Multi-Source Spatio-Temporal Data-Based Tourism Structure Analysis of Demonstration City for Global Tourism: Case Study of Liyang, China

Abstract

Tourism can bring economic development and social benefits to cities. At present, global tourism is the leading urban tourism development model in China, and there is a growing tendency to use global tourism demonstration cities as models for urban tourism development; however, existing research has mostly focused on the theoretical level, and it is unclear whether such cities achieve sustainable development on a realistic level. This study selected the first demonstration cities of global tourism in China and conducted a coupling analysis using multi-source big data, clustering algorithm models, regional tourism flow distribution characteristics, etc., to explore whether the model cities meet development requirements. The following findings can be drawn from the analysis results. Firstly, the clustering algorithm coupled model study can provide a more accurate assessment of the current situation of regional tourism compared to the thermal values; secondly, the selected cities did not meet the development requirements of sustainable tourism and are in urgent need of improvement. The overarching contribution of this study is to propose a quantitative and replicable framework for urban tourism evaluation, combining spatial big data, computer algorithmic models and urban economics, etc.; this study also extends the interpretation of global tourism cities, reminds scholars, urban planners and urban tourism managers not to underestimate the possible tourism-related unsustainability of global tourism cities, and provides theoretical support for future tourism construction and urban planning development in China.