Publications

Highlights

Park, K. & Khanal, A. (in-press). Park features, neighbourhood environment, and time factors affect park visitor volume: A meta analysis. Environment and Behavior. https://doi.org/10.1177/00139165251342974 [download]

Urban parks are essential for sustainable urban planning, but their usage patterns remain complex. This meta-analysis of 30 studies identifies factors influencing park visitor volume, focusing on park attributes, neighborhood environments, and temporal aspects. Random-effect models reveal positive associations with park size, diverse facilities, organized activities, trails, maintenance, and quality. Neighborhood population density and points of interest also increase visitation, while socio-economically disadvantaged areas see reduced use. Temporal factors, such as time of day and season, significantly shape patterns. However, features like water, greenness, crime safety, and transit accessibility show mixed or insignificant effects. Regional differences highlight stronger impacts of population density and transit accessibility in the U.S. compared to Asian studies. These findings provide actionable insights for urban planners and landscape architects to design parks that cater to diverse needs, boost visitation, and maximize their community benefits.

Chen, M., Liu, Y., Liu, F., Chadha, T., Park, K. (2025). Measuring pedestrian-level street greenery visibility through space syntax and crowdsourced imagery: A case study in London, UK. Urban Forestry & Urban Greening, 105, 128725. | https://doi.org/10.1016/j.ufug.2025.128725 [download]

Linear green spaces, composed of street trees, shrubs, and grass, provide diverse opportunities for human-nature interaction. However, current research tends to visualize street greenery from a single perspective, such as images or planar analysis and neglects pedestrian-scale street tree visual analytics. Space syntax relies on precise urban context data input, and street view image analysis does not cover sidewalk greenery visibility. This study integrates green visibility analysis based on space syntax’s Visibility Graph Analysis (VGA) with the Pedestrian Green View Index (PGVI) calculated from street imagery to propose a comprehensive evaluation model for pedestrian-scale green visibility. To validate the accuracy of the methods, we established a participation scoring system involving 183 volunteers to collect their green perceptions of nine types of streets in the City of London, UK. The study reveals a complex relationship between VGA and PGVI, with VGA providing a robust, geometric-based visibility measure and PGVI offering a qualitative, human-centric perspective on urban greenery. Our findings indicate a significant correlation between PGVI and human evaluations, affirming PGVI’s potential to reflect pedestrian experiences, while highlighting the limitations of VGA in capturing the nuanced, multi-dimensional aspects of human perception. This underscores the necessity of integrating human feedback in urban planning tools to ensure a comprehensive understanding of green spaces. Future research should enhance methodological rigor by incorporating temporal and seasonal dynamics, expanding datasets, and exploring the interplay between green visibility and other environmental factors.

Peer-Reviewed Journal Articles (Since September 2021)

Note: Names of the lab members are in bold

  • Park, K. & Khanal, A. (in-press). Park features, neighbourhood environment, and time factors affect park visitor volume: A meta analysis. Environment and Behavior. https://doi.org/10.1177/00139165251342974
  • Chen, M., Liu, Y., Liu, F., Chadha, T., Park, K. (2025). Measuring pedestrian-level street greenery visibility through space syntax and crowdsourced imagery: A case study in London, UK. Urban Forestry & Urban Greening, 105, 128725. https://doi.org/10.1016/j.ufug.2025.128725 [download]
  • Luo, T., & Chen, M. (2024). Advancements in supervised machine learning for outdoor thermal comfort: A comprehensive systematic review of scales, applications, and data types. Energy and Buildings, 115255. https://doi.org/10.1016/j.enbuild.2024.115255 [download]
  • Chen, S., Sleipness, O., Christensen, K., Yang, B., Park, K., Knowles, R., Yang, Z., & Wang, H. (2024). Exploring the Associations between Social Interaction and Park Quality: An Urban Case Study in Utah, USA, Cities 145: 104714. https://doi.org/10.1016/j.cities.2023.104714 [download]
  • Chen, M., Cai, Y., Guo, S., Sun, R., Yang, S., & Shen, X. (2024). Evaluating implied urban nature vitality in San Francisco: An interdisciplinary approach combining census data, street view images, and social media analysis. Urban Forestry & Urban Greening, 128289. https://doi.org/10.1016/j.ufug.2024.128289 [download]
  • Khanal, A., Abdelfattah, R. S., Alawadi, K., & Nguyen, N. H. (2024). Beyond streets: The role of alleys in Abu Dhabi’s and Dubai’s network systems. Journal of Urban Management, 13(1), 33-51. https://doi.org/10.1016/j.jum.2023.10.002 [download]
  • Park, K., Garcia, I., & Kim, K. (2023). Who visited parks and trails more or less during the COVID-19 pandemic, and how? A mixed-methods study, Landscape Research Record 11: 157-171. [download]
  • Park, K., Singleton, P.A., Brewer, S. & Zuban, J. (2023). Pedestrians and the built environment during the COVID-19 pandemic: Changing relationships by the pandemic phases in Salt Lake County, UT, USA. Transportation Research Record: Journal of the Transportation Research Board 2677(4): 448-462. https://doi.org/10.1177/03611981221083606 [download]
  • Park, K., Nasr-Isfahani, H., Novack, V., Sheen, J., Hadayeghi, H., Song, Z., & Christensen, K. (2023). Impacts of disability on daily travel behaviour: A systematic review. Transport Reviews 43(2): 178-203. https://doi.org/10.1080/01441647.2022.2060371 [The editors’ choice] [download] 
  • Zhang, Y., Li, X., Jiang, Q., Chen, M., & Liu, L. (2022). Quantify the spatial association between the distribution of catering business and urban spaces in London using catering POI data and image segmentation. Atmosphere, 13(12), 2128. https://doi.org/10.3390/atmos13122128 [download]
  • Ren, B., Park, K., Shrestha, A., Yang, J., McHale, M., Bai, W., Wang, G. (2022). Impact of Human Disturbances on the Spatial Heterogeneity of Landscape Fragmentation in Qilian Mountain National Park, China, Land, 11: 2087. https://doi.org/10.3390/land11112087 [download]
  • Wang, L., Ding, J., Chen, M., Sun, Y., Tang, X., & Ge, M. (2022). Exploring tourists’ multilevel spatial cognition of historical town based on multi-source data—A case study of Feng Jing ancient town in Shanghai. Buildings, 12(11), 1833. https://doi.org/10.3390/buildings12111833 [download]
  • Shen, X., Chen, M., Ge, M., & Padua, M. G. (2022). Examining the conceptual model of potential urban development patch (PUDP), VOCs, and food culture in urban ecology: A case in Chengdu, China. Atmosphere, 13(9), 1369. https://doi.org/10.3390/atmos13091369 [download]
  • Chen, M., Zhang, Y.*, Yang, Y., Fang, Z. (2022). Application of data visualization in urban design based on Grasshopper. Landscape Architecture 陈铭泽,张洋,杨玉冰,方智果. 基于Grasshopper平台的数据可视化在城市设计中的研究与实践[J].园林, 2022, 39(05):44-51. [download]
  • Park, K., Sanchez, T., & Zuban, J. (2022). Evaluating scholarly productivity and impacts of landscape architecture faculty using citation analysis. Landscape Journal 41(1): 1-14. https://doi.org/10.3368/lj.41.1.1 [download]
  • Park, K., Chamberlain, B., Song, Z., Nasr-Isfahani, H., Sheen, J., Larsen, T., Novack, V., Licon, C., & Christensen, K. (2022). A double jeopardy: COVID-19 impacts on people with disabilities’ travel behavior and community living. Transportation Research Part A: Policy and Practice 156: 24-35. https://doi.org/10.1016/j.tra.2021.12.008 [download]
  • Abu Ali, M., Alawadi, K., & Khanal, A. (2021). “The role of green infrastructure in enhancing microclimate conditions: a case study of a low-rise neighborhood in Abu Dhabi”. Sustainability, 13(8), 4260. https://doi.org/10.3390/su13084260 [download]