| 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：一、来汉中市自驾游的出
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；二、在区域自驾游空间
结构方面，形成游憩点轴—闭环模式，表现为
来汉中自驾游游客的客源地呈近域集中特征，
游客来自西安市方向的特征显著，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；三、在内部自驾游空
间结构方面，形成城景放射—互动模式，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；四、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 旅游时空行为 汉中市 |
| DOI：10.13791/j.cnki.hsfwest.20170511 |
| 分类号: |
| 基金项目: |
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| A Study on Self-Driving Trip’s Temporal-Spatial Behavior Based on the Analysis of Web Logs—A Case Study of Hanzhong City |
|
YANG Bin,CHEN Xiaojian
|
| Abstract: |
| This paper collects travel information of self-driving trip of Hanzhong City, Shanxi
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 the 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 |
