Approach to Visual Attractiveness of Event Space Through Data-Driven Environment and Spatial Perception
This work addresses urban revitalization challenges in remote areas of Japan by providing a replicable framework for improving event spaces, though it appears incremental in applying existing methods to a specific context.
This research tackled the problem of enhancing visual attractiveness in temporary event spaces in remote Japanese areas by analyzing the relationship between data-driven insights from generative AI and spatial perception, finding that successful design requires balancing spatial efficiency with diverse visitor needs.
Revitalizing Japan's remote areas has become a crucial task, and Matsue City exemplifies this effort in its temporary event spaces, created through collective efforts to foster urban vibrancy and bring together residents and visitors. This research examines the relationship between data-driven in-sights using generative AI and visual attractiveness by evaluating tempo-rary events in Matsue City, particularly considering the cognitive-cultural differences in processing visual information of the participants. The first phase employs semantic keyword extraction from interviews, categorizing responses into physical elements, activities, and atmosphere. The second phase analyzes spatial perception through three categories: layout hierar-chy, product visibility, and visual attention. The correlation indicates that successful event design requires a balance between spatial efficiency and diverse needs, with a spatial organization that optimizes visitor flow and visibility strategies considering cultural and demographic diversity. These findings contribute to understanding the urban quality of temporary event spaces and offer a replicable framework for enhancing the visual appeal of events in remote areas throughout Japan.