{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,10]],"date-time":"2026-02-10T08:39:54Z","timestamp":1770712794291,"version":"3.49.0"},"reference-count":44,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2022,3,15]],"date-time":"2022-03-15T00:00:00Z","timestamp":1647302400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2018YFB0505304"],"award-info":[{"award-number":["2018YFB0505304"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The study of patterns of crowd flows represents an emerging and expanding research field. The most straightforward and efficient approach to investigate the patterns of crowd flows is to concentrate on traffic flow. However, assessments of simple point-to-point movement frequently lack universal validity, and little research has been conducted on the regularity of nighttime movement. Due to the suspension of public transportation at night, taxi orders are critical in capturing the features of nighttime crowd flows in a tourism city. Using Haikou as an example, this paper proposes a mixed Geogrid Spatio-temporal model (MG-STM) for the tourism city in order to address the challenges. Firstly, by collecting the pick-up\/drop-off\/in-out flow of crowds, this research uses DCNMF dimensionality reduction to extract semi-supervised spatio-temporal variation features and the K-Means clustering method to determine the cluster types of nighttime crowd flows\u2019 changes in each geogrid. Secondly, by constructing a mixed-evaluation model based on LJ1-01 nighttime light data, crowd flows\u2019 clusters, and land use data in geogrid-based regions, the pattern of nighttime crowd flows in urban land use areas is successfully determined. The results suggest that MG-STM can estimate changes in the number of collective flows in various regions of Haikou effectively and appropriately. Moreover, population density of land use areas shows a high positive correlation with the lag of crowd flows. Each 5% increase in population density results in a 30-min delay in the peak of crowd flows. The MG-STM will be extremely beneficial in developing and implementing systems for criminal tracking and pandemic prevention.<\/jats:p>","DOI":"10.3390\/rs14061413","type":"journal-article","created":{"date-parts":[[2022,3,16]],"date-time":"2022-03-16T03:36:23Z","timestamp":1647401783000},"page":"1413","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Patterns of Nighttime Crowd Flows in Tourism Cities Based on Taxi Data\u2014Take Haikou Prefecture as an Example"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4890-7563","authenticated-orcid":false,"given":"Bing","family":"Han","sequence":"first","affiliation":[{"name":"Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4351-2359","authenticated-orcid":false,"given":"Daoye","family":"Zhu","sequence":"additional","affiliation":[{"name":"Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China"},{"name":"Center for Geographic Analysis, Harvard University, Cambridge, MA 02138, USA"}]},{"given":"Chengqi","family":"Cheng","sequence":"additional","affiliation":[{"name":"Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China"},{"name":"College of Engineering, Peking University, Beijing 100871, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0415-1562","authenticated-orcid":false,"given":"Jiawen","family":"Pan","sequence":"additional","affiliation":[{"name":"College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China"},{"name":"Key Laboratory of Agricultural Machinery Monitoring and Big Data Applications, Ministry of Agriculture and Rural Affairs, Beijing 100083, China"}]},{"given":"Weixin","family":"Zhai","sequence":"additional","affiliation":[{"name":"College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China"},{"name":"Key Laboratory of Agricultural Machinery Monitoring and Big Data Applications, Ministry of Agriculture and Rural Affairs, Beijing 100083, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,3,15]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Ali, A., Zhu, Y., Chen, Q., Yu, J., and Cai, H. 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