基于网络日志内容分析的自驾游时空行为研究——以陕西汉中市为例

A Study on Self-Driving Trip's Temporal-Spatial Behavior Based on the Analysis of Web Logs——A Case Study of Hanzhong City

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。

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 about2.098days,the tourists are primarily for excursions,and the average daily access node is1.80.2.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 G108as 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.