"160","author":"Chen","year":"2017","journal-title":"Landsc. Urban Plan."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Wang, Y., Wang, T., Tsou, M.H., Li, H., Jiang, W., and Guo, F. (2016). Mapping dynamic urban land use patterns with crowdsourced geo-tagged social media (Sina-Weibo) and commercial points of interest collections in Beijing, China. Sustainability, 8.","DOI":"10.3390\/su8111202"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Wang, Y., Gu, Y., Dou, M., and Qiao, M. (2018). Using Spatial Semantics and Interactions to Identify Urban Functional Regions. ISPRS Int. J. Geo-Inf., 7.","DOI":"10.3390\/ijgi7040130"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Wang, S., Xu, G., and Guo, Q. (2018). Street Centralities and Land Use Intensities Based on Points of Interest (POI) in Shenzhen, China. ISPRS Int. J. Geo-Inf., 7.","DOI":"10.3390\/ijgi7110425"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"625","DOI":"10.1007\/s11116-015-9597-y","article-title":"Understanding aggregate human mobility patterns using passive mobile phone location data: A home-based approach","volume":"42","author":"Xu","year":"2015","journal-title":"Transportation"},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Kong, X., Liu, Y., Wang, Y., Tong, D., and Zhang, J. (2017). Investigating public facility characteristics from a spatial interaction perspective: A case study of Beijing hospitals using taxi data. ISPRS Int. J. Geo-Inf., 6.","DOI":"10.3390\/ijgi6020038"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1021","DOI":"10.14358\/PERS.69.9.1021","article-title":"A Housing-Unit-Level Approach to Characterizing Residential Sprawl","volume":"69","author":"Hasse","year":"2003","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_40","unstructured":"Li, M. (2008, January 19\u201321). Research on pedestrian accessibility and scope of metro station services. Proceedings of the China Annual Meeting of Urban Planning, Dalian, China."},{"key":"ref_41","first-page":"314","article-title":"Urban Hotpot and Commercial Area Exploration with Check-in Data","volume":"43","author":"Hu","year":"2014","journal-title":"Acta Geod. Cart. Sin."},{"key":"ref_42","first-page":"1481","article-title":"Labeling Residential Community Characteristics from Collective Activity Patterns Using Taxi Trip Data","volume":"XLII-2","author":"Zhou","year":"2017","journal-title":"ISPRS Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Rodr\u00edguez, J., Semanjski, I., Gautama, S., Weghe, N.V.D., and Ochoa, D. (2018). Unsupervised Hierarchical Clustering Approach for Tourism Market Segmentation Based on Crowdsourced Mobile Phone Data. Sensors, 18.","DOI":"10.3390\/s18092972"},{"key":"ref_44","unstructured":"Han, J., Pei, J., and Kamber, M. (2006). Data Mining: Concepts and Techniques, China Machine Press."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1111\/j.1469-8137.1912.tb05611.x","article-title":"The distribution of the flora in the alpine zone","volume":"11","author":"Jaccard","year":"1912","journal-title":"New Phytol."},{"key":"ref_46","unstructured":"Wuhan Municipal Government (2018, November 06). Comprehensive Planning of Wuhan (2010\u20132020), Available online: http:\/\/gtghj.wuhan.gov.cn\/pc-0-61109.html."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/3\/461\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T12:28:09Z","timestamp":1760185689000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/3\/461"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,1,23]]},"references-count":46,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2019,2]]}},"alternative-id":["s19030461"],"URL":"https:\/\/doi.org\/10.3390\/s19030461","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,1,23]]}}}