旅游地理

旅游流齐夫结构及空间差异化特征——以四川省为例

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  • 1. 南京大学城市与资源学系,南京 210093;
    2. 四川师范大学城乡规划与景观设计研究所,成都 610068;
    3. 四川师范大学地理与资源科学学院,成都 610068;
    4. 四川大学建筑与环境学院,成都 610065;
    5. 江苏省镇江市规划局,镇江 212001
杨国良 (1965-), 男, 重庆市大足人, 副教授, 中国地理学会会员, 主要从事旅游规划、旅游地理方面研究, 发表论文30余篇。E-mail:geoygl@163.com

收稿日期: 2006-06-21

  修回日期: 2006-09-19

  网络出版日期: 2006-12-25

基金资助

国家自然科学基金项目 (40371030); 四川省科技厅重点项目 (05ZR025-111)

Zipf Structure and Difference Degree of Tourist Flow Size System:A Case Study of Sichuan Province

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  • 1. Department of Urban and Resources Sciences, Nanjing University, Nanjing 210093, China;
    2. Urban-rural Planning and Landscape Design Institute, Sichuan Normal University, Chengdu 610068, China;
    3. College of Environmental and Geographical Sciences, Sichuan Normal University, Chengdu 610068, China;
    4. Architecture and Environment College of Sichuan University, Chengdu 610065, China;
    5. Zhenjiang Urban Planning Department, Zhenjiang 212001, China

Received date: 2006-06-21

  Revised date: 2006-09-19

  Online published: 2006-12-25

Supported by

National Natural Science Foundation of China, No.40371030; Key Project of Science and Technology Foundation of Sichuan Province, No.05ZR025-111

摘要

借用Zipf指标和差异度指标,采取由“假设”到“论证”的研究方法证明旅游流规模结构符合Zipf法则。以1996年至2004年四川省国内旅游统计数据为样本,研究了旅游流的规模等级结构特征。结果表明,国内旅游流规模结构符合Zipf定律,具有分段特征,用回归拟合可进一步分析各标度区的内部结构特点。标度区可分为有效标度区和无效标度区两种类型。从四川省旅游业的发展情况看,旅游流规模结构中无效标度区的空间分布面积逐渐减少,而有效标度区面积正在逐步扩大。Zipf参数可以用来进行标度区分段,分析有效标度区的内部结构和旅游流总体结构体系的变化规律;对不满足Zipf法则的分段区域,则用均衡度和差异度分析其内部结构的差异化程度。用Zipf参数分析有效标度区,用均衡度和差异度指标分析无效标度区旅游流规模结构所得结果既与客观实际相符合,同时又能更清晰地反映该结构的标度分段特征、各标度区内部的差异化程度以及历年所发生的结构分布变化规律,这对丰富旅游流的分析方法具有重要价值。

本文引用格式

杨国良, 张捷, 艾南山, 刘波 . 旅游流齐夫结构及空间差异化特征——以四川省为例[J]. 地理学报, 2006 , 61(12) : 1281 -1289 . DOI: 10.11821/xb200612005

Abstract

The Zipf theory is the law to study the relation between word frequency and word sequence which is now extensively used in city size structure, city spatial fractal, economics, sociology, and so on. From supposition to discussion, this paper proves that tourist flow size grading structure is in conformity with the Zipf theory in aid of the Zipf and difference degree index. The scaling section feature and internal structural difference in each scaling range of domestic and inbound tourist flow size grading structure in Sichuan province were studied in this paper based on statistic data of domestic tourist flow from 1996 to 2004. The result shows that tourist flow size grading structure has possessed the Zipf feature, even could be sectioned by fractal dimension scaling in certain years, and the bifurcation points of each scaling range can be determined by regression equations. The scaling section may be divided into two types, which are effective and ineffective scaling sections. Viewing from the tourism development in Sichuan province, the space distribution area of tourist flow ineffective scaling section is reducing and effective scaling section area is increasing. The Zipf index can be used to divide the scope of each scaling section and analyze the internal structural feature of effective scaling section and the changing law of the tourist flow size grading structure. For the region without the unobvious Zipf feature, equilibrium degree and difference index can be used to study the difference of the internal structure. The study shows that the results of effective scaling section being analyzed by the Zipf index and ineffective scaling section by equilibrium degree and difference index accord with the objective reality, also clearly reflect the structure scaling section feature, the internal structural difference of each section and the changing law of the total structure system. This is very important to enrich the methods of analyzing tourist flow size grading structure. Concerning the tourist flow size structure in Sichuan province, the Zipf index "q" of domestic tourist flow is mostly between one and two before 2002, and the size grading structure system assumes Pareto distribution pattern; after 2003, the Zipf index "q" further reduces and the tourist flow size structure is turning to logarithmic regular distribution pattern.

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