海南旅游客流量年内变化与气候的相关性分析

气候是旅游资源不可或缺的组成部分,也是影响旅游地开发的重要因素,直接影响到旅游季节的长短及旅游客流的年内变化。利用海南9个气象站点自建站以来的气候资料及近5年旅游统计资料,通过特吉旺气候舒适指数、相关分析和回归分析等方法,分析海南气候舒适度及其与旅游客流量年内变化的相关性。结果表明:11月~3月是海南旅游的最适宜期;气候对海南旅游客流量有显著影响,以气温为主导的气候舒适度是海南旅游客流年内淡旺季变化及游客旅游决策的主要影响因素;温度与海南旅游客流量呈显著负相关关系;与海口比较而言,三亚旅游业对气候更加敏感。本项研究对更好地将气候整合到旅游产品中进行宣传促销、提高产品吸引力,对海南旅游业发展规划,对提前预判游客规模尽早做出对策安排及旅游投资有很强的现实指导意义。

An analysis of annual variation of tourist flows and climate change in Hainan Province

Climate resource is one of the most important natural tourism resources in tourism development. The plentiful climate resources not only have the special landscape function, but also have impact on tourism demand. Climate comfort degree effectively responses the comfort of climate in tourism destination for tourist, it is the key factor to tourism development. It directly affects the length of tourism season and annual variation of tourist flows. The climate data of 30 years from nine meteorological stations and tourism data of 5 years from tourism administration of Hainan province were used in this paper. By adopting Comfort Index of W. H. Terjung, correlation and regression analysis, this article analyzed the relationship between climate and annual variation of tourist flows in Hainan province. The results suggested that the advantage of tourism in Hainan was winter and the most comfortable period of tourism began from current November to next March. According to the correlation analysis, climate influences tourist flows remarkably, and comfortable degree of climate is the main factor that influences annual variation of tourist flows and tourism decision to Hainan. Furthermore, air temperature correlates negatively to tourist flows. Compared to Haikou, tourism of Sanya is more sensitive to climate. In view of the importance of climate to tourism in Hainan, it will improve the attractiveness of tourism product when climate factor is integrated into tourism product for better advertisement. At the same time, for the negative correlation between tourist flows and climate, it is easier to forecast tourist flows so that we can make preparation ahead of schedule. Therefore, this study provides important references for tourism planning and investment.