Popularity influence mechanism of coastal spaces in urban areas: Insights from multi-modal large language models

Abstract

Urban coastal spaces enhance public health, attract tourists, and boost cultural ecosystem services, making understanding public usage patterns and experiences crucial for coastal management and planning. This study employs multimodal big data and large language models (LLaMA and LLaVA) to explore the mechanisms influencing the popularity of urban coastal areas. By integrating social media text and image data, mobile signaling data, and multisource geographic data, this research identifies key perceptual factors affecting coastal spaces' popularity. The findings highlight that visual and auditory perceptions, aesthetic services, and amenity services are vital for visitor satisfaction, while biodiversity and cultural services significantly impact visitation frequency. This research offers practical strategies for urban planners to optimize coastal space design and management, promoting sustainable development in tourism and cultural ecosystems.