Multiscale Characteristics and Connection Mechanisms of Attraction Networks:A Trajectory Data Mining Approach Leveraging Geotagged Data  

作　　者：JIANG Hongqiang WEI Ye MEI Lin WANG Zhaobo 

机构地区：[1]School of Resource and Environment Engineering,Ludong University,Yantai 264025,China [2]School of Geographical Sciences,Northeast Normal University,Changchun 130024,China [3]Changchun University of Finance and Economics,Changchun 130122,China [4]Jilin Jizhi City Architectural Design Co.,LTD,Changchun 130012,China

出　　处：《Chinese Geographical Science》2024年第3期533-547,共15页中国地理科学（英文版）

基　　金：Under the auspices of the National Natural Science Foundation of China(No.41971202);the National Natural Science Foundation of China(No.42201181);the Fundamental research funding targets for central universities(No.2412022QD002)。

摘　　要：Urban tourism is considered a complex system,and multiscale exploration of the organizational patterns of attraction networks has become a topical issue in urban tourism,so exploring the multiscale characteristics and connection mechanisms of attraction networks is important for understanding the linkages between attractions and even the future destination planning.This paper uses geotagging data to compare the links between attractions in Beijing,China during four different periods:the pre-Olympic period(2004–2007),the Olympic Games and subsequent‘heat period’(2008–2013),the post-Olympic period(2014–2019),and the COVID-19(Corona Virus Disease 2019)pandemic period(2020–2021).The aim is to better understand the evolution and patterns of attraction networks at different scales in Beijing and to provide insights for tourism planning in the destination.The results show that the macro,meso-,and microscales network characteristics of attraction networks have inherent logical relationships that can explain the commonalities and differences in the development process of tourism networks.The macroscale attraction network degree Matthew effect is significant in the four different periods and exhibits a morphological monocentric structure,suggesting that new entrants are more likely to be associated with attractions that already have high value.The mesoscale links attractions according to the common purpose of tourists,and the results of the community segmentation of the attraction networks in the four different periods suggest that the functional polycentric structure describes their clustering effect,and the weak links between clusters result from attractions bound by incomplete information and distance,and the functional polycentric structure with a generally more efficient network of clusters.The pattern structure at the microscale reveals the topological transformation relationship of the regional collaboration pattern,and the attraction network structure in the four different periods has a very similar imp

关 键 词：attraction network travel mobility polycentric structure network motif connectivity mechanism destination management organization(DMO) destination planning Beijing China 

分 类 号：P208[天文地球—地图制图学与地理信息工程] F592.7[天文地球—测绘科学与技术]