A Study on the Guilin Tourism Visual Corpus Based on Multi modal Geospatial Information Fusion - Sun, Yuhe; Wu, Jingjing (International Journal of Natural Resources and Environmental Studies, 2025)
The global tourism industry is undergoing a rapid transition from traditional service-based models to those driven by multimodal data. As a key tourist destination situated in the heart of China's karst region, Guilin is rich in natural landscapes, cultural heritage, and multilingual tourism content. However, these resources are dispersed and fragmented, which hinders the integration required for effective smart tourism management. Despite substantial domestic research in areas such as geospatial multimodal fusion, tourism corpora, and geovisualization, these efforts are often siloed within individual disciplines and struggle to establish a cohesive system that links multimodal data integration, corpus construction, and visualization. This paper addresses these issues by reviewing the evolving trends in these three core fields and emphasizing the critical role of multimodal data integration, the function of tourism corpora as data storage and semantic linkage tools, and the transformative potential of visualization in making multimodal data more accessible and understandable. The study develops a framework for collaborative multimodal fusion, corpus support, and visualization output, focusing on Guilin as a case study. By integrating diverse datasets, such as terrain remote sensing data, images of scenic areas, tourist reviews, and spatio-temporal paths, this work provides valuable data support for Guilin's tourism strategy and fills gaps in domestic research on the integration of multimodal geospatial data, tourism corpora, and visualization. Furthermore, it proposes a transferable model for similar international tourist destinations, advancing interdisciplinary research at the intersection of geospatial information science and tourism management.