Next Article in Journal
Radio Astronomy Demonstrator: Assessment of the Appropriate Sites through a GIS Open Source Application
Next Article in Special Issue
Pattern of Spatial Distribution and Temporal Variation of Atmospheric Pollutants during 2013 in Shenzhen, China
Previous Article in Journal
The Physical Density of the City—Deconstruction of the Delusive Density Measure with Evidence from Two European Megacities
Previous Article in Special Issue
Assessing Land Degradation Dynamics and Distinguishing Human-Induced Changes from Climate Factors in the Three-North Shelter Forest Region of China
Article Menu
Issue 11 (November) cover image

Export Article

Open AccessArticle
ISPRS Int. J. Geo-Inf. 2016, 5(11), 210;

Analysis of Attraction Features of Tourism Destinations in a Mega-City Based on Check-in Data Mining—A Case Study of Shenzhen, China

College of Architecture and Urban Planning, Shenzhen University, Shenzhen 518060, China
Shenzhen Key Laboratory for Optimizing Design of Built Environment, Shenzhen 518060, China
Shenzhen Key Laboratory of Spatial Smart and Services, Shenzhen 518060, China
Author to whom correspondence should be addressed.
Academic Editors: Yichun Xie, Xinyue Ye and Wolfgang Kainz
Received: 21 September 2016 / Revised: 4 November 2016 / Accepted: 7 November 2016 / Published: 10 November 2016
(This article belongs to the Special Issue Spatiotemporal Computing for Sustainable Ecosystem)
View Full-Text   |   Download PDF [4614 KB, uploaded 10 November 2016]   |  


Location-based service information, provided by social networks, provides new data sources and perspectives to research tourism activities, especially in highly populated mega-cities. Based on three years (2012–2014) of approximately 340,000 check-in records collected from Sina micro-blog at 86 tourist attractions in Shenzhen, a first-tier city in southern China, we conducted a comprehensive study of the attraction features involving different aspects, such as tourist source, duration of stay, check-in activity index, and attraction correlation degree. The results showed that (1) theme parks established in the early 1990s were the most popular tourist attractions in Shenzhen, but a negative trend was detected in the check-in population; (2) compared with check-in times from surrounding activities and the kernel density of tourists, most destinations in Shenzhen showed a lack of attraction, failing to make the most of their geographic accessibility; and (3) the homogeneity and inconvenient traffic conditions of major tourist destinations leading to the construction of a tourism tour chain has become a challenge. The results of this study demonstrate the potential of big-data mining and provide valuable insights into tourism market design and management in mega-cities. View Full-Text
Keywords: check-in data; tourist destination; tourist scenic spot; attraction feature check-in data; tourist destination; tourist scenic spot; attraction feature

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Share & Cite This Article

MDPI and ACS Style

Gu, Z.; Zhang, Y.; Chen, Y.; Chang, X. Analysis of Attraction Features of Tourism Destinations in a Mega-City Based on Check-in Data Mining—A Case Study of Shenzhen, China. ISPRS Int. J. Geo-Inf. 2016, 5, 210.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
ISPRS Int. J. Geo-Inf. EISSN 2220-9964 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top