It is important for urban tourism development to focus on the accessibility of tourist points of interest (POIs). The spatial distribution of POIs should be closely linked to sustainable traffic development. In recent years, smartphones and global positioning systems have provided strong technical support for tourist POIs through social media. Many studies have been conducted to investigate the correlation between POIs and transportation from different perspectives. There is however a lack of quantitative research on the correlation between traffic accessibility and the distribution of urban tourist POIs using space syntax theory. This study proposes a method for optimizing the layout of tourist POIs based on traffic accessibility. We crawled 2,322 tourist POIs in Dalian as research objects, adopted kernel density estimation and constructed spatial syntax models. We analysed these models from the perspective of the spatial distribution characteristics of the POIs and traffic accessibility. The results showed no direct correlation between the spatial distribution of POIs and road networks. The conclusion is that the distribution of the most popular POIs does not coincide with the roads with the highest accessibility in Dalian. Therefore, we propose feasible optimization strategies for spatial planning of tourist POIs and sustainable traffic development.
As Dalian, China, is a touristic city, optimization of the touristic space plan has become increasingly important for its sustainable development. In recent years, big data, GIS, computer simulation and other technologies have been applied widely in the field of tourism spatial planning research. However, the integration of those information technology-based methods with the sustainable urban development framework has not been sufficiently studied to suggest how to optimize the spatial planning strategies for scenic spots in urban areas. This paper aims to propose a method for optimizing the layout of tourism space based on the sustainable urban development framework. We used five districts, including the centre of Dalian, as the background for the evolution of scenic spots; simultaneously, we used integrated methods including kernel density estimation (KDE) and spatial syntax, to analyse the spatial pattern of tourism in Dalian. We used big data from the three most authoritative evaluation websites in China, to collect the current popularity and location data of scenic spots. According to the analysis of spatiotemporal patterns, and transportation accessibility of each scenic spot, the results show that there are some problems in the network of tourist attractions, such as low connectivity and unbalanced distribution. Therefore, we propose a method for optimizing the geographical views of spatial structure for tourist attractions in Dalian, as a countermeasure of sustainable urban development.
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