{"id":204285,"date":"2025-11-28T05:54:49","date_gmt":"2025-11-28T05:54:49","guid":{"rendered":"https:\/\/www.europesays.com\/ie\/204285\/"},"modified":"2025-11-28T05:54:49","modified_gmt":"2025-11-28T05:54:49","slug":"exploring-nonlinear-and-interactive-associations-between-built-environment-features-and-subjective-streetscape-perceptions","status":"publish","type":"post","link":"https:\/\/www.europesays.com\/ie\/204285\/","title":{"rendered":"Exploring nonlinear and interactive associations between built environment features and subjective streetscape perceptions"},"content":{"rendered":"
  • \n

    Harvey, C. & Aultman-Hall, L. Measuring urban streetscapes for livability: a review of approaches. Prof. Geogr. 68<\/b>, 149\u2013158 (2016).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Ma, X. et al. Measuring human perceptions of streetscapes to better inform urban renewal: a perspective of scene semantic parsing. Cities 110<\/b>, 103086 (2021).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Koo, B. W., Hwang, U. & Guhathakurta, S. Streetscapes as part of servicescapes: can walkable streetscapes make local businesses more attractive?. Comput. Environ. Urban Syst. 106<\/b>, 102030 (2023).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Anand, S. & Pujara, T. Towards anxiety alleviating streetscape design: a comprehensive literature review. Cities Health 8<\/b>, 1134\u20131152 (2024).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Latkin, C. A. & Curry, A. D. Stressful neighborhoods and depression: a prospective study of the impact of neighborhood disorder. J. Health Soc. Behav. 44<\/b>, 34\u201344 (2003).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Jiang, Y., Christopher Zegras, P. & Mehndiratta, S. Walk the line: station context, corridor type and bus rapid transit walk access in Jinan, China. J. Transp. Geogr. 20<\/b>, 1\u201314 (2012).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Rossetti, T., Lobel, H., Rocco, V. & Hurtubia, R. Explaining subjective perceptions of public spaces as a function of the built environment: a massive data approach. Landsc. Urban Plan. 181<\/b>, 169\u2013178 (2019).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Dharmasthala, S., Sun, Q. & Langenheim, N. Are high distributed streetscapes also located in the high social interaction streets? A Space syntax approach on street liveability assessment. In 2021 28th International Conference on Geoinformatics 1\u20137, https:\/\/doi.org\/10.1109\/IEEECONF54055.2021.9687512<\/a> (2021).<\/p>\n<\/li>\n

  • \n

    Inoue, T., Manabe, R., Murayama, A. & Koizumi, H. The effect of culture-specific differences in urban streetscapes on the inference accuracy of deep learning models. ISPRS Ann. Photogramm. Remote Sens. Spat. Inf. Sci. X-4-W3-2022<\/b>, 73\u201380 (2022).<\/p>\n


    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Qiu, W. et al. Subjective and objective measures of streetscape perceptions: Relationships with property value in Shanghai. Cities 132<\/b>, 104037 (2023).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Ogawa, Y., Oki, T., Zhao, C., Sekimoto, Y. & Shimizu, C. Evaluating the subjective perceptions of streetscapes using street-view images. Landsc. Urban Plan. 247<\/b>, 105073 (2024).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Lee, S. & Cho, N. Nonlinear and interaction effects of multi-dimensional street-level built environment features on urban vitality in Seoul. Cities 165<\/b>, 106145 (2025).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Said, S. & Samadi, Z. The evolution of historic streetscape in adapting modern demand in achieving the quality of life. Proc. Soc. Behav. Sci. 234<\/b>, 488\u2013497 (2016).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Wey, W. M. & Wei, W. L. Urban street environment design for quality of urban life. Soc. Indic. Res. 126<\/b>, 161\u2013186 (2016).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Sharifi, A. Resilient urban forms: a review of literature on streets and street networks. Build. Environ. 147<\/b>, 171\u2013187 (2019).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Chen, Z. & Huang, B. Achieving urban vibrancy through effective city planning: a spatial and temporal perspective. Cities 152<\/b>, 105230 (2024).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Yang, L., Ao, Y., Ke, J., Lu, Y. & Liang, Y. To walk or not to walk? Examining non-linear effects of streetscape greenery on walking propensity of older adults. J. Transp. Geogr. 94<\/b>, 103099 (2021).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Devlin, A. S. Environmental Psychology and Human Well-Being (Academic Press, 2018).<\/p>\n<\/li>\n

  • \n

    Rapoport, A. The Meaning of the Built Environment: A Nonverbal Communication Approach (University of Arizona Press, 1990).<\/p>\n<\/li>\n

  • \n

    Hawley, A. H. Human Ecology: A Theory of Community Structure (The Ronald Press Company, 1950).<\/p>\n<\/li>\n

  • \n

    Zacharias, J. Pedestrian behavior pedestrian behavior and perception in urban walking environments. J. Plan. Lit. 16<\/b>, 3\u201318 (2001).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Kim, S. Are small cities disappearing? The policy responses to urban shrinkage oriented toward young people in Uiseong-gun, South Korea. Cities 155<\/b>, 105450 (2024).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    He, X., Gao, W., Guan, D. & Zhou, L. Impacts of urban shrinkage on the built environment and its environmental sustainability: an analytical review. Environ. Res. Lett. 18<\/b>, 103004 (2023).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Lima, M. F. & Eischeid, M. R. Shrinking cities: rethinking landscape in depopulating urban contexts. Landsc. Res. 42<\/b>, 691\u2013698 (2017).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Haase, A., Rink, D., Grossmann, K., Bernt, M. & Mykhnenko, V. Conceptualizing Urban Shrinkage. Environ. Plan. Econ. Space 46<\/b>, 1519\u20131534 (2014).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Sarif, N. & Roy, A. K. Measuring urban shrinkage in India using night-light data from DMSP-OLS and VIIRS-NPP satellite sensors. Cities 152<\/b>, 105176 (2024).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Li, Z. & Long, Y. Analysis of the Variation in Quality of Street Space in Shrinking Cities Based on Dynamic Street View Picture Recognition: A Case Study of Qiqihar. In Shrinking Cities in China: The Other Facet of Urbanization (eds. Long, Y. & Gao, S.) 141\u2013155 (Springer, 2019). https:\/\/doi.org\/10.1007\/978-981-13-2646-2_8<\/a>.<\/p>\n<\/li>\n

  • \n

    Barreira, A. P., Nunes, L. C., Guimar\u00e3es, M. H. & Panagopoulos, T. Satisfied but thinking about leaving: the reasons behind residential satisfaction and residential attractiveness in shrinking Portuguese cities. Int. J. Urban Sci. 23<\/b>, 67\u201387 (2019).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Khavarian-Garmsir, A. R. A systematic review of shrinking cities literature: lessons from the past and directions for the future. Int. Plan. Stud. 28<\/b>, 219\u2013238 (2023).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Istrate, A.-L., Bos\u00e1k, V., Nov\u00e1\u010dek, A. & Slach, O. How attractive for walking are the main streets of a shrinking city?. Sustainability 12<\/b>, 6060 (2020).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Boarnet, M. G., Forsyth, A., Day, K. & Oakes, J. M. The street level built environment and physical activity and walking: results of a predictive validity study for the Irvine Minnesota Inventory. Environ. Behav. 43<\/b>, 735\u2013775 (2011).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Park, K., Ewing, R., Sabouri, S. & Larsen, J. Street life and the built environment in an auto-oriented US region. Cities 88<\/b>, 243\u2013251 (2019).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Jiang, Y., Han, Y., Liu, M. & Ye, Y. Street vitality and built environment features: a data-informed approach from fourteen Chinese cities. Sustain. Cities Soc. 79<\/b>, 103724 (2022).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Lee, S., Lee, S. & Putri, D. W. Multifaceted associations between built environments and POI visit patterns by trip purposes. Cities 161<\/b>, 105903 (2025).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Chen, L., Lu, Y., Ye, Y., Xiao, Y. & Yang, L. Examining the association between the built environment and pedestrian volume using street view images. Cities 127<\/b>, 103734 (2022).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Vallebueno, A. & Lee, Y. S. Measuring urban quality and change through the detection of physical attributes of decay. Sci. Rep. 13<\/b>, 17316 (2023).<\/p>\n

    Article<\/a>\u00a0
    \n     CAS<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Xu, Y., Tong, H., Liu, J., Su, Y. & Li, M. An assessment of the urban streetscape using multiscale data and semantic segmentation in Jinan Old City, China. Buildings 14<\/b>, 2687 (2024).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Cetintahra, G. E. & Cubukcu, E. The influence of environmental aesthetics on economic value of housing: an empirical research on virtual environments. J. Hous. Built Environ. 30<\/b>, 331\u2013340 (2015).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Sheets, V. L. & Manzer, C. D. Affect, cognition, and urban vegetation: some effects of adding trees along city streets. Environ. Behav. 23<\/b>, 285\u2013304 (1991).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Foster, S., Hooper, P., Knuiman, M., Bull, F. & Giles-Corti, B. Are liveable neighbourhoods safer neighbourhoods? Testing the rhetoric on new urbanism and safety from crime in Perth, Western Australia. Soc. Sci. Med. 164<\/b>, 150\u2013157 (2016).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Mertens, L. et al. Which environmental factors most strongly influence a street\u2019s appeal for bicycle transport among adults? A conjoint study using manipulated photographs. Int. J. Health Geogr. 15<\/b>, 31 (2016).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Ki, D. & Lee, S. Analyzing the effects of Green View Index of neighborhood streets on walking time using Google Street View and deep learning. Landsc. Urban Plan. 205<\/b>, 103920 (2021).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Ding, C., Jason Cao, X. & N\u00e6ss, P. Applying gradient boosting decision trees to examine non-linear effects of the built environment on driving distance in Oslo. Transp. Res. Part Policy Pract. 110<\/b>, 107\u2013117 (2018).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Gao, K., Yang, Y., Gil, J. & Qu, X. Data-driven interpretation on interactive and nonlinear effects of the correlated built environment on shared mobility. J. Transp. Geogr. 110<\/b>, 103604 (2023).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Lee, S. Relationships between transportation expenditures and built environment in the United States: insights from interpretable machine-learning approach. J. Plan. Educ. Res. https:\/\/doi.org\/10.1177\/0739456X241268464<\/a> (2024).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Lee, S., Ki, D., Hipp, J. R. & Kim, J. H. Analysing non-linearities and threshold effects between street-level built environments and local crime patterns: an interpretable machine learning approach. Urban Stud. https:\/\/doi.org\/10.1177\/00420980241270948<\/a> (2024).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Jin, K., Guo, W. & Yang, T. Urban street quality measurement in central city by combining street view images and deep learning. In 2023 5th International Academic Exchange Conference on Science and Technology Innovation (IAECST) 592\u2013601. https:\/\/doi.org\/10.1109\/IAECST60924.2023.10502610<\/a> (2023).<\/p>\n<\/li>\n

  • \n

    Liang, X., Chang, J. H., Gao, S., Zhao, T. & Biljecki, F. Evaluating human perception of building exteriors using street view imagery. Build. Environ. 263<\/b>, 111875 (2024).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Jacobs, J. The Death and Life of Great American Cities (Random House, 1961).<\/p>\n<\/li>\n

  • \n

    Woo, A., Han, J., Shin, H. & Lee, S. Economic benefits of urban streetscapes: analyzing the interrelationships between visual street environments and single-family property values in Seoul, Korea. Appl. Geogr. 163<\/b>, 103182 (2024).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Bibri, S. E., Krogstie, J. & K\u00e4rrholm, M. Compact city planning and development: emerging practices and strategies for achieving the goals of sustainability. Dev. Built Environ. 4<\/b>, 100021 (2020).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Hu, Y., Liu, Y., Chen, P. & Zhang, M. The impact of residents\u2019 perceptions of urban shrinkage on overall life satisfaction \u2013 The case of Yichun, China. Cities 141<\/b>, 104445 (2023).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Rupprecht, C. D. D. Informal urban green space: residents\u2019 perception, use, and management preferences across four major Japanese shrinking cities. Land 6<\/b>, 59 (2017).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Xu, J. et al. Understanding the nonlinear effects of the street canyon characteristics on human perceptions with street view images. Ecol. Indic. 154<\/b>, 110756 (2023).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Koo, B. W., Guhathakurta, S. & Botchwey, N. How are neighborhood and street-level walkability factors associated with walking behaviors? A big data approach using street view images. Environ. Behav. 54<\/b>, 211\u2013241 (2022).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Zhou, H. et al. A multiscale assessment of the impact of perceived safety from street view imagery on street crime. Ann. Am. Assoc. Geogr. 114<\/b>, 69\u201390 (2024).<\/p>\n


    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Biljecki, F. & Ito, K. Street view imagery in urban analytics and GIS: a review. Landsc. Urban Plan. 215<\/b>, 104217 (2021).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    He, J., Zhang, J., Yao, Y. & Li, X. Extracting human perceptions from street view images for better assessing urban renewal potential. Cities 134<\/b>, 104189 (2023).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Sun, H. et al. A spatial analysis of urban streets under deep learning based on street view imagery: quantifying perceptual and elemental perceptual relationships. Sustainability 15<\/b>, 14798 (2023).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Yuan, Y., Wang, R., Niu, T. & Liu, Y. Using street view images and a geographical detector to understand how street-level built environment is associated with urban poverty: a case study in Guangzhou. Appl. Geogr. 156<\/b>, 102980 (2023).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Lu, Y., Ferranti, E. J. S., Chapman, L. & Pfrang, C. Assessing urban greenery by harvesting street view data: a review. Urban. Urban Green. 83<\/b>, 127917 (2023).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Li, Y., Miller, H. J., Root, E. D., Hyder, A. & Liu, D. Understanding the role of urban social and physical environment in opioid overdose events using found geospatial data. Health Place 75<\/b>, 102792 (2022).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Quercia, D., O\u2019Hare, N. K. & Cramer, H. Aesthetic capital: what makes london look beautiful, quiet, and happy? In Proceedings of the 17th ACM conference on Computer supported cooperative work & social computing 945\u2013955 (Association for Computing Machinery, 2014). https:\/\/doi.org\/10.1145\/2531602.2531613<\/a>.<\/p>\n<\/li>\n

  • \n

    Dubey, A., Naik, N., Parikh, D., Raskar, R. & Hidalgo, C. A. Deep learning the city: quantifying urban perception at a global scale. In Computer Vision \u2013 ECCV 2016 (eds. Leibe, B., Matas, J., Sebe, N. & Welling, M.) 196\u2013212 (Springer International Publishing, Cham, 2016). https:\/\/doi.org\/10.1007\/978-3-319-46448-0_12<\/a>.<\/p>\n<\/li>\n

  • \n

    Kushlev, K., Drummond, D. M. & Diener, E. Subjective well-being and health behaviors in 2.5 million Americans. Appl. Psychol. Health Well Being 12<\/b>, 166\u2013187 (2020).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Li, X., Zhang, C. & Li, W. Does the visibility of greenery increase perceived safety in urban areas? Evidence from the place pulse 1.0 dataset. ISPRS Int. J. Geo Inf. 4<\/b>, 1166\u20131183 (2015).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Freitas, F., Berreth, T., Chen, Y.-C. & Jhala, A. Characterizing the perception of urban spaces from visual analytics of street-level imagery. AI Soc. 38<\/b>, 1361\u20131371 (2023).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Huang, X. et al. Comprehensive walkability assessment of urban pedestrian environments using big data and deep learning techniques. Sci. Rep. 14<\/b>, 26993 (2024).<\/p>\n

    Article<\/a>\u00a0
    \n     CAS<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Shi, H., Yu, L., Xu, Y., Liu, Y. & Zhao, M. The impact of the streetscape built environment on recreation satisfaction: a case study of Guangzhou. J. Transp. Geogr. 112<\/b>, 103702 (2023).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Rita, L., Peliteiro, M., Bostan, T.-C., Tamagusko, T. & Ferreira, A. Using deep learning and google street view imagery to assess and improve cyclist safety in London. Sustainability 15<\/b>, 10270 (2023).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Kim, G.-E. & Lee, J.-R. The impact of historic building preservation in urban economics: focusing on accommodation prices in Jeonju Hanok Village, South Korea. Sustainability 12<\/b>, 5005 (2020).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Lee, J.-S. Measuring the benefits of the intangible cultural heritage hall in Jeonju Korea: results of a contingent valuation survey. J. Cult. Herit. 16<\/b>, 236\u2013238 (2015).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Lee, S., Ock, Y., Kim, M. & Schrock, G. The regional uneven development and the state intervention to reshape the spatial hierarchy. Int. J. Reg. Dev. 8<\/b>, 1 (2021).<\/p>\n

    CAS<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Lee, J., Kim, D. & Park, J. A machine learning and computer vision study of the environmental characteristics of streetscapes that affect pedestrian satisfaction. Sustainability 14<\/b>, 5730 (2022).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Lavieri, P. S. & Bhat, C. R. Investigating objective and subjective factors influencing the adoption, frequency, and characteristics of ride-hailing trips. Transp. Res. Part C. Emerg. Technol. 105<\/b>, 100\u2013125 (2019).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Kang, Y., Kim, J., Park, J. & Lee, J. Assessment of perceived and physical walkability using street view images and deep learning technology. ISPRS Int. J. Geo-Inf. 12<\/b>, 186 (2023).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Zhang, J. & Hu, A. Analyzing green view index and green view index best path using Google street view and deep learning. J. Comput. Des. Eng. 9<\/b>, 2010\u20132023 (2022).<\/p>\n


    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Aikoh, T., Homma, R. & Abe, Y. Comparing conventional manual measurement of the green view index with modern automatic methods using google street view and semantic segmentation. Urban. Urban Green. 80<\/b>, 127845 (2023).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Shin, H.-C. et al. Deep convolutional neural networks for computer-aided detection: CNN architectures, dataset characteristics and transfer learning. IEEE Trans. Med. Imaging 35<\/b>, 1285\u20131298 (2016).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Gupta, J., Pathak, S. & Kumar, G. Deep learning (CNN) and transfer learning: a review. J. Phys. Conf. Ser. 2273<\/b>, 012029 (2022).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Lee, J. S., Won, S. & Kim, S. Describing changes in the built environment of shrinking cities: case study of Incheon, South Korea. J. Urban Plan. Dev. 142<\/b>, 05015010 (2016).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Hollander, J., Johnson, M., Drew, R. B. & Tu, J. Changing urban form in a shrinking city. Environ. Plan. B 46<\/b>, 963\u2013991 (2019).<\/p>\n


    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Yin, C., Cao, J. & Sun, B. Examining non-linear associations between population density and waist-hip ratio: an application of gradient boosting decision trees. Cities 107<\/b>, 102899 (2020).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Yang, L., Liang, Y., Zhu, Q. & Chu, X. Machine learning for inference: using gradient boosting decision tree to assess non-linear effects of bus rapid transit on house prices. Ann. GIS 27<\/b>, 273\u2013284 (2021).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Liu, J., Wang, B. & Xiao, L. Non-linear associations between built environment and active travel for working and shopping: an extreme gradient boosting approach. J. Transp. Geogr. 92<\/b>, 103034 (2021).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Lee, S. Transportation Mode Choice Behavior in the Era of Autonomous Vehicles: The Application of Discrete Choice Modeling and Machine Learning (Portland State University, 2022).<\/p>\n<\/li>\n

  • \n

    Wu, J. & Kulcs\u00e1r, B. A modular, adaptive, and autonomous transit system (MAATS): A in-motion transfer strategy and performance evaluation in urban grid transit networks. Transp. Res. Part Policy Pract. 151<\/b>, 81\u201398 (2021). Selpi & Qu, X.<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Shams, M. Y. et al. Water quality prediction using machine learning models based on grid search method. Multimed. Tools Appl. 83<\/b>, 35307\u201335334 (2024).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Refaeilzadeh, P., Tang, L. & Liu, H. Cross-validation. In Encyclopedia of Database Systems (eds. Liu, L. & \u00d6zsu, M. T.) 1\u20137 (Springer, 2016). https:\/\/doi.org\/10.1007\/978-1-4899-7993-3_565-2<\/a>.<\/p>\n<\/li>\n

  • \n

    Malakouti, S. M., Menhaj, M. B. & Suratgar, A. A. The usage of 10-fold cross-validation and grid search to enhance ML methods performance in solar farm power generation prediction. Clean. Eng. Technol. 15<\/b>, 100664 (2023).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Huang, N., Lu, G. & Xu, D. A permutation importance-based feature selection method for short-term electricity load forecasting using random forest. Energies 9<\/b>, 767 (2016).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Mi, X., Zou, B., Zou, F. & Hu, J. Permutation-based identification of important biomarkers for complex diseases via machine learning models. Nat. Commun. 12<\/b>, 3008 (2021).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Zhao, X. et al. Factors affecting traffic risks on bridge sections of freeways based on partial dependence plots. Phys. Stat. Mech. Appl. 598<\/b>, 127343 (2022).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Shi, H., Yang, N., Yang, X. & Tang, H. Clarifying relationship between PM2.5 concentrations and spatiotemporal predictors using multi-way partial dependence plots. Remote Sens. 15<\/b>, 358 (2023).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Inglis, A., Parnell, A. & Hurley, C. B. Visualizing variable importance and variable interaction effects in machine learning models. J. Comput. Graph. Stat. 31<\/b>, 766\u2013778 (2022).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n

  • \n

    Ullah, I., Liu, K., Yamamoto, T., Zahid, M. & Jamal, A. Modeling of machine learning with SHAP approach for electric vehicle charging station choice behavior prediction. Travel Behav. Soc. 31<\/b>, 78\u201392 (2023).<\/p>\n

    Article<\/a>\u00a0
    \n
    \n Google Scholar<\/a>\u00a0\n <\/p>\n<\/li>\n","protected":false},"excerpt":{"rendered":"Harvey, C. & Aultman-Hall, L. Measuring urban streetscapes for livability: a review of approaches. Prof. Geogr. 68, 149\u2013158…\n","protected":false},"author":2,"featured_media":204286,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[77],"tags":[4912,18,440,910,19,17,133,14644,2376,9301,14646,14648,14645,14647],"class_list":{"0":"post-204285","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-science","8":"tag-cities","9":"tag-eire","10":"tag-environment","11":"tag-general","12":"tag-ie","13":"tag-ireland","14":"tag-science","15":"tag-social-sciences","16":"tag-sustainable-development","17":"tag-technology-and-society","18":"tag-towns","19":"tag-urban-ecology","20":"tag-urban-geography-urbanism-inc-megacities","21":"tag-urbanism"},"share_on_mastodon":{"url":"https:\/\/pubeurope.com\/@ie\/115625782329639290","error":""},"_links":{"self":[{"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/posts\/204285","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/comments?post=204285"}],"version-history":[{"count":0,"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/posts\/204285\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/media\/204286"}],"wp:attachment":[{"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/media?parent=204285"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/categories?post=204285"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/tags?post=204285"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}