运用空间自相关分析中国入境旅游增长空间格局

Application of Spatial Autocorrelation Analysis to the Spatial Pattern of Inbound Tourism Increase in China

空间自相关分析是空间统计学的一个重要组成部分,在设定显著性水平下研究邻近位置属性(或现象)之间的相关性,是认识空间格局的有效手段。中国省级水平上的入境旅游区域增长空间自相关分析显示,1996年至2004年期间,除1997年外,我国在其它时期均不存在显著的全局空间自相关,表明邻近省区入境旅游区域增长之间的关系在整体上既不综合表现为趋同,也不综合表现为趋异,入境旅游区域增长整体空间格局为随机格局;各个时期均有一个或少数几个省区与邻近省区的局部空间自相关显著,在局部区域呈现出集聚或离散的空间格局。这类局部区域的个数随时间变化,但2001年以后趋于稳定,在没有对入境旅游产生重大冲击事件发生的正常时期为2个,即以上海为核心的共同增长集聚格局区域和以广东省为中心的“中高周低”的离散格局区域(α=0.05,双侧显著性检验)。

As an important part of Spatial Statistics, spatial autocorrelation analysis studies the degree to which objects or activities are similar to other objects or activities located nearby at a significance level, and is an efficient means to understand the spatial pattern based on the relation between objects and their neighbours. Using spatial autocorrelation techniques,the inbound tourism increase in the period of 1996 -2004 in China is studied, and the results show that there is no significant global spatial autocorrelation in the data sets of the inbound tourism increase at province level and the patterns are random on the whole except the year of 1997; there are one or two significant LISAs every year, and the patterns in the subregions are clustered or dispersed respectively. The number of these patterns are changed during the period above, but from 2001, the number is two stably, namely a clustered one influenced markedly by Shanghai and a dispersed one governed by Guangdong province （ α = 0.05, two - tailed）.