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气候舒适度对热点城市入境游客时空变化的影响
引用本文:马丽君,孙根年,马耀峰,王洁洁.气候舒适度对热点城市入境游客时空变化的影响[J].旅游学刊,2011,26(1):45-50.
作者姓名:马丽君  孙根年  马耀峰  王洁洁
作者单位:陕西师范大学旅游与环境学院,陕西,西安,710062
基金项目:国家社会科学基金,陕西省社会科学基金,陕西师范大学研究生培养创新基金
摘    要:文章选取东部18个城市分析气候舒适度的年内时空变化,将其年内变化分为3种类型:倒"U"形、"M"形、宽"U"形。收集2005~2007年各城市入境客流量,分析其年内时空变化状况,将其年内变化分为4种类型:"W"形、倒"U"形、"M"形、"U"形。年内客流量重心变化与气候舒适度重心变化具有很强的时间同步性,说明气候舒适度是影响客流量空间分布的重要因素。在客流量月指数与气候舒适度指数比较的基础上,建立了入境旅游客流量月指数模拟模型。利用旅游资源丰度、经济发展水平、综合气候舒适指数3个因素,建立其与客流量地域分布的统计关系,结果显示:综合气候舒适度指数每变化1个单位,客流量将增加(或减少)7.659万人。

关 键 词:气候舒适度  客流量月变化  空间分布  相关分析

An Analysis on the Influence of Climate Comfortable Degree on Temporal and Spatial Variation of Inbound Tourists in China's Hot Cities
MA Li-jun,SUN Gen-nian,MA Yao-feng,WANG Jie-jie.An Analysis on the Influence of Climate Comfortable Degree on Temporal and Spatial Variation of Inbound Tourists in China's Hot Cities[J].Tourism Tribune,2011,26(1):45-50.
Authors:MA Li-jun  SUN Gen-nian  MA Yao-feng  WANG Jie-jie
Institution:(College of Tourism and Environment Science,Shaanxi Normal University,Xi'an 710062,China)
Abstract:The paper analyzes the temporal and spatial variation of climate comfortable degree in 18 cities in east China and yearly variations are divided into 3 types:reversed "U"shape,"M" shape and "W " shape.The number of inbound tourists from 2005 to 2007 in these cities is collected to analyze their spatial and temporal variation.Their yearly variations are divided into 4 types:"W","reversed U","M"and"U"shapes respectively.There is a strong time synchronization between the variation of climate comfortable degree's gravity center and the variation of inbound tourist 's gravity center.This shows that climate comfortable degree is an important factor that affects the spatial distribution of inbound tourists.Based on the comparison of monthly index of tourist flows and that of climate comfortable degree,a simulated model of monthly index of inbound tourist flows is established.By using 3 factors of abundant tourism resources,economic development level and comprehensive climate comfortable degree index,their statistical relation is thus founded.The results show that while the comprehensive climate comfortable index changes"one unit",the inbound tourists will increase(or decrease) 76,590.
Keywords:climate comfortable degree  monthly variation of tourist flow  spatial distribution  correlative analysis
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