摘要
科学研究国家级旅游度假区的空间结构及影响因素对促进我国度假旅游产业布局、推动度假旅游高质量发展以及形成国际影响力具有重要意义.以国家级旅游度假区为研究对象,运用最邻近指数、不均衡指数、核密度分析等方法对其空间分布特征进行分析,并采用地理探测器、叠加分析法和缓冲区分析法进一步探讨其主要影响因素.结果表明:①整体分布上,国家级旅游度假区呈现"东南多西北少"的凝聚型空间分布格局;从省域尺度来看,国家级旅游度假区空间分布不均衡,集中分布在浙江、江苏、山东、四川、云南和江西等省份.②密度特征上,国家级旅游度假区密度分布差异较大,呈现出 1 个高密度核心区、1 个次密度核心区以及1 条倒"Y"字形核心带.③影响因素上,国家级旅游度假区空间分布受经济产业、社会政治、自然地理和旅游资源等因素的综合影响,其中经济产业因素和旅游资源因素的影响作用尤为显著.
Abstract
Scientific research on the spatial structure and influencing factors of national tourism resorts is of great significance for promoting the layout of China's vacation tourism industry,promoting high-quality development of vacation tourism,and forming inter-national influence.This paper took national tourism resorts in China as the research objects and analyzed their spatial distribution char-acteristics by using the nearest neighbor index,unbalance index,and kernel density analysis in geographic information system technolo-gy.The influencing factors of spatial distribution characteristics were further explored by combining geographic detector,superimposition analysis,and buffer zone analysis.The results showed that:①In terms of overall distribution,national tourism resorts presented a cohe-sive spatial distribution pattern of more in the southeast and less in the northwest.From the perspective of provincial scale,the spatial distribution of national tourism resorts was uneven,concentrated in provinces such as Zhejiang,Jiangsu,Shandong,Sichuan,Yunnan and Jiangxi.②In terms of density characteristics,the density distribution of national tourism resorts varies greatly,showed a high-density core area,a sub-density core area and an inverted"Y-shape"core belt.③In terms of influencing factors,the spatial distribution of national tourism resorts was comprehensively affected by such factors as economic-industrial,socio-political,physical geography and tourism resources,among which the influence of economic-industrial factors and tourism resources factors was particularly significant.
基金项目
教育部人文社会科学研究规划基金(18YJAZH057)
国家语委科研项目(WT136-66)
国家科技期刊平台
NSTL
维普
万方数据