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中国城市旅游气候舒适性分析

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气候是影响人们旅游活动的重要因子.本文选取了人生气候舒适指数来衡量城市旅游气候的舒适性,该指数包括温湿指数、风效指数、着衣指数.首先,计算了全国44个城市的人生气候舒适指数以及偏离度,分析了旅游气候舒适期,发现其中19个城市舒适气候期是5个月,舒适期过短或者过长的城市都较少.按照舒适期的长短以及舒适月分布的连续性,将舒适期分为3类2型.其次,从季节上看,春秋季节特别是4月、10月,除热带地区外的全国大部分地区气候都较适宜.夏季,全国大部分地区气候发生热偏,以海口气候偏离度最大,丽江、昆明、拉萨等气候都相对比较适宜,可以成为人们避暑的选择地;而冬季,全国大部分地区气候发生冷偏,以哈尔滨气候偏离度最大,地处亚热带、热带地区的城市人生气候感觉舒适.最后,为评价各城市的气候综合状况,利用各人生气候指数偏离度,通过Kohonen神经网络方法,将44个城市分成5类.
Climate Suitability Index for City Tourism in China
Climate is the main factor in tourism development This article used the human climate suitability index to evaluate the climate suitability of cities, including the THI(temperature humidity index)、K( index of wind effect ) and ICL (index of clothing). Firstly, the article calculated the value and the bias value of the human climate suitability of 44 cities in China, and analyzed the suitable duration and the change of the index value and the bias value of the human climate suitability. Then it was found that there were 19 cities with five suitable months and few cities with too long or too short suitable duration. According to the climate suitability duration and the distribution of suitability months, the article classified the climate suitability duration into three classes and two types. Secondly, the comfortable seasons are spring and autumn, the comfortable months are April and October for most places except the tropical ones. In summer,the climate tends to be heated bias,particularly in Haikou,where the bias reaches the maximum, and the comfortable places are Lijiang,Kunming and so on. In winter,the climate tends to be cold bias, particularly in Harbin,where the bias value reaches the maximum,but in the tropical or subtropical places people feel comfortable. Lastly,to evaluate the overall climate condition of the cities,the article classified 44 cities into five clusters by means of Kohonen neural network self-organization in Matlab. The results show the fist class, with the highest climate suitability bias, is comfortable in summer and suitable for tourism. People should prevent coldness in the other seasons,particularly in winter,but the special cold in the north can attract people to travel. The second class is comfortable in winter, most of which are coastal cities and suitable to travel. The third class, with the average bias level, has the comfortable seasons of summer and winter, The forth class, with the lowest bias level, is cool in summer and warm in winter, and the overall climate is comfortable, so the cities included have the climate advantage to develop tourism. The fifth class,where is hot in summer and cold in winter,must make full use of the comfortable spring and autumn and develop the particular tourism resource in order to improve the regional tourism competition.

THIKICLNeural network

刘清春、王铮、许世远

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华东师范大学地理信息科学教育部重点实验室,上海,200062

中国科学院科技政策与管理科学研究所,北京,100080

温湿指数 风效指数 着衣指数 神经网络

国家自然科学基金

40371007

2007

资源科学
中国科学院地理科学与资源研究所 中国自然资源学会

资源科学

CSTPCDCSSCICSCDCHSSCD北大核心
影响因子:2.408
ISSN:1007-7588
年,卷(期):2007.29(1)
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