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基于网络日志内容分析的自驾游时空行为研究
杨斌,陈晓键
作者单位E-mail
杨斌 西安建筑科技大学硕士研究生陕西建工集团有限公司建筑设计院 youngb@126.com 
陈晓键 西安建筑科技大学  
摘要:
本文以陕西汉中市为研究案例,通过网络日志采集市域范围内的自驾游出行信息,并采用数据挖掘方式对自驾游时空行为进行分析。结果表明:①来汉中市自驾出游时间集中在4月和10月,平均逗留时间为2.098天,日均访问节点个数为1.80个,以短途、短时观光出游为主,具有长时维度的季相模式和短时维度的周末模式。②在区域自驾游结构方面,形成游憩点轴-闭环模式,表现为来汉中自驾游游客客源地呈现近域集中特征,依靠西安市方向显著,自驾旅游流线和路径以高等级道路为主骨架,来汉中市自驾游以西汉高速和G108为主体交通廊道,辐射周边国道和省道沿线。③在内部自驾游结构方面,形成城景放射-互动模式,在汉中市境内自驾游游客行为访问热点呈现高聚集特征,以汉中市区、南郑县城和勉县县城周边景区(点)为主,辐射带动围绕城市和景区近邻集群区域。④结合旅游时空行为的发生机制,发现来汉中自驾旅游时空行为以时间规限、交通指向、设施贴近、营销刺激四大机制影响其形成和组织。
关键词:  网络日志,自驾游,时空行为,汉中市
DOI:
分类号:G642
基金项目:
A study of self-driving trip’s temporal-spatial behavior based on an analysis of web logs —a case study of Hanzhong city
yangbin,chenxiaojian
Abstract:
This paper collects travel information of self-driving trip of Hanzhong city,Shaanxi province, by means of web logs. At the same time, the paper analyzes the temporal-spatial behavior of self-driving trip by data exploitation. The results show that:(1) The self-driving trip to Hanzhong focuses on the months of April and October. In April, the rape flowers are in full bloom, the average stay of tourists is about 2.098 days, the tourists are primarily for excursions, and the average daily access node is 1.80. (2)The source of tourists to Hanzhong city is characterized by immediate clustering, and Xi’an, capital city of Shaanxi province, is the main source and the interchange city for car renting or car sharing from other regions. (3)The hotspot of self-driving trips inside of Hanzhong city appear the features of high aggregation, mainly in the inner city of Hanzhong, Nanzheng county, Mian county and its suburban areas. Hanzhong city is the transferring node for self-driving, and it becomes an important visiting point since the facilities have largely been improved. (4) The route of self-driving trip takes the high grade road, visitors to Hanzhong primarily take the Xihan express way and the national highway G108 as well as the surrounding national roads and provincial roads.(5)This paper has a relatively strong geographical adaptability and technical operability for the study of self-driving trip’s spatiotemporal behavior based on an analysis of web logs, and it can provide new thoughts for self-driving trip’s planning and management research.
Key words:  Web Logs  Self-driving trip  Temporal-spatial Behavior  Hanzhong City