Unraveling Street Configuration Impacts on Urban Vibrancy: A GeoXAI Approach
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Longzhu Xiao & Siuming Lo & Jiangping Zhou & Jixiang Liu & Linchuan Yang, 2021. "Predicting vibrancy of metro station areas considering spatial relationships through graph convolutional neural networks: The case of Shenzhen, China," Environment and Planning B, , vol. 48(8), pages 2363-2384, October.
- Bo Huang & Yulun Zhou & Zhigang Li & Yimeng Song & Jixuan Cai & Wei Tu, 2020. "Evaluating and characterizing urban vibrancy using spatial big data: Shanghai as a case study," Environment and Planning B, , vol. 47(9), pages 1543-1559, November.
- Aibo Jin & Yunyu Ge & Shiyang Zhang, 2024. "Spatial Characteristics of Multidimensional Urban Vitality and Its Impact Mechanisms by the Built Environment," Land, MDPI, vol. 13(7), pages 1-22, July.
- Wang, Xiaoxi & Zhang, Yaojun & Yu, Danlin & Qi, Jinghan & Li, Shujing, 2022. "Investigating the spatiotemporal pattern of urban vibrancy and its determinants: Spatial big data analyses in Beijing, China," Land Use Policy, Elsevier, vol. 119(C).
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Cong Li & Yajuan Zhou & Manfei Wu & Jiayue Xu & Xin Fu, 2025. "Exploring Nonlinear Threshold Effects and Interactions Between Built Environment and Urban Vitality at the Block Level Using Machine Learning," Land, MDPI, vol. 14(6), pages 1-25, June.
- Tianwen Li & Xiaohui Wang & Longsheng Wang & Yu Ye & Yige Zhang & Yanfeng Zhang & Shimou Yao, 2026. "Evaluating the spatiotemporal impacts of urban spatial structure on urban vitality: an exploratory study using big geo-data," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 75(1), pages 1-30, March.
- Hongyu Gong & Xiaozihan Wang & Zihao Wang & Ziyi Liu & Qiushan Li & Yunhan Zhang, 2022. "How Did the Built Environment Affect Urban Vibrancy? A Big Data Approach to Post-Disaster Revitalization Assessment," IJERPH, MDPI, vol. 19(19), pages 1-25, September.
- Hu, Qiyu & Shen, Wencang & Yan, Jinming & Kong, Weilong & Li, Wei & Zhang, Zhengfeng, 2024. "Does existing mixed land development promote the urban spatial composite function? Evidence from Beijing, China," Land Use Policy, Elsevier, vol. 143(C).
- Tangqi Tu & Enjia Zhang & Ying Long, 2026. "Profile and theoretical advances in urban big data studies: A systematic review of 57 representative journals (2013–2023)," Environment and Planning B, , vol. 53(3), pages 673-688, March.
- Wang, Xiaoxi & Zhang, Yaojun & Yu, Danlin & Qi, Jinghan & Li, Shujing, 2022. "Investigating the spatiotemporal pattern of urban vibrancy and its determinants: Spatial big data analyses in Beijing, China," Land Use Policy, Elsevier, vol. 119(C).
- Zheng, Wei & Wei, Sheng, 2024. "A ‘node-place-network-city’ framework to examine HSR station area development dynamics: Station typologies and development strategies," Journal of Transport Geography, Elsevier, vol. 120(C).
- Yiming Song & Wang Zhang & Yunze Deng & Hongzhi Mo & Yuan Li, 2025. "Decoding Spatial Vitality in Historic Districts: A Grey Relational Analysis of Multidimensional Built Environment Factors in Shanghai’s Zhangyuan," Land, MDPI, vol. 14(9), pages 1-25, September.
- Zheng, Xian & Du, Xinyi & Wu, Weihao, 2025. "The impact of digital government on cross-regional investment: Evidence from Chinese cities," Economic Analysis and Policy, Elsevier, vol. 87(C), pages 99-122.
- Jinyao Lin & Yaye Zhuang & Yang Zhao & Hua Li & Xiaoyu He & Siyan Lu, 2022. "Measuring the Non-Linear Relationship between Three-Dimensional Built Environment and Urban Vitality Based on a Random Forest Model," IJERPH, MDPI, vol. 20(1), pages 1-18, December.
- Pan, Huijun & Huang, Yu, 2024. "TOD typology and station area vibrancy: An interpretable machine learning approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 186(C).
- Ruijing Yu & Chen Zeng & Mingxin Chang & Chanchan Bao & Mingsong Tang & Feng Xiong, 2022. "Effects of Urban Vibrancy on an Urban Eco-Environment: Case Study on Wuhan City," IJERPH, MDPI, vol. 19(6), pages 1-18, March.
- Dong Li & Houzeng Han & Jian Wang & Xingxing Xiao, 2025. "Explaining Urban Vitality Through Interpretable Machine Learning: A Big Data Approach Using Street View Images and Environmental Factors," Sustainability, MDPI, vol. 17(11), pages 1-21, May.
- Shaojun Liu & Yao Long & Ling Zhang & Hao Liu, 2021. "Quantifying and Characterizing Urban Leisure Activities by Merging Multiple Sensing Big Data: A Case Study of Nanjing, China," Land, MDPI, vol. 10(11), pages 1-20, November.
- Aibo Jin & Yunyu Ge & Shiyang Zhang, 2024. "Spatial Characteristics of Multidimensional Urban Vitality and Its Impact Mechanisms by the Built Environment," Land, MDPI, vol. 13(7), pages 1-22, July.
- Naifu Yu & Yingkai Tang & Ying Ma, 2023. "Spatio-Temporal Evolution, Spillover Effects of Land Resource Use Efficiency in Urban Built-Up Area: A Further Analysis Based on Economic Agglomeration," Land, MDPI, vol. 12(3), pages 1-17, February.
- Yuan Lai & Jiatong Li & Jiachen Zhang & Lan Yan & Yifeng Liu, 2022. "Do Vibrant Places Promote Active Living? Analyzing Local Vibrancy, Running Activity, and Real Estate Prices in Beijing," IJERPH, MDPI, vol. 19(24), pages 1-19, December.
- Stelian Dimitrov & Bilyana Borisova & Antoaneta Ivanova & Martin Iliev & Lidiya Semerdzhieva & Maya Ruseva & Zoya Stoyanova, 2025. "Digital Geospatial Twinning for Revaluation of a Waterfront Urban Park Design (Case Study: Burgas City, Bulgaria)," Land, MDPI, vol. 14(8), pages 1-28, August.
- Luo, Haizhi & Li, Yuanji & Zhang, Yiwen & Song, Xia & Gao, Xinyu & Luo, Xilian & Meng, Xiangzhao & Yang, Xiaohu & Liu, Zhengguang & Yan, Jinyue, 2025. "Land–energy–population Nexus: A systemic framework for per capita energy consumption characterization and prediction toward land use structure optimization," Applied Energy, Elsevier, vol. 402(PA).
- Yuchen Xie & Jiaxin Zhang & Yunqin Li & Zehong Zhu & Junye Deng & Zhixiu Li, 2024. "Integrating Multi-Source Urban Data with Interpretable Machine Learning for Uncovering the Multidimensional Drivers of Urban Vitality," Land, MDPI, vol. 13(12), pages 1-24, November.
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jlands:v:14:y:2025:i:7:p:1422-:d:1696297. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.
Printed from https://ideas.repec.org/a/gam/jlands/v14y2025i7p1422-d1696297.html