Spatiotemporal Heterogeneity of Metro Station Area Vitality and Driving Mechanisms of Built Environment Using Multi-Source Data Fusion: A Case Study of Shanghai City.
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| Title: | Spatiotemporal Heterogeneity of Metro Station Area Vitality and Driving Mechanisms of Built Environment Using Multi-Source Data Fusion: A Case Study of Shanghai City. |
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| Authors: | Ou, Zhiyue1 ozy20230312@163.com, Fu, Zhongning2 fuzhongning@163.com, Tong, Dongdong1 3514966755@qq.com, Yang, Xiangfei2 yangxfei06@163.com, Bai, Yue1 2413475237@qq.com |
| Source: | IAENG International Journal of Applied Mathematics. Oct2025, Vol. 55 Issue 10, p3446-3462. 17p. |
| Subjects: | Built environment, Transit-oriented development, Subway stations, Urban planning, Multisensor data fusion, Cities & towns, Spatiotemporal processes |
| Geographic Terms: | Shanghai (China) |
| Abstract: | Accurately identifying the spatiotemporal driving mechanisms through which the built environment influences metro station area vitality is critical for advancing the coordinated development of urban human-land systems. Taking Shanghai--a representative megacity--as the case study, this research quantifies weekend station area vitality using Baidu heatmap data. A comprehensive built environment indicator system is constructed by integrating multi-source datasets, including points of interest (POIs), urban road networks, and streetscape imagery. To investigate the dynamic patterns and underlying drivers of vitality across spatial and temporal dimensions, this study employs a combination of Exploratory Spatiotemporal Data Analysis (ESTDA), Optimal-Parameter Geographic Detector (OPGD), and Spatiotemporal Geographically Weighted Regression (GTWR). The results indicate that station area vitality demonstrates strong migratory inertia and spatial lock-in effects over time, with a high likelihood of maintaining its previous state. Key influencing factors include the density of functional facilities, distance to the city center, closeness centrality, sky openness, and floor area ratio. Moreover, interactions among built environment variables manifest in three primary forms: single-factor enhancement, nonlinear enhancement, and nonlinear suppression. The effects of these variables exhibit pronounced spatiotemporal heterogeneity, with most factors exerting both positive and negative impacts depending on the specific spatial-temporal context. These findings provide important insights for urban spatial governance and offer strategic guidance for enhancing station area vitality within a transit-oriented development (TOD) framework. [ABSTRACT FROM AUTHOR] |
| Copyright of IAENG International Journal of Applied Mathematics is the property of International Association of Engineers (IAENG) and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 188428762 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Spatiotemporal Heterogeneity of Metro Station Area Vitality and Driving Mechanisms of Built Environment Using Multi-Source Data Fusion: A Case Study of Shanghai City. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Ou%2C+Zhiyue%22">Ou, Zhiyue</searchLink><relatesTo>1</relatesTo><i> ozy20230312@163.com</i><br /><searchLink fieldCode="AR" term="%22Fu%2C+Zhongning%22">Fu, Zhongning</searchLink><relatesTo>2</relatesTo><i> fuzhongning@163.com</i><br /><searchLink fieldCode="AR" term="%22Tong%2C+Dongdong%22">Tong, Dongdong</searchLink><relatesTo>1</relatesTo><i> 3514966755@qq.com</i><br /><searchLink fieldCode="AR" term="%22Yang%2C+Xiangfei%22">Yang, Xiangfei</searchLink><relatesTo>2</relatesTo><i> yangxfei06@163.com</i><br /><searchLink fieldCode="AR" term="%22Bai%2C+Yue%22">Bai, Yue</searchLink><relatesTo>1</relatesTo><i> 2413475237@qq.com</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22IAENG+International+Journal+of+Applied+Mathematics%22">IAENG International Journal of Applied Mathematics</searchLink>. Oct2025, Vol. 55 Issue 10, p3446-3462. 17p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Built+environment%22">Built environment</searchLink><br /><searchLink fieldCode="DE" term="%22Transit-oriented+development%22">Transit-oriented development</searchLink><br /><searchLink fieldCode="DE" term="%22Subway+stations%22">Subway stations</searchLink><br /><searchLink fieldCode="DE" term="%22Urban+planning%22">Urban planning</searchLink><br /><searchLink fieldCode="DE" term="%22Multisensor+data+fusion%22">Multisensor data fusion</searchLink><br /><searchLink fieldCode="DE" term="%22Cities+%26+towns%22">Cities & towns</searchLink><br /><searchLink fieldCode="DE" term="%22Spatiotemporal+processes%22">Spatiotemporal processes</searchLink> – Name: SubjectGeographic Label: Geographic Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Shanghai+%28China%29%22">Shanghai (China)</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Accurately identifying the spatiotemporal driving mechanisms through which the built environment influences metro station area vitality is critical for advancing the coordinated development of urban human-land systems. Taking Shanghai--a representative megacity--as the case study, this research quantifies weekend station area vitality using Baidu heatmap data. A comprehensive built environment indicator system is constructed by integrating multi-source datasets, including points of interest (POIs), urban road networks, and streetscape imagery. To investigate the dynamic patterns and underlying drivers of vitality across spatial and temporal dimensions, this study employs a combination of Exploratory Spatiotemporal Data Analysis (ESTDA), Optimal-Parameter Geographic Detector (OPGD), and Spatiotemporal Geographically Weighted Regression (GTWR). The results indicate that station area vitality demonstrates strong migratory inertia and spatial lock-in effects over time, with a high likelihood of maintaining its previous state. Key influencing factors include the density of functional facilities, distance to the city center, closeness centrality, sky openness, and floor area ratio. Moreover, interactions among built environment variables manifest in three primary forms: single-factor enhancement, nonlinear enhancement, and nonlinear suppression. The effects of these variables exhibit pronounced spatiotemporal heterogeneity, with most factors exerting both positive and negative impacts depending on the specific spatial-temporal context. These findings provide important insights for urban spatial governance and offer strategic guidance for enhancing station area vitality within a transit-oriented development (TOD) framework. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of IAENG International Journal of Applied Mathematics is the property of International Association of Engineers (IAENG) and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 17 StartPage: 3446 Subjects: – SubjectFull: Built environment Type: general – SubjectFull: Transit-oriented development Type: general – SubjectFull: Subway stations Type: general – SubjectFull: Urban planning Type: general – SubjectFull: Multisensor data fusion Type: general – SubjectFull: Cities & towns Type: general – SubjectFull: Spatiotemporal processes Type: general – SubjectFull: Shanghai (China) Type: general Titles: – TitleFull: Spatiotemporal Heterogeneity of Metro Station Area Vitality and Driving Mechanisms of Built Environment Using Multi-Source Data Fusion: A Case Study of Shanghai City. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Ou, Zhiyue – PersonEntity: Name: NameFull: Fu, Zhongning – PersonEntity: Name: NameFull: Tong, Dongdong – PersonEntity: Name: NameFull: Yang, Xiangfei – PersonEntity: Name: NameFull: Bai, Yue IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 10 Text: Oct2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 19929978 Numbering: – Type: volume Value: 55 – Type: issue Value: 10 Titles: – TitleFull: IAENG International Journal of Applied Mathematics Type: main |
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