Guangsi Lin

596 total citations
21 papers, 394 citations indexed

About

Guangsi Lin is a scholar working on Global and Planetary Change, Health, Toxicology and Mutagenesis and Environmental Engineering. According to data from OpenAlex, Guangsi Lin has authored 21 papers receiving a total of 394 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Global and Planetary Change, 13 papers in Health, Toxicology and Mutagenesis and 5 papers in Environmental Engineering. Recurrent topics in Guangsi Lin's work include Urban Green Space and Health (13 papers), Land Use and Ecosystem Services (10 papers) and Urban Agriculture and Sustainability (4 papers). Guangsi Lin is often cited by papers focused on Urban Green Space and Health (13 papers), Land Use and Ecosystem Services (10 papers) and Urban Agriculture and Sustainability (4 papers). Guangsi Lin collaborates with scholars based in China, Germany and United States. Guangsi Lin's co-authors include Wenwen Huang, Chengguang Lai, Zhaoli Wang, Yuxing Lu, Shanshan Li, Guoru Huang, Shanshan Li, Xiaoqing Wu, W. C. Sullivan and Huaqing Wang and has published in prestigious journals such as Social Science & Medicine, Journal of Hydrology and Landscape and Urban Planning.

In The Last Decade

Guangsi Lin

19 papers receiving 387 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Guangsi Lin China 11 197 173 107 53 51 21 394
Yuning Cheng China 14 243 1.2× 127 0.7× 221 2.1× 30 0.6× 62 1.2× 41 493
Catharina Sternudd Sweden 7 299 1.5× 165 1.0× 121 1.1× 146 2.8× 62 1.2× 18 501
Wonmin Sohn United States 13 360 1.8× 199 1.2× 312 2.9× 45 0.8× 86 1.7× 24 586
Martin Buchert United States 7 210 1.1× 124 0.7× 84 0.8× 35 0.7× 52 1.0× 15 351
Susannah Gill United Kingdom 6 279 1.4× 178 1.0× 172 1.6× 18 0.3× 26 0.5× 6 394
Priya Narayanan India 7 249 1.3× 157 0.9× 124 1.2× 27 0.5× 26 0.5× 14 372
Annegret Kindler Germany 13 213 1.1× 151 0.9× 94 0.9× 39 0.7× 19 0.4× 16 380
Zhanqiang Zhu China 7 187 0.9× 97 0.6× 124 1.2× 36 0.7× 28 0.5× 9 334
Renwu Wu China 10 316 1.6× 151 0.9× 130 1.2× 17 0.3× 16 0.3× 30 471

Countries citing papers authored by Guangsi Lin

Since Specialization
Citations

This map shows the geographic impact of Guangsi Lin's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Guangsi Lin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Guangsi Lin more than expected).

Fields of papers citing papers by Guangsi Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Guangsi Lin. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Guangsi Lin. The network helps show where Guangsi Lin may publish in the future.

Co-authorship network of co-authors of Guangsi Lin

This figure shows the co-authorship network connecting the top 25 collaborators of Guangsi Lin. A scholar is included among the top collaborators of Guangsi Lin based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Guangsi Lin. Guangsi Lin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
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Lin, Guangsi, et al.. (2025). How to quantify multidimensional perception of urban parks? Integrating deep learning-based social media data analysis with questionnaire survey methods. Urban forestry & urban greening. 107. 128754–128754. 6 indexed citations
5.
Lu, Yuxing, et al.. (2024). Assessing and interpreting perceived park accessibility, usability and attractiveness through texts and images from social media. Sustainable Cities and Society. 112. 105619–105619. 22 indexed citations
6.
Huang, He, et al.. (2024). Exploring temporal and spatial patterns and nonlinear driving mechanism of park perceptions: A multi-source big data study. Sustainable Cities and Society. 119. 106083–106083. 13 indexed citations
7.
Li, Yue & Guangsi Lin. (2024). Demand-side effects of urban green spaces: How attractiveness helps overcome subjective barriers to health behaviours. Urban forestry & urban greening. 94. 128277–128277. 6 indexed citations
8.
Plieninger, Tobías, et al.. (2024). Governing Landscape Simplification in Rapid Commercialization Contexts – the Case of the Dike-Pond System in the Pearl River Delta, China. International Journal of the Commons. 18(1). 2 indexed citations
9.
Huang, Wenwen & Guangsi Lin. (2023). The relationship between urban green space and social health of individuals: A scoping review. Urban forestry & urban greening. 85. 127969–127969. 47 indexed citations
10.
Lin, Guangsi, et al.. (2023). How perceived sensory dimensions of urban green spaces affect cultural ecosystem benefits: A study on Haizhu Wetland Park, China. Urban forestry & urban greening. 86. 127983–127983. 15 indexed citations
11.
Lu, Yuxing, et al.. (2023). An integrated deep learning approach for assessing the visual qualities of built environments utilizing street view images. Engineering Applications of Artificial Intelligence. 130. 107805–107805. 29 indexed citations
12.
Xu, Wenyan, et al.. (2023). Impacts of sights and sounds on anxiety relief in the high-density city. Landscape and Urban Planning. 241. 104927–104927. 31 indexed citations
13.
Lin, Guangsi. (2023). A milestone in the history of Chinese modern landscape design: the Fangta Park in Shanghai. Studies in the History of Gardens & Designed Landscapes. 43(4). 319–333. 3 indexed citations
14.
Huang, Wenwen, et al.. (2022). Bridging landscape preference and landscape design: A study on the preference and optimal combination of landscape elements based on conjoint analysis. Urban forestry & urban greening. 73. 127615–127615. 53 indexed citations
15.
Wang, Zhaoli, Shanshan Li, Xiaoqing Wu, Guangsi Lin, & Chengguang Lai. (2022). Impact of spatial discretization resolution on the hydrological performance of layout optimization of LID practices. Journal of Hydrology. 612. 128113–128113. 23 indexed citations
16.
Lei, Xiangdong, Zhaoli Wang, Guangsi Lin, & Chengguang Lai. (2021). Response of vegetation dynamics to drought at the eco-geographical region scale across China. Arabian Journal of Geosciences. 14(23). 6 indexed citations
17.
Lin, Guangsi, et al.. (2021). Evaluation of the cost-effectiveness of Green Infrastructure in climate change scenarios using TOPSIS. Urban forestry & urban greening. 64. 127287–127287. 47 indexed citations
18.
Yang, Yang, Zhifang Wang, & Guangsi Lin. (2021). Performance Assessment Indicators for Comparing Recreational Services of Urban Parks. International Journal of Environmental Research and Public Health. 18(7). 3337–3337. 10 indexed citations
19.
Li, Shanshan, Zhaoli Wang, Chengguang Lai, & Guangsi Lin. (2020). Quantitative assessment of the relative impacts of climate change and human activity on flood susceptibility based on a cloud model. Journal of Hydrology. 588. 125051–125051. 68 indexed citations
20.
Lin, Guangsi, et al.. (2019). The Use of Community Greenways: A Case Study on A Linear Greenway Space in High Dense Residential Areas, Guangzhou. Land. 8(12). 188–188. 10 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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