Landscape Perception in Cultural and Creative Industrial Parks: Integrating User-Generated Content (UGC) and Electrodermal Activity Insights

Xuefei Wang, Baoyao Zhu, Zhiqi Chen, Dawei Ma, Chuanhao Sun, Mo Wang () and Xing Jiang ()
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Xuefei Wang: College of Architecture and Urban Planning, Guangzhou University, Guangzhou 510006, China
Baoyao Zhu: College of Architecture and Urban Planning, Guangzhou University, Guangzhou 510006, China
Zhiqi Chen: College of Architecture and Urban Planning, Guangzhou University, Guangzhou 510006, China
Dawei Ma: School of Management, Guangzhou University, Guangzhou 510091, China
Chuanhao Sun: College of Architecture and Urban Planning, Guangzhou University, Guangzhou 510006, China
Mo Wang: College of Architecture and Urban Planning, Guangzhou University, Guangzhou 510006, China
Xing Jiang: College of Architecture and Urban Planning, Guangzhou University, Guangzhou 510006, China

Sustainability, 2024, vol. 16, issue 21, 1-13

Abstract: As economic growth and societal shifts reshape urban environments, cultural and creative industrial parks are emerging as vital contributors to sustainable urban development. The design of these landscapes plays a pivotal role in enhancing user satisfaction, increasing spatial attractiveness, and promoting eco-friendly urban practices. This study examines visitor landscape perception preferences in the Textile and Garment Cultural and Creative Industrial Park, located in Haizhu District, Guangzhou, through a novel methodology combining user-generated content (UGC), deep learning models, outdoor electrodermal activity (EDA) measurements, and questionnaire surveys. The UGC-based landscape recognition model achieved an accuracy of 86.8% and was validated against user preferences captured through questionnaires. Results demonstrate that visitors prefer areas featuring cultural landmarks and natural elements, while spaces dominated by human activity and transportation infrastructure are less favored. Key landscape elements, such as signage, thematic sculptures, brand logos, and trees, were identified as highly preferred features within the park. While EDA experiments revealed significant variations in physiological responses across different spatial settings, no strong correlation was observed between EDA indicators and subjective questionnaire scores. This integrative approach enables a comprehensive, objective assessment of landscape perception, providing a data-driven, user-centered framework for improving landscape design in cultural and creative industrial parks.

Keywords: cultural and creative industrial park; landscape; perception preference; user-generated content; electrodermal activity (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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