Assessing Public Space Vitality in a Central-City High-Speed Rail Station Area Using Multi-Source Data: A Case Study of Shapingba Station, Chongqing

This study examines how high-speed rail (HSR) hubs shape public space vitality in central-city station areas, using Shapingba Station (Chongqing, China) as a representative case of station–city integration. We delineated pedestrian catchments using Baidu Map walking isochrones (300–1200 s) and integrated multi-source data, including Public Space Public Life (PSPL) field observations (eight monitoring points, 07:00–24:00), Baidu heat maps, point-of-interest (POI) records, streetscape semantic segmentation, and a perception questionnaire. Indicators were synthesized via entropy weighting, and multivariate associations between perceived vitality and environmental variables were examined using Mantel tests. Pedestrian flow exhibits a clear double-peak pattern (09:00–11:00 and 15:00–16:00), averaging 42,248 pedestrians per day (2347 per hour) and showing strong spatial heterogeneity across monitoring points. POIs show a pronounced core–periphery structure: totals increase from 803 (300 s) to 4365 (600 s) and 7539 (1200 s), while overall density declines from 7477 to 2492 POIs/km2, highlighting a 600 s core where accessibility and functional agglomeration are most strongly coupled. Overall, this study contributes a replicable multi-source evaluation framework and quantitative evidence on accessibility–function coupling and micro-scale design effects in HSR station areas, enabling theory-informed comparisons across station typologies and urban contexts.

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Publication Details

Journal
Land
Published
2026-04-14
DOI
https://doi.org/10.3390/land15040641
Primary Topic
Urban Transport and Accessibility
Type
article
Field-Weighted Citation Impact
0.00

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article

Assessing Public Space Vitality in a Central-City High-Speed Rail Station Area Using Multi-Source Data: A Case Study of Shapingba Station, Chongqing

Xu Cui, Tao Wang
Land
Urban Transport and Accessibility
article

Assessing Public Space Vitality in a Central-City High-Speed Rail Station Area Using Multi-Source Data: A Case Study of Shapingba Station, Chongqing

Xu Cui, Tao Wang
article en

Abstract

This study examines how high-speed rail (HSR) hubs shape public space vitality in central-city station areas, using Shapingba Station (Chongqing, China) as a representative case of station–city integration. We delineated pedestrian catchments using Baidu Map walking isochrones (300–1200 s) and integrated multi-source data, including Public Space Public Life (PSPL) field observations (eight monitoring points, 07:00–24:00), Baidu heat maps, point-of-interest (POI) records, streetscape semantic segmentation, and a perception questionnaire. Indicators were synthesized via entropy weighting, and multivariate associations between perceived vitality and environmental variables were examined using Mantel tests. Pedestrian flow exhibits a clear double-peak pattern (09:00–11:00 and 15:00–16:00), averaging 42,248 pedestrians per day (2347 per hour) and showing strong spatial heterogeneity across monitoring points. POIs show a pronounced core–periphery structure: totals increase from 803 (300 s) to 4365 (600 s) and 7539 (1200 s), while overall density declines from 7477 to 2492 POIs/km2, highlighting a 600 s core where accessibility and functional agglomeration are most strongly coupled. Overall, this study contributes a replicable multi-source evaluation framework and quantitative evidence on accessibility–function coupling and micro-scale design effects in HSR station areas, enabling theory-informed comparisons across station typologies and urban contexts.

LandVol. 15(4)
Sichuan Fine Arts Institute (CN), Southwest Jiaotong University (CN)
National Natural Science Foundation of China
Sustainable cities and communities
Openalex Percentile: Top 23%
Urban Transport and Accessibility
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Assessing Public Space Vitality in a Central-City High-Speed Rail Station Area Using Multi-Source Data: A Case Study of Shapingba Station, Chongqing — Xu Cui, Tao Wang · Land (2026) | TGRS Research Map | TGRS