{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,5]],"date-time":"2025-12-05T12:29:48Z","timestamp":1764937788246,"version":"build-2065373602"},"reference-count":45,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2024,8,21]],"date-time":"2024-08-21T00:00:00Z","timestamp":1724198400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Research Grant of Kwangwoon University"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Systems"],"abstract":"<jats:p>Research on capturing human mobility patterns for efficient and sustainable urban planning has been widely conducted. However, studies that unveil spatial context beyond macro-level mobility patterns are relatively scarce. This study aims to analyze the spatiotemporal human meta-mobility patterns with rich context using POI data in Seoul from comprehensive perspectives. As a result, the floating population of Seoul exhibits regular and irregular cyclical mobility patterns on weekdays and weekends, respectively, stemming from the periodicity of the dominant POIs. Additionally, graph construction based on mobility similarity and their regional clustering show clusters vary by POIs but are generally divided into peripheral and central regions of Seoul. This indicates that socioeconomic factors cannot be ignored when understanding human mobility patterns. This helps to provide scientific evidence to support policy recommendations towards greenways and sustainable urban mobility systems, such as quantitative disparity of greenways, qualitative issues of greenways in the central areas, and inequality in cultural consumption. Addressing key considerations through targeted policies could significantly improve the overall quality of life for urban residents. We expect this study to lay the groundwork for future research that aims to understand realistic human mobility patterns with a rich context.<\/jats:p>","DOI":"10.3390\/systems12080313","type":"journal-article","created":{"date-parts":[[2024,8,22]],"date-time":"2024-08-22T04:26:57Z","timestamp":1724300817000},"page":"313","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Decoding Urban Dynamics: Contextual Insights from Human Meta-Mobility Patterns"],"prefix":"10.3390","volume":"12","author":[{"given":"Seokjoon","family":"Oh","sequence":"first","affiliation":[{"name":"Department of Big Data Analytics, Graduate School, Kyung Hee University, Seoul 02447, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-1895-8804","authenticated-orcid":false,"given":"Seungyoung","family":"Joo","sequence":"additional","affiliation":[{"name":"Department of Big Data Analytics, Graduate School, Kyung Hee University, Seoul 02447, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2891-7537","authenticated-orcid":false,"given":"Soohwan","family":"Kim","sequence":"additional","affiliation":[{"name":"School of Information Convergence, College of AI Convergence, Kwangwoon University, Seoul 01897, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8292-7851","authenticated-orcid":false,"given":"Minkyoung","family":"Kim","sequence":"additional","affiliation":[{"name":"Department of Big Data Analytics, School of Management, Kyung Hee University, Seoul 02447, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,8,21]]},"reference":[{"key":"ref_1","unstructured":"Lee, C., and Botto, K. 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