Evaluation on AI-Generative Emotional Design Approach for Urban Vitality Spaces: A LoRA-Driven Framework and Empirical Research

Ruoshi Zhang (), Xiaoqing Tang, Lifang Wu, Yuchen Wang, Xiaojing He and Mengjie Liu
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Ruoshi Zhang: School of Landscape Architecture, Beijing Forestry University, Beijing 100083, China
Xiaoqing Tang: School of Landscape Architecture, Beijing Forestry University, Beijing 100083, China
Lifang Wu: School of Landscape Architecture, Beijing Forestry University, Beijing 100083, China
Yuchen Wang: School of Landscape Architecture, Beijing Forestry University, Beijing 100083, China
Xiaojing He: School of Landscape Architecture, Beijing Forestry University, Beijing 100083, China
Mengjie Liu: School of Landscape Architecture, Beijing Forestry University, Beijing 100083, China

Land, 2025, vol. 14, issue 6, 1-23

Abstract: Recent advancements in urban vitality space design reflect increasing academic attention to emotional experience dimensions, paralleled by the emergence of AI-based generative technology as a transformative tool for systematically exploring the emotional attachment potential in preliminary designs. To effectively utilize AI-generative design results for spatial vitality creation and evaluation, exploring whether generated spaces respond to people’s emotional demands is necessary. This study establishes a comparative framework analyzing emotional attachment characteristics between LoRA-generated spatial designs and the real urban vitality space, using the representative case of THE BOX in Chaoyang, Beijing. Empirical data were collected through structured on-site surveys with 115 validated participants, enabling a comprehensive emotional attachment evaluation. SPSS 26.0 was employed for multi-dimensional analyses, encompassing aggregate attachment intensity, dimensional differentiation, and correlation mapping. Key findings reveal that while both generative and original spatial representations elicit measurable positive responses, AI-generated designs demonstrate a limited capacity to replicate the authentic three-dimensional experiential qualities inherent to physical environments, particularly regarding structural articulation and material tactility. Furthermore, significant deficiencies persist in the generative design’s cultural semiotic expression and visual-interactive spatial legibility, resulting in diminished user satisfaction. The analysis reveals that LoRA-generated spatial solutions require strategic enhancements in dynamic visual hierarchy, interactive integration, chromatic optimization, and material fidelity to bridge this experiential gap. These insights suggest viable pathways for integrating generative AI methodologies with conventional urban design practices, potentially enabling more sophisticated hybrid approaches that synergize digital innovation with built environment realities to cultivate enriched multisensory spatial experiences.

Keywords: LoRA technology; AI-generative design; emotional design; emotional attachment scales; urban vitality space (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2025
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