[1]丁 鼎,葛军莲,龙 毅,等.基于运营商客流大数据的乡村旅游点类型划分研究——以南京市江宁区为例[J].南京师范大学学报(自然科学版),2018,41(03):116.[doi:10.3969/j.issn.1001-4616.2018.03.018]
 Ding Ding,Ge Junlian,Long Yi,et al.The Type Classification of Rural Tourist Sites Based onthe Passenger Flow Big Data of Operators—A Case Study of Jiangning District of Nanjing[J].Journal of Nanjing Normal University(Natural Science Edition),2018,41(03):116.[doi:10.3969/j.issn.1001-4616.2018.03.018]
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基于运营商客流大数据的乡村旅游点类型划分研究——以南京市江宁区为例()
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《南京师范大学学报》(自然科学版)[ISSN:1001-4616/CN:32-1239/N]

卷:
第41卷
期数:
2018年03期
页码:
116
栏目:
·地理学·
出版日期:
2018-09-30

文章信息/Info

Title:
The Type Classification of Rural Tourist Sites Based onthe Passenger Flow Big Data of Operators—A Case Study of Jiangning District of Nanjing
文章编号:
1001-4616(2018)03-0116-06
作者:
丁 鼎1葛军莲1龙 毅123周贵鹏1
(1.南京师范大学地理科学学院,江苏 南京 210023)(2.南京师范大学虚拟地理环境教育部重点实验室,江苏 南京 210023)(3.江苏省地理信息资源开发与利用协同创新中心,江苏 南京 210023)
Author(s):
Ding Ding1Ge Junlian1Long Yi123Zhou Guipeng1
(1.School of Geography Science,Nanjing Normal University,Nanjing 210023,China)(2.Key Laboratory of Virtual Geographic Environment,Ministry of Education,Nanjing Normal University,Nanjing 210023,China)(3.Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application,Nanjing 210023,China)
关键词:
客流大数据乡村旅游点类型划分南京市江宁区
Keywords:
passenger flow big datarural tourist sitestype classificationJiangning District of Nanjing
分类号:
K901.2
DOI:
10.3969/j.issn.1001-4616.2018.03.018
文献标志码:
A
摘要:
基于运营商客流大数据,以南京市江宁区22个星级乡村旅游点为研究对象,从客流时间序列特征与客流空间结构特征视角出发,利用层次聚类分析方法对其进行类型划分. 结果显示:按照客流时间序列特征可分为客流单峰型、客流双峰型和客流多峰型3类乡村旅游点,按照客流空间结构特征分为强市场吸引型、中市场吸引型和弱市场吸引型3类乡村旅游点,且这两种划分结果有高度的一致性,并探讨了产生一致性的原因.
Abstract:
This paper takes 22 star-rating rural tourist sites in Jiangning District of Nanjing as research area,and uses hierarchical cluster analysis to divide them into different types,based on the passenger flow big data of operators. The study has two perspectives,one based on the time series characteristics of passenger flow,while the other on the spatial structure characteristics. The result shows that,the rural tourist sites can be divided into unimodal,biomodal or multimodal passenger flow patterns from the former perspective,or strong,medium and weak market attraction patterns from the latter. The classifications of both have high resemblance,the reasons of the resemblance are also discussed in the study.

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备注/Memo

备注/Memo:
收稿日期:2018-04-30.
基金项目:国家自然科学基金(青年基金)(41301144)、江苏省普通高校研究生科研创新计划项目(CXZZ13_0404)、南京师范大学英才培养计划项目.
通讯联系人:葛军莲,博士研究生,讲师,研究方向:旅游信息化. E-mail:gejunlian@njnu.edu.cn
更新日期/Last Update: 2018-11-19