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基于地理标记照片数据挖掘的游客流动特征及其形成机制——以苏州为例 被引量:10

The Flow Characteristics of Tourists and Its Forming Mechanism Based on Geo-Tagged Photo Data Mining:Take Suzhou as an Example
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摘要 流动网络的成长和形成,表征了当今社会的流动性特质。文章基于地理标记照片数据,综合运用数据挖掘技术、GIS空间分析技术、多元回归及广义矩等多种分析技术和方法,对苏州城市内部入境游客流动网络结构的时空演化过程及其形成机制进行分析。结果表明:①针对流空间的时空演化分析,在不同的流量约束下,苏州城市内部节点间的流动路径发生较大改变,形成了以姑苏古城区为核心节点,不断向外围地带节点延伸的放射性特征,表现出相对稳定的"一核多点"的空间结构模式。②利用多元回归分析和广义矩(GMM)估计方法进行影响因素及其作用机理的分析,发现资源禀赋、区位交通、市场需求、经济发展、政府行为、基础设施等因素对入境游客在不同时空下产生影响和发生作用。 The growth and formation of mobile networks represent the characteristics of mobility in today’s society.Based on the geographic marker image data,this paper analyzes the spatial-temporal evolution process and formation mechanism of the flow network structure of inbound tourists in suzhou city by comprehensively applying various analysis techniques and methods,such as data mining technology,GIS spatial analysis technology,multiple regression and generalized moment.The results showed that:1)Analyses the space-time evolution of the flow space,under the different flow constraints,suzhou city in great changes of the flow path between internal nodes,formed the gusu ancient city as the core node,continuously to the peripheral zone node characteristics of radioactive showed relatively stable space structure of"one core multipoint"mode.2)Multiple regression analysis and generalized moment(GMM)estimation method are used to analyze the influencing factors and their action mechanism,and it is found that resource endowment,location transportation,market demand,economic development,government behavior,infrastructure and other factors have an impact on inbound tourists in different time and space.The above research provides a useful attempt to reveal the evolution law of the space-time scale of tourist flow and to effectively interpret the flow space.
作者 徐敏 曹芳东 朱海珠 XU Min;CAO Fangdong;ZHU Haizhu(School of Humanities,Jinling Institute of Technology,Nanjing 210038,Jiangsu,China;School of Geographical Science,Nanjing Normal University,Nanjing 210023,Jiangsu,China)
出处 《经济地理》 CSSCI CSCD 北大核心 2020年第4期223-231,共9页 Economic Geography
基金 国家自然科学基金项目(41771154) 教育部人文社会科学研究青年基金项目(14YJC790003)。
关键词 地理标记照片 数据挖掘 游客流动 网络结构 入境旅游 核心-边缘空间结构 区域旅游 geo-tagged photos data mining tourist flows network structure inbound tourism core-edge spatial structure regional tourism
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