Next Article in Journal
Research on Social Service Effectiveness Evaluation for Urban Blue Spaces—A Case Study of the Huangpu River Core Section in Shanghai
Next Article in Special Issue
A Data-Driven Farm Typology as a Basis for Agricultural Land Use Decisions
Previous Article in Journal
Food Security from the Forest: The Case of the Commodification of Baobab Fruit (Adansonia digitata L.) in Boundou Region, Senegal
Previous Article in Special Issue
Citizen Sensing within Urban Greenspaces: Exploring Human Wellbeing Interactions in Deprived Communities of Glasgow
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Analysis of High-Quality Tourism Destinations Based on Spatiotemporal Big Data—A Case Study of Urumqi

1
Key Laboratory of Sustainable Development of Xinjiang’s Historical and Cultural Tourism, Xinjiang University, Urumqi 830049, China
2
School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, China
*
Authors to whom correspondence should be addressed.
Land 2023, 12(7), 1425; https://doi.org/10.3390/land12071425
Submission received: 11 June 2023 / Revised: 5 July 2023 / Accepted: 10 July 2023 / Published: 16 July 2023
(This article belongs to the Special Issue Geospatial Data for Landscape Change)

Abstract

Although high-quality tourism destinations directly determine the tourism experiences of tourists and the management focuses of tourism management departments, existing studies have paid little attention to the relationship between tourism destinations of differing quality and tourist experiences. This study analyzed the spatiotemporal distribution of tourists and the quality of tourism destinations in Urumqi based on Tencent migration big data and Weibo sign-in big data and ultimately determined whether there are spatial correlations between the two. The results show that there are large differences in quality between different tourist destinations, and although the spatial and temporal distribution of tourists is not strongly correlated with the quality of tourist destinations, we can divide tourist destinations into four categories based on the correlations between the two (e.g., high-quality tourist destinations with a low number of tourists). The results of this study provide tourists with examples of high-quality tourist destinations, thus improving their holiday experiences, and they also provide a basis by which tourism management departments can manage and develop tourist destinations. The results of this study can also be extended to other regions and play a positive role in promoting the development of the tourism industry.
Keywords: tourism destination; Tencent migration; Weibo sign-in; spatial correlation; tourism experience tourism destination; Tencent migration; Weibo sign-in; spatial correlation; tourism experience

Share and Cite

MDPI and ACS Style

Chen, B.; Zhu, Y.; He, X.; Zhou, C. Analysis of High-Quality Tourism Destinations Based on Spatiotemporal Big Data—A Case Study of Urumqi. Land 2023, 12, 1425. https://doi.org/10.3390/land12071425

AMA Style

Chen B, Zhu Y, He X, Zhou C. Analysis of High-Quality Tourism Destinations Based on Spatiotemporal Big Data—A Case Study of Urumqi. Land. 2023; 12(7):1425. https://doi.org/10.3390/land12071425

Chicago/Turabian Style

Chen, Bing, Yiting Zhu, Xiong He, and Chunshan Zhou. 2023. "Analysis of High-Quality Tourism Destinations Based on Spatiotemporal Big Data—A Case Study of Urumqi" Land 12, no. 7: 1425. https://doi.org/10.3390/land12071425

APA Style

Chen, B., Zhu, Y., He, X., & Zhou, C. (2023). Analysis of High-Quality Tourism Destinations Based on Spatiotemporal Big Data—A Case Study of Urumqi. Land, 12(7), 1425. https://doi.org/10.3390/land12071425

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop