Accessibility Cluster Analysis of Subway Station Based on Spatial Big Data——A Case Study of Dongcheng and Xicheng Districts in Beijing City
Subway is an important means of daily commuting in city life due to its punctuality and speed. Residential accessibility around subway station reflects the transportation convenience and connectivity between the necessary facilities which affecting residents’ daily lives. Therefore, this study resea...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2024-01-01
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| Series: | E3S Web of Conferences |
| Online Access: | https://www.e3s-conferences.org/articles/e3sconf/pdf/2024/42/e3sconf_uct2024_01019.pdf |
| _version_ | 1797213140335722496 |
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| author | Zhao Lingmei Wang Zhenyang Cao Mingliang |
| author_facet | Zhao Lingmei Wang Zhenyang Cao Mingliang |
| author_sort | Zhao Lingmei |
| collection | DOAJ |
| description | Subway is an important means of daily commuting in city life due to its punctuality and speed. Residential accessibility around subway station reflects the transportation convenience and connectivity between the necessary facilities which affecting residents’ daily lives. Therefore, this study research on station accessibility factors by improving the walk-score model and establishing a multi-feature integrated transportation model that comprehensively considers the age difference based on spatial big data. Quantitative analysis was conducted on facility and station accessibility. Based on clustering algorithm considering three age groups, subway stations were classified into four types: mature, well-equipped, nurturing, and deficient. Using friendly characteristics, subway stations were categorized into three dominant age types. By integrating the analysis of accessibility, spatial layout, clustering differences and age-friendly characteristics, suggestions were proposed to improve station connectivity and supporting facility development. |
| first_indexed | 2024-04-24T10:53:33Z |
| format | Article |
| id | doaj.art-c506c624252c4514b946c3d996528efd |
| institution | Directory Open Access Journal |
| issn | 2267-1242 |
| language | English |
| last_indexed | 2024-04-24T10:53:33Z |
| publishDate | 2024-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | E3S Web of Conferences |
| spelling | doaj.art-c506c624252c4514b946c3d996528efd2024-04-12T07:41:52ZengEDP SciencesE3S Web of Conferences2267-12422024-01-015120101910.1051/e3sconf/202451201019e3sconf_uct2024_01019Accessibility Cluster Analysis of Subway Station Based on Spatial Big Data——A Case Study of Dongcheng and Xicheng Districts in Beijing CityZhao Lingmei0Wang Zhenyang1Cao Mingliang2Beijing Institute of Surveying and Mapping, 60 Nanlishi Road, XichengBeijing Institute of Surveying and Mapping, 60 Nanlishi Road, XichengBeijing Institute of Surveying and Mapping, 60 Nanlishi Road, XichengSubway is an important means of daily commuting in city life due to its punctuality and speed. Residential accessibility around subway station reflects the transportation convenience and connectivity between the necessary facilities which affecting residents’ daily lives. Therefore, this study research on station accessibility factors by improving the walk-score model and establishing a multi-feature integrated transportation model that comprehensively considers the age difference based on spatial big data. Quantitative analysis was conducted on facility and station accessibility. Based on clustering algorithm considering three age groups, subway stations were classified into four types: mature, well-equipped, nurturing, and deficient. Using friendly characteristics, subway stations were categorized into three dominant age types. By integrating the analysis of accessibility, spatial layout, clustering differences and age-friendly characteristics, suggestions were proposed to improve station connectivity and supporting facility development.https://www.e3s-conferences.org/articles/e3sconf/pdf/2024/42/e3sconf_uct2024_01019.pdf |
| spellingShingle | Zhao Lingmei Wang Zhenyang Cao Mingliang Accessibility Cluster Analysis of Subway Station Based on Spatial Big Data——A Case Study of Dongcheng and Xicheng Districts in Beijing City E3S Web of Conferences |
| title | Accessibility Cluster Analysis of Subway Station Based on Spatial Big Data——A Case Study of Dongcheng and Xicheng Districts in Beijing City |
| title_full | Accessibility Cluster Analysis of Subway Station Based on Spatial Big Data——A Case Study of Dongcheng and Xicheng Districts in Beijing City |
| title_fullStr | Accessibility Cluster Analysis of Subway Station Based on Spatial Big Data——A Case Study of Dongcheng and Xicheng Districts in Beijing City |
| title_full_unstemmed | Accessibility Cluster Analysis of Subway Station Based on Spatial Big Data——A Case Study of Dongcheng and Xicheng Districts in Beijing City |
| title_short | Accessibility Cluster Analysis of Subway Station Based on Spatial Big Data——A Case Study of Dongcheng and Xicheng Districts in Beijing City |
| title_sort | accessibility cluster analysis of subway station based on spatial big data a case study of dongcheng and xicheng districts in beijing city |
| url | https://www.e3s-conferences.org/articles/e3sconf/pdf/2024/42/e3sconf_uct2024_01019.pdf |
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