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

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.

Authors

Institutions

Publication Details

Journal
Land
Published
2025-06-18
DOI
https://doi.org/10.3390/land14061300
Citations
2
Primary Topic
Urban Green Space and Health
Type
article
Field-Weighted Citation Impact
2.40

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Xiaojing He, Ruoshi Zhang, Yuchen Wang, Mengjie Liu et al.
2 citations
Land
Urban Green Space and Health
2.40
article

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

Xiaojing He, Ruoshi Zhang, Yuchen Wang, Mengjie Liu, Xiaoqing Tang, Lifang Wu
article en
2 citations

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.

LandVol. 14(6)
Beijing Forestry University (CN)
National Natural Science Foundation of China, Beijing Forestry University, Beijing Municipal Social Science Foundation
Sustainable cities and communities
Openalex Percentile: Top 12%
Urban Green Space and Health
2.40
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.