Between place attachment and urban planning in Jinan: Does environmental quality affect human perception in a developing country context?

Jia Jia, Xiaoqing Zhang and Wenzhong Zhang

Land Use Policy, 2025, vol. 148, issue C

Abstract: Human perception is a critical component of place attachment, but its contribution to people-oriented urban planning remains unclear. Global shifts have dramatically transformed the way people live, with a surge in engagement in online “social” spheres. Social media has risen to prominence as the principal conduit through which individuals articulate their views. However, current research lacks an overall consideration of the use of social media to link the urban environment with people’s perceptions. Furthermore, complex social media data processing presents another technical difficulty. This study presents an innovative use of deep learning BERT-based techniques to analyze online data from social media and subdivide human perceptions into 9 emotions and 10 behaviors. On the basis of Spearman correlation, geographically weighted regression (GWR), and multilevel multinomial logistic regression, we investigate the impact of the quality of the urban built environment and individual differences on residents’ perceptions. The results show that the greater the density of urban amenities and the more diverse urban land uses are, the more likely residents are to express positive emotions and the greater the number of types of activity. Women and older people are more likely to develop place attachment. Our research explores the impact of environmental quality on human perception from both theoretical and empirical perspectives and provides a deeper understanding of the humanland relationship. Urban planning that considers place attachment can create opportunities for sustainable urban development and improve the quality of human life.

Keywords: Place attachment; Environmental quality; Human perception; Social media; Deep learning; Urban Planning (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:lauspo:v:148:y:2025:i:c:s0264837724003375

DOI: 10.1016/j.landusepol.2024.107384

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