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Spatial Pattern Analysis of Xinjiang Tourism Resources Based on Electronic Map Points of Interest

Author

Listed:
  • Yao Chang

    (College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830046, China
    Key Laboratory of Wisdom City and Environment Modeling of Higher Education Institute, Urumqi 830046, China)

  • Dongbing Li

    (College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830046, China
    Key Laboratory of Wisdom City and Environment Modeling of Higher Education Institute, Urumqi 830046, China)

  • Zibibula Simayi

    (College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830046, China
    Key Laboratory of Wisdom City and Environment Modeling of Higher Education Institute, Urumqi 830046, China)

  • Shengtian Yang

    (Institute of Water Science, Beijing Normal University, Beijing 100875, China)

  • Maliyamuguli Abulimiti

    (College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830046, China
    Key Laboratory of Wisdom City and Environment Modeling of Higher Education Institute, Urumqi 830046, China)

  • Yiwei Ren

    (College of Resources and Environmental Engineering, Ludong University, Yantai 264025, China)

Abstract

This study considers the Point of Interest data of tourism resources in Xinjiang and studies their spatial distribution by combining geospatial analysis methods, such as the average nearest neighbor index, standard deviation ellipse, kernel density analysis, and hotspot analysis, to explore their spatial distribution characteristics. Based on the analysis results, the following conclusions are made. Different categories of tourism resource sites have different spatial distributions, and all categories of tourism resources in Xinjiang are clustered in Urumqi city. The geological landscape resource sites are widely distributed and have a ring-shaped distribution in the desert area of southern Xinjiang. The biological landscape resources are distributed in a strip along the Tianshan Mountains. The water landscape resources are concentrated in the northern Xinjiang area. The site ruins are mostly distributed in the western region of Xinjiang. The distributions of the architectural landscape and entertainment and shopping resources are highly coupled with the distribution of cities. The distributions of the six categories of tourism resource points are in the northeast-southwest direction. The centripetal force and directional nature of the resource points of the water landscape are not obvious. The remaining five categories of resource points have their own characteristics. The distribution of resources in the site ruins is relatively even, and there are many hotspot areas in the geomantic and architectural landscapes, which are mainly concentrated in Bazhou and other places. The biological landscape has many cold-spot areas, distributed in areas such as Altai in northern Xinjiang and Hotan in southern Xinjiang. The remaining four categories have cold-spot and hotspot areas with different distributions. Tourism is an important thrust for economic development. The study of the distribution of tourism resources on the spatial distribution of tourism resources has clear guidance for later tourism development, can help the tourism industry optimize the layout of resources, and can promote tourism resources to achieve maximum benefits. The government can implement effective control and governance.

Suggested Citation

  • Yao Chang & Dongbing Li & Zibibula Simayi & Shengtian Yang & Maliyamuguli Abulimiti & Yiwei Ren, 2022. "Spatial Pattern Analysis of Xinjiang Tourism Resources Based on Electronic Map Points of Interest," IJERPH, MDPI, vol. 19(13), pages 1-18, June.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:13:p:7666-:d:845741
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    References listed on IDEAS

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    Cited by:

    1. Yao Chang & Dongbing Li & Zibibula Simayi & Yiwei Ren & Shengtian Yang, 2022. "Spatial Distribution of Leisure Agriculture in Xinjiang and Its Influencing Factors Based on Geographically Weighted Regression," Sustainability, MDPI, vol. 14(22), pages 1-20, November.
    2. Tai Zhang & Bin Wang & Yisong Ge & Chengzhi Li, 2022. "Research on Green Space Service Space Based on Crowd Aggregation and Activity Characteristics under Big Data—Take Tacheng City as an Example," IJERPH, MDPI, vol. 19(22), pages 1-15, November.
    3. Shengrui Zhang & Lei Chi & Tongyan Zhang & Yingjie Wang, 2022. "Spatial Pattern and Influencing Factors of Tourism Resources in Northwestern Ethnic Areas in China—A Case Study of Longde County," IJERPH, MDPI, vol. 19(24), pages 1-20, December.

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