| 兰州市旅游气候舒适度与客流量关系分析 |
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| 引用本文： | 孟丽霞.兰州市旅游气候舒适度与客流量关系分析[J].新疆气象,2017,11(5):89-94. |
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| 作者姓名： | 孟丽霞 |
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| 作者单位： | 甘肃省气象服务中心 |
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| 基金项目： | 甘肃省气象局气象科研项目(GSMAMs2017-07)。 |
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| 摘 要： | 基于兰州市1981—2010年的气象观测资料,采用温湿指数、风效指数和着衣指数3个指标,对兰州市旅游气候舒适度进行分析评价。结果表明,兰州市全年旅游气候舒适期可达7个月,旅游最舒适月份从5月持续到9月,不适宜期主要集中在冬季的1月、12月。结合2010—2014年兰州市旅游客流量年内变化数据,划分了兰州市旅游淡旺季和客流量月指数;综合分析客流量月指数与三个指数关系得出:客流量年内变化与气候舒适度呈明显的相关性,客流量月指数与温湿指数、风效指数呈正相关,与着衣指数呈负相关,且3个指数与客流量月指数相关性较好,都在0.7以上。
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| 关 键 词： | 旅游气候舒适度 客流量变化 兰州 相关性分析 |
| 收稿时间： | 2017/6/12 0:00:00 |
| 修稿时间： | 2017/9/7 0:00:00 |
A Correlation Analysis Between Climate Comfort Degree and Variation of Tourists in Lanzhou |
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| menglixia.A Correlation Analysis Between Climate Comfort Degree and Variation of Tourists in Lanzhou[J].Bimonthly of Xinjiang Meteorology,2017,11(5):89-94. |
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| Authors: | menglixia |
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| Abstract: | Climate comfortable degree is an important factor that influences the tourist destinations. It directly affects yearly variation of tourist. Based on 30 years(1981-2010) climate data of Lanzhou, adopting temperature humidity index(THI),wind effect index(K) and clothing index (ICL),this article makes a comment on the tourist climate comfort in Lanzhou. The result shows as follows. Lanzhou has the long period with suitable climatic conditions for tourism, and tourism climate comfort period could reach 7 months; the best tourism climate comfort months lasted from May to September, yet uncomfortable in winter time mainly from December to January. Combining yearly variation of tourists in Lanzhou in the past five years(2010-2014) , the result shows that: the correlation of monthly variation of tourists and climate comfort degree is significantly; there are positive correlation between the monthly visitors proportion index and the THI,K; there are negative correlation between the monthly visitors proportion index and the ICL;and the correlation coefficient between the monthly visitors proportion index and three climate comfort index is above 0.7. |
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| Keywords: | climate comfortable degree variation of tourists Lanzhou correlation analysis |
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