Publications

Highlights

Wang, Y., Rigolon, A., & Park, K. (2024). Transit to parks initiatives in the U.S. and Canada: Practitioners’ perspectives, Transport Policy 154: 84-95. https://doi.org/10.1016/j.tranpol.2024.06.007 [download] [link to the project page]

As large open spaces, such as national and regional parks, have become popular as recreational destinations, car dependency to access those open spaces has created capacity challenges. Due to these issues, transit-to-parks (T2P) initiatives—public transportation services connecting populated areas to large parks—have gained global traction. Limited research has examined these sustainability initiatives, and more knowledge is needed about how these initiatives are created and function. To address these gaps, this study explores motivations, facilitators, and challenges related to T2P initiatives in the U.S. and Canada. We conducted semi-structured interviews with 28 practitioners involved in the planning or operation of T2P initiatives in the two countries. Motivations for T2P included parking and congestion issues, environmental concerns, equity, and economic development. Facilitators of T2P initiatives included robust partnerships, community engagement, and advocacy efforts, emphasizing the importance of tailored narratives and coalition-building. The primary challenges mentioned were limited funding and labor, inadequate infrastructure, and siloed agencies and politics. This study reveals the complex dynamics of T2P initiatives and provides practical implications for transit agencies, public lands agencies, and community advocates seeking to enhance more sustainable and equitable access to nature.

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

  • 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]