首页 | 本学科首页   官方微博 | 高级检索  
     

中国主要城市入境旅游网络结构演变分析
引用本文:马耀峰,林志慧,刘宪锋,马林. 中国主要城市入境旅游网络结构演变分析[J]. 地理科学, 2014, 34(1): 25-31. DOI: 10.13249/j.cnki.sgs.2014.01.25
作者姓名:马耀峰  林志慧  刘宪锋  马林
作者单位:1.陕西师范大学旅游与环境学院,陕西 西安 710062
2.青岛旅游学校,山东 青岛 266023
3.北京师范大学资源学院,北京 100875
基金项目:国家自然科学基金项目(41271158、41001077)资助
摘    要:基于旅游经济联系模型,运用GIS技术手段,构建中国入境旅游城市的旅游经济联系网络,并对1997年和2010年的Top1、Top5和Top10网络的结构演变特征进行研究。研究发现:① 整体网络规模在缩小,但是最大联系强度和平均联系强度却明显增长,且最大联系强度一直出现在广州和深圳之间;② 整体网络结构处于核心极化阶段,总体呈现“东部强,中西弱”的“L”型分布,一级节点城市北京、上海和广州的集聚作用显著,且进一步增强;③ 旅游城市联系以东部区内联系为主,东部地区城市的集聚作用愈加明显,中部和西部地区城市的集聚作用在减弱;④ 中国入境旅游城市可分为三大体系,形成三极多核的空间格局。

关 键 词:入境旅游  城市网络  经济联系  中国  
收稿时间:2012-11-05
修稿时间:2013-01-18

The Evolution of Network Structure of Inbound Tourist in Major Cities of China
Yao-feng MA,Zhi-hui LIN,Xian-feng LIU,Lin MA. The Evolution of Network Structure of Inbound Tourist in Major Cities of China[J]. Scientia Geographica Sinica, 2014, 34(1): 25-31. DOI: 10.13249/j.cnki.sgs.2014.01.25
Authors:Yao-feng MA  Zhi-hui LIN  Xian-feng LIU  Lin MA
Affiliation:1.College of Tourism and Environment, Shaanxi Normal University, Xi’an, Shaanxi 710062, China
2.Qingdao Tourism School, Qingdao, Shandong 266023, China
3.College of Resources Science and Technology, Beijing Normal University, Beijing 100875, China
Abstract:This article established the Inbound Tourist urban network that is linked by the model of tourist economic interrelationships employing GIS. Then the spatiotemporal evolution characteristics of Top1, Top5, Top10 networks in 1997 and 2010 were studied. The conclusions can be drawn as follows: 1) The network size is shrinking, but the maximum runoff and average runoff significantly grow, and the maximum runoff has occurred between Guangzhou and Shenzhen. 2) The agglomeration effect in a few core cities is more prominent. The structure of China inbound tourism is at the stage of core polarization, showing an overall “L” shaped distribution which means “the agglomeration effect of tourism in the eastern China is strong, but that in central and western China is weak”. Beijing, Shanghai, Guangzhou were the first class node cities, whose agglomeration effect significantly increased, Xi’an and Guilin were declined, while Shenzhen and Tianjin raised in 1997 and 2010. Agglomeration effect of cities in the eastern China was more obvious, while it declined in central and western China. The in-degree of cities in the western China was significantly higher than that in central China, but this advantage was reducing. That in the central China grew, but the economic interrelationship did not significant grow, still obviously lower than that in cities of the eastern and western China; 3) The in-degree and the strength of economic interrelationship were not proportional, Beijing’s in-degree was the highest, but its economic interrelationship was ranked only fourth, behind Guangzhou, Shenzhen and Shanghai. The first reason is the cities’ spatial distribution density, and the other is that the inbound tourism level of the two regions is very high, coupled with its relatively close distance. This also resulted in Zhuhai and Wuxi’s in-degrees were not high, but the economic interrelationships were very close; 4) From the bidirectional flow within the region and between regions, it is found that within the eastern area, the economic interrelationships are the highest and the most important relationship all over the country. The centers of the eastern China are Shanghai, Guangzhou, Beijing and Shenzhen. The centers of the western China are Xi’an, Chengdu, Chongqing and Guilin, whose relation with cities in the western China is very close, but that with other areas is not close. The centers of the central area are Changsha and Wuhan, whose relation with cities in the western is not close, but that with other areas is very close; 5) According to the network structure we can divide China inbound tourist urban into three systems: Beijing system, Shanghai system and Guangzhou system, which displays the patterns of “three centers, several cores”. Three centers are the first class node cities, Beijing, Shanghai and Guangzhou. Several cores are the second node and third node cities. The several cores of Beijing system are Tianjin, Xi’an, Qingdao and Dalian, the several cores of Shanghai system are Suzhou, Nanjing, Hangzhou, Changsha and Wuhan, and the several cores of Guangzhou system are Shenzhen, Zhuhai, Xiamen, Fuzhou, Chengdu, Chongqing and Guilin.
Keywords:inbound tourist  urban network  economic interrelationships  China  
本文献已被 CNKI 等数据库收录!
点击此处可从《地理科学》浏览原始摘要信息
点击此处可从《地理科学》下载全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号