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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Using Google Street View to investigate the association between street greenery and physical activity
Yi Lü
Landscape and Urban Planning (2018) Vol. 191, pp. 103435-103435
Closed Access | Times Cited: 311

Showing 1-25 of 311 citing articles:

Street view imagery in urban analytics and GIS: A review
Filip Biljecki, Koichi Ito
Landscape and Urban Planning (2021) Vol. 215, pp. 104217-104217
Open Access | Times Cited: 429
Analyzing the effects of Green View Index of neighborhood streets on walking time using Google Street View and deep learning
Donghwan Ki, Sugie Lee
Landscape and Urban Planning (2020) Vol. 205, pp. 103920-103920
Closed Access | Times Cited: 255
Neighbourhood greenness and mental wellbeing in Guangzhou, China: What are the pathways?
Ye Liu, Ruoyu Wang, George Grekousis, et al.
Landscape and Urban Planning (2019) Vol. 190, pp. 103602-103602
Closed Access | Times Cited: 219
A review of urban physical environment sensing using street view imagery in public health studies
Yuhao Kang, Fan Zhang, Song Gao, et al.
Annals of GIS (2020) Vol. 26, Iss. 3, pp. 261-275
Open Access | Times Cited: 201
Measuring human perceptions of streetscapes to better inform urban renewal: A perspective of scene semantic parsing
Xiangyuan Ma, Chenyan Ma, Chao Wu, et al.
Cities (2021) Vol. 110, pp. 103086-103086
Closed Access | Times Cited: 194
An ecosystem service perspective on urban nature, physical activity, and health
Roy P. Remme, Howard Frumkin, Anne D. Guerry, et al.
Proceedings of the National Academy of Sciences (2021) Vol. 118, Iss. 22
Open Access | Times Cited: 186
Associations between overhead-view and eye-level urban greenness and cycling behaviors
Yi Lü, Yiyang Yang, Guibo Sun, et al.
Cities (2019) Vol. 88, pp. 10-18
Closed Access | Times Cited: 180
Perceptions of built environment and health outcomes for older Chinese in Beijing: A big data approach with street view images and deep learning technique
Ruoyu Wang, Ye Liu, Yi Lü, et al.
Computers Environment and Urban Systems (2019) Vol. 78, pp. 101386-101386
Open Access | Times Cited: 166
Exploring the linkage between greenness exposure and depression among Chinese people: Mediating roles of physical activity, stress and social cohesion and moderating role of urbanicity
Ye Liu, Ruoyu Wang, Yang Xiao, et al.
Health & Place (2019) Vol. 58, pp. 102168-102168
Closed Access | Times Cited: 159
Natural outdoor environment, neighbourhood social cohesion and mental health: Using multilevel structural equation modelling, streetscape and remote-sensing metrics
Yuqi Liu, Ruoyu Wang, Yi Lü, et al.
Urban forestry & urban greening (2020) Vol. 48, pp. 126576-126576
Open Access | Times Cited: 140
Escaping to nature during a pandemic: A natural experiment in Asian cities during the COVID-19 pandemic with big social media data
Yi Lü, Jianting Zhao, Xueying Wu, et al.
The Science of The Total Environment (2021) Vol. 777, pp. 146092-146092
Open Access | Times Cited: 128
Assessing bikeability with street view imagery and computer vision
Koichi Ito, Filip Biljecki
Transportation Research Part C Emerging Technologies (2021) Vol. 132, pp. 103371-103371
Open Access | Times Cited: 123
Assessing impacts of objective features and subjective perceptions of street environment on running amount: A case study of Boston
Lin Dong, Hongchao Jiang, Wenjing Li, et al.
Landscape and Urban Planning (2023) Vol. 235, pp. 104756-104756
Closed Access | Times Cited: 82
Environmental factors for outdoor jogging in Beijing: Insights from using explainable spatial machine learning and massive trajectory data
Wei Yang, Yingpeng Li, Yong Liu, et al.
Landscape and Urban Planning (2023) Vol. 243, pp. 104969-104969
Closed Access | Times Cited: 53
Unraveling nonlinear and interaction effects of multilevel built environment features on outdoor jogging with explainable machine learning
Wei Yang, Jun Fei, Yingpeng Li, et al.
Cities (2024) Vol. 147, pp. 104813-104813
Closed Access | Times Cited: 21
How well do NDVI and OpenStreetMap data capture people’s visual perceptions of urban greenspace?
Roos Teeuwen, Vasileios Milias, Alessandro Bozzon, et al.
Landscape and Urban Planning (2024) Vol. 245, pp. 105009-105009
Open Access | Times Cited: 15
Towards a cycling-friendly city: An updated review of the associations between built environment and cycling behaviors (2007–2017)
Yiyang Yang, Xueying Wu, Peiling Zhou, et al.
Journal of Transport & Health (2019) Vol. 14, pp. 100613-100613
Open Access | Times Cited: 119
The Role of Methodological Choices in the Effects of Experimental Exposure to Simulated Natural Landscapes on Human Health and Cognitive Performance: A Systematic Review
Matthew H.E.M. Browning, Fatemeh Saeidi-Rizi, Olivia McAnirlin, et al.
Environment and Behavior (2020) Vol. 53, Iss. 7, pp. 687-731
Closed Access | Times Cited: 114
Relationship between eye-level greenness and cycling frequency around metro stations in Shenzhen, China: A big data approach
Ruoyu Wang, Yi Lü, Xueying Wu, et al.
Sustainable Cities and Society (2020) Vol. 59, pp. 102201-102201
Closed Access | Times Cited: 97
Are greenspace quantity and quality associated with mental health through different mechanisms in Guangzhou, China: A comparison study using street view data
Ruoyu Wang, Zhiqiang Feng, Jamie Pearce, et al.
Environmental Pollution (2021) Vol. 290, pp. 117976-117976
Open Access | Times Cited: 90
The distribution of greenspace quantity and quality and their association with neighbourhood socioeconomic conditions in Guangzhou, China: A new approach using deep learning method and street view images
Ruoyu Wang, Zhiqiang Feng, Jamie Pearce, et al.
Sustainable Cities and Society (2020) Vol. 66, pp. 102664-102664
Open Access | Times Cited: 87
Dynamic greenspace exposure and residents’ mental health in Guangzhou, China: From over-head to eye-level perspective, from quantity to quality
Ruoyu Wang, Zhiqiang Feng, Jamie Pearce, et al.
Landscape and Urban Planning (2021) Vol. 215, pp. 104230-104230
Open Access | Times Cited: 86
Modelling and mapping eye-level greenness visibility exposure using multi-source data at high spatial resolutions
S.M. Labib, Jonny Huck, Sarah Lindley
The Science of The Total Environment (2020) Vol. 755, pp. 143050-143050
Open Access | Times Cited: 83
Investigating the Relationship between the Built Environment and Relative Risk of COVID-19 in Hong Kong
Jianwei Huang, Mei‐Po Kwan, Zihan Kan, et al.
ISPRS International Journal of Geo-Information (2020) Vol. 9, Iss. 11, pp. 624-624
Open Access | Times Cited: 83
Estimating pedestrian volume using Street View images: A large-scale validation test
Long Chen, Yi Lü, Qiang Sheng, et al.
Computers Environment and Urban Systems (2020) Vol. 81, pp. 101481-101481
Closed Access | Times Cited: 81
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