Spatial Distribution and Influencing Factors of High-Level Tourist Attractions in China: A Case Study of 9296 A-Level Tourist Attractions

被引:4
|
作者
Zikirya, Bahram [1 ,2 ]
Zhou, Chunshan [1 ,2 ]
机构
[1] Xinjiang Univ, Coll Tourism, Key Lab Sustainable Dev Xinjiangs Hist & Cultural, Urumqi 830046, Peoples R China
[2] Sun Yat Sen Univ, Sch Geog & Planning, Guangzhou 510275, Peoples R China
关键词
tourist attractions; influencing factors; spatial distribution; spatial correlation; geographical detector; NETWORK ANALYSIS; PATTERNS;
D O I
10.3390/su151914339
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The distribution pattern of high-level tourist attractions is crucial for the sustainable development of the tourism industry. However, few studies have explored the spatial distribution and dominant influencing factors of tourist attractions of different levels from a macro perspective in China. This study, which was based on large-scale multi-source data, involved the use of kernel density analysis, local spatial autocorrelation, and geographical detector analysis to explore the spatial distribution, spatial correlation, and dominant influencing factors of high-level tourist attractions in China. The study's results show that the spatial distribution of tourist attractions of different levels is polarized and regionally clustered, and there exist some spatial correlation effects among attractions of the same level. Additionally, different influencing factors play a different role in determining the spatial distribution of attractions of different levels. Based on market demand and tourism resources, it is necessary to regulate attractions of different levels to promote the sustainable development of high-level tourist attractions and provide a reference for the development of China's tourism industry.
引用
收藏
页数:18
相关论文
共 50 条
  • [31] Indicator System and Construction Level of Online Service Functions on New Media Platforms of Tourist Attractions: A Case Study of Yangzhou City, China
    Ye, Peng
    Liu, Yuping
    SUSTAINABILITY, 2023, 15 (09)
  • [32] Applicability of Demographic Recommender System to Tourist Attractions: A Case Study on TripAdvisor
    Wang, Yuanyuan
    Chan, Stephen Chi-Fai
    Ngai, Grace
    2012 IEEE/WIC/ACM INTERNATIONAL CONFERENCE ON WEB INTELLIGENCE AND INTELLIGENT AGENT TECHNOLOGY WORKSHOPS (WI-IAT WORKSHOPS 2012), VOL 3, 2012, : 97 - 101
  • [33] The Matching Relationship Between the Distribution Characteristics of High-Grade Tourist Attractions and Spatial Vitality in Xinjiang
    Zikirya, Bahram
    Xing, Yueqing
    Zhou, Chunshan
    SUSTAINABILITY, 2024, 16 (21)
  • [34] Tourism Highway Traffic Demand Forecasting of Tourist Attractions: A Case Study of Xingkai Lake, China
    Han Juan
    Hu Xiao Wei
    Wang Lei
    MATERIALS, TRANSPORTATION AND ENVIRONMENTAL ENGINEERING, PTS 1 AND 2, 2013, 779-780 : 868 - +
  • [35] Do social media data indicate visits to tourist attractions? A case study of Shanghai, China
    Liang, Huilin
    Zhang, Qingping
    OPEN HOUSE INTERNATIONAL, 2022, 47 (01) : 17 - 35
  • [36] Quantitative Identification of the Information Pattern for Tourist Attractions in the Internet Space A case study in Beijing, China
    Li, Renjie
    Wang, Yun
    Cao, Rui
    Guo, Fenghua
    Sun, Guiping
    2010 18TH INTERNATIONAL CONFERENCE ON GEOINFORMATICS, 2010,
  • [37] Fuzzy TOPSIS Approaches for Assessing the Intelligence Level of IoT-Based Tourist Attractions
    Guo, Xudong
    Zeng, Tao
    Wang, Yuxuan
    Zhang, Jie
    IEEE ACCESS, 2019, 7 : 1195 - 1207
  • [38] REVIEW AND DIAGNOSIS OF TOURIST ATTRACTIONS: CASE STUDY VILLA DEL MAR (ARGENTINA)
    Elias, Silvina
    Leonardi, Viviana
    Del Rosario Fernandez, Maria
    GRAN TOUR, 2015, (11): : 19 - 44
  • [39] Tourist risk assessment of pollen allergy in tourism attractions: A case study in the Summer Palace, Beijing, China
    Zhou, Yu
    Dai, Junhu
    Liu, Haolong
    Liu, Xian
    FRONTIERS IN PUBLIC HEALTH, 2022, 10
  • [40] Exploring emotion differences in tourist attractions based on online travel notes: a case study in Nanjing, China
    Ruan, Ling
    Song, Bing
    Huang, Zhenfang
    Long, Yi
    Zhang, Ling
    ASIA PACIFIC JOURNAL OF TOURISM RESEARCH, 2022, 27 (07) : 726 - 743