Spatio-temporal big data analysis of tourists: a case study of Hangzhou

Jie Xue; Jinhao Shi

doi:10.1117/12.2625593

9 December 2021 Spatio-temporal big data analysis of tourists: a case study of Hangzhou

Jie Xue, Jinhao Shi

Proceedings Volume 12129, International Conference on Environmental Remote Sensing and Big Data (ERSBD 2021); 121290S (2021) https://doi.org/10.1117/12.2625593
Event: 2021 International Conference on Environmental Remote Sensing and Big Data, 2021, Wuhan, China

Abstract

With the transformation of urban functions and the development of tourism, the research on the temporal and spatial behavior characteristics of tourist flow and destination preference within cities has gradually attracted the attention of domestic and foreign scholars. Based on the digital footprint data, with the help of social network analysis and mathematical statistical analysis, the time and space distribution and network structure characteristics of the tourist flow of external tourists in Hangzhou are studied. The results show that: Hangzhou’s tourist flows have strong seasonal time characteristics; it presents a “dual core” and gradually decreasing spatial distribution characteristics, as well as the spatial preference characteristics dominated by natural scenery and historical sites; the overall density of the tourist flow network is relatively loose.

Citation Download Citation

Jie Xue and Jinhao Shi "Spatio-temporal big data analysis of tourists: a case study of Hangzhou", Proc. SPIE 12129, International Conference on Environmental Remote Sensing and Big Data (ERSBD 2021), 121290S (9 December 2021); https://doi.org/10.1117/12.2625593

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