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作 者:赵胡兰 杨兆萍[1] 时卉[1] 刘勤 韩芳[1] 王璀蓉[1] 郭姣姣 ZHAO Hulan;YANG Zhaoping;SHI Hui;LIU Qin;HAN Fang;WANG Cuirong;GUO Jiaojiao(State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830001, China;University of Chinese Academy of Sciences, Beijing 100049, China)
机构地区:[1]中国科学院新疆生态与地理研究所荒漠与绿洲生态国家重点实验室,乌鲁木齐830001 [2]中国科学院大学,北京100049
出 处:《中国科学院大学学报(中英文)》2021年第3期367-373,共7页Journal of University of Chinese Academy of Sciences
基 金:新疆重大科技专项课题(2016A02002-1);新疆维吾尔自治区自然科学基金面上项目(2019D01A96);中国科学院“西部之光”人才培养计划(2016-QNXZ-B-18)资助。
摘 要:旅游景区系统的空间结构不仅影响区域设施空间布局,同时也影响区域空间结构的优化和调整。基于分形理论,对乌鲁木齐市A级旅游景区系统空间结构进行研究,以唯一的5A级旅游景区天山大峡谷为中心,测算聚集维数以及基于乌鸦距离和乳牛距离的空间关联维数。结果表明:乌鲁木齐市A级旅游景区系统的空间结构存在明显的双分形特征,总体上呈现聚集分布,分布密度由中心向四周衰减较快,在演变过程中可能出现多中心并存的格局;系统空间结构具有自组织优化趋势,各景区之间关联程度较高,但总体交通通达性一般,交通网络体系还不够完善。据此提出多中心协同发展模式、大力打造主题式景区、开发精品自驾游路线等建议,形成旅游空间网络体系。Spatial structure of tourist attraction system has effects on spatial layout of regional infrastructures as well as the optimization and adjustment of regional spatial structure.Based on the fractal theory,this article studies the spatial structure of class-A tourist attraction system in Urumqi.Taking the Tianshan Grand Canyon(the only class-5A tourist attraction)as center to measure the aggregation dimension as well as the spatial correlation dimension based on crow distance and cow distance.This article indicates the following results:There are double fractal characteristics in the spatial structure of class-A tourist attraction system in Urumqi.In general,there is an aggregate distribution,and the distribution density decays rapidly from the center to the surrounding areas.In the evolution of the spatial structure,multi-center pattern may occur.The spatial structure of the tourist attraction system has a trend of self-organization optimization.Although there are strong traffic correlations among tourist attractions,the transportation network is not adequate enough.Based on these,the article proposes few recommendations to help shape tourism spatial network system by developing polycentric collaborative model,building theme sight-seeing spots,and creating high-quality self-driving routes.
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