Water bodies in urban green spaces are important parts of urban landscapes, and their planar shapes are an important factor governing the creation of waterfront landscapes. To improve the aesthetics and functionality of water bodies, this paper takes Nanjing as an example for analysis to investigate whether it is possible to scientifically quantify the planar shape of urban green space water bodies. First, water bodies meeting the conditions within the municipal area were selected as the study objects for classification. Second, in view of the lack of theoretical and innovative problems in previous studies, the use of fractal theory was proposed to improve the scientificity. Finally, remote sensing data images were used to extract water body planes, and the fractal dimensions were calculated and quantitatively evaluated by coupling the box dimension method with fractal theory. The results show that the fractal dimension could be used as a quantitative parameter to determine the planar morphology of water bodies in urban green spaces, and the fractal dimension value is positively correlated with the complexity of the water body, which can be used for both quantitative assessment of the landscape aesthetics of existing water bodies in urban green spaces and theoretical support for the future design of water planar morphology.

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.

Sustainable tourism can bring economic development and social benefits to tourism cities. At present, Global tourism is the leading urban tourism development model in China, and the Global tourism demonstration cities is tended to be used as a role model for urban tourism development, however, the existing research is mostly focused on the theoretical level, and it is unclear whether such cities actually achieve sustainable development on a realistic level. This study selects the first demonstration cities of Global tourism in China, and conducts a coupling analysis by using multi-source big data, clustering algorithm models, and regional tourism flow distribution characteristics etc. to explore whether the demonstration cities have achieved sustainable tourism. The following results 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 city do 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 and urban planners not to underestimate the possible tourism unsustainability of all-area tourism cities, and provides theoretical support for future tourism construction and urban planning development in China.