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Arid Land Geography ›› 2022, Vol. 45 ›› Issue (2): 389-400.doi: 10.12118/j.issn.1000–6060.2021.206

• Earth Surface Process • Previous Articles     Next Articles

Spatial differentiation pattern and influencing factors of China National Forest Park

ZHU Lei1,2,3(),LI Yannan1,HU Jing2,3(),ZHOU Baohua1,JIA Yaoyan4   

  1. 1. College of Resources and Environment, Anqing Normal University, Anqing 246133, Anhui, China
    2. College of Urban and Environmental Science, Central China Normal University, Wuhan 430079, Hubei, China
    3. Wuhan Branch of China Tourism Academy,Wuhan 430079, Hubei, China
    4. Faculty of Culture Tourism, Shanxi University of Finance and Economics, Taiyuan 030031, Shanxi, China
  • Received:2021-05-07 Revised:2021-08-05 Online:2022-03-25 Published:2022-04-02
  • Contact: Jing HU E-mail:aqdxzl@126.com;huj@mail.ccnu.edu.cn

Abstract:

National Forest Parks are important tourist destinations in China and are the main positions for the development of ecological, mountain, health, and leisure tourism in China. This study takes National Forest Parks in 1994, 2004, and 2019 as the research object. It employs the vector data of National Forest Parks and national precipitation, raster data of the national elevation, national A-level scenic spots, and national spatial administrative boundary vector data from 1994 to 2019 as the research data. Various GIS analysis and SPSS analysis methods are adopted, such as grid fractal method, kernel density method, exploratory spatial analysis, buffer analysis, and correlation analysis. The research results are as follows. (1) National Forest Parks are mainly distributed in east of Hu Huanyong Line, roughly forming high-density distribution areas centered on the Beijing-Tianjin-Hebei, Yangtze River Delta, Sichuan-Chongqing junction, and Hunan-Jiangxi junction. It shows a distribution pattern of “large agglomeration and small scattered”. (2) The fractal characteristics of the National Forest Parks system are obvious, and the fractal structure is more complicated. (3) The distribution of National Forest Parks varies significantly among provinces. The three major zones show a “convex pattern” differentiation law with less in the east and west and more in the middle. The eight regions show that “the distribution of National Forest Parks decreases from the middle and lower reaches of the Yangtze River, the southwest to the northeast and the middle reaches of the Yellow River”. (4) The hot spots of National Forest Parks show a certain degree of instability, where Heilongjiang, Jiangsu, and Zhejiang are more active in the development and keep in hot spots, whereas Xinjiang, Tibet, and Sichuan are in cold spots, and the development of forest parks is relatively slow. (5) Topography, precipitation, tourist source market, and tourism resource endowment are the main factors affecting the spatial distribution pattern of National Forest Parks. Therefore, it is proposed that: (1) Increase the number of locations of National Forest Parks in the east and west. (2) The spatial relevance of National Forest Parks is obvious, and the Matthew effect of space is significant. In the future, all regions, provinces, and National Forest Parks should strengthen cooperation to form a community of destiny for developing forest park tourism. This will contribute to the better and faster development of national parks in China. (3) According to the four major influencing factors of National Forest Parks, the development model of National Forest Parks can be divided into scenic-reliant development, natural geographic element utilization development, and market-driven development models. This research will further expand and deepen the research content and direction of China’s forest parks. It will also provide references for rational layout and healthy development of China’s National Forest Parks to form a community of common destiny of forest park tourism in China and promote the better and faster development of China’s national parks.

Key words: National Forest Park, spatial differentiation, influencing factors, spatial analysis technology, China