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作 者:黄钦 杨波[1] 龚熊波 梁莉莉 王敏[1] 陈颖[1] 袁慧芳 邹小燕 HUANG Qin;YANG Bo;GONG Xiong-bo;LIANG Li-li;WANG Min;CHEN Ying;YUAN Hui-fang;ZOU Xiao-yan(College of Geographic Science,Hunan Key Laboratory of Geospatial Big Data Mining and Application,Hunan Normal University,Changsha 410081,China)
机构地区:[1]湖南师范大学地理科学学院,地理空间大数据挖掘与应用湖南省重点实验室,中国长沙410081
出 处:《湖南师范大学自然科学学报》2021年第5期40-49,共10页Journal of Natural Science of Hunan Normal University
基 金:国家自然科学基金资助项目(41171342,41071067);湖南省教育厅重点项目(17A127)。
摘 要:基于POI数据,以长沙市为研究对象,通过从百度地图爬取的旅游景点POI数据,采用平均最近邻指数、核密度估计及标准差椭圆等方法来分析长沙市旅游景点的空间格局特征。在此基础上,进一步从旅游景点空间分异的视角,探讨长沙市旅游景点分布模式及集聚特征。分析结果表明:(1)长沙市旅游景点的空间分布整体上表现为集聚型,形成了整体集聚、多中心发展、块状分散的空间格局;(2)从不同景点类型看,其空间分布特征各异,在空间分布形态上主要表现为"单核心","双核心"和"多核心"等不同类型;(3)从不同类型景点均衡度与集聚性看,寺庙类旅游景点分布最为均衡,景点类旅游景点分布最为集中,其他类型旅游景点均具有不同程度的集聚特征。Based on POI data and take Changsha as the research object,through the POI data of tourist attractions crawled from Baidu map,the average nearest neighbor index,kernel density estimation and standard deviation ellipse are used to analyze the spatial pattern characteristics of Changsha tourist attractions.On this basis,from the perspective of the spatial differentiation of tourist attractions,the distribution pattern and agglomeration characteristics of tourist attractions in Changsha are further discussed.The analysis results are as follows.Ⅰ.The spatial distribution of tourist attractions in Changsha city as a whole is agglomerated,forming a spatial pattern of overall agglomeration,multi-center development and massive dispersion.Ⅱ.From the perspective of different types of attractions,their spatial distribution characteristics are different.In terms of spatial distribution,it is mainly manifested in different types such as"single core","dual core"and"multi-core".Ⅲ.From the perspective of the balance and agglomeration of different types of scenic spots,the distribution of temple tourist attractions is the most balanced,and of the distribution scenic tourist attractions is the most concentrated,while other types of tourist attractions have different levels of agglomeration characteristics.
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