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青藏高原气候变化敏感因子多源遥感监测与分析研究
中文摘要

气候是人类环境最活跃的组成部分,气候变化对人类活动及地球环境的影响日益显著,对气候变化的研究具有重要的科学意义和现实意义。气候变化敏感因子能够影响和反应气候变化。青藏高原是“地球第三极”,特殊的地貌特征及对全球气候变化的影响,决定了研究青藏高原的重要意义。因此本文的主要工作,利用多源遥感数据对青藏高原地区气候变化敏感因子的时空变化及其与气候变化的相互关系进行较系统的研究和分析,从中得出了一些新的认识和结论。 本文首先较全面的回顾和分析了以往研究成果,指出由于采用的方法和数据不同,研究者得出的结论不尽相同,研究内容往往局限于一个方面,并没有进行全面的系统研究。然后本文概述了研究中常用的数学方法。根据青藏高原特殊的地貌特征和气候特征,提出利用植被覆盖、地表温度、积雪覆盖三个典型地表参数作为高原地区气候变化的敏感因子。在综合考虑遥感不同波段电磁特性的基础上,提出利用可见光-近红外、热红外、微波多源遥感数据对高原地区气候变化敏感因子进行遥感监测和分析。利用统计分析方法探讨了气候敏感因子与气候变化之间的关系。 论文的工作及结论主要体现在如下几个方面: 1.利用光学遥感数据对高原地区气候变化敏感因子进行监测和分析。高原地区植被覆盖分布呈西北至东南递增分布,在时间变化上,高原植被在4月份进入生长期,一直持续到10月份。NDVI时间变化曲线显示,8月份高原植被覆盖最好,12月份植被覆盖状况最差;地表温度状况与地势高度密切相关,其等温线基本与地形等高线走向一致。地表温度呈现非常明显的季节变化;积雪覆盖呈高山多雪腹地少雪的分布特点。在季节变化上,发现冬季雪盖面积最大,春秋两季次之,夏季则基本无雪。 2.利用微波遥感数据对高原地区气候变化敏感因子进行监测和分析。将被动微波遥感数据应用到青藏高原植被覆盖变化监测上,并与光学遥感植被指数NDVI作对比,发现两者都能表示出植被的疏密程度,但NDVI表示植被覆盖的层次相对丰富。同时我们发现,MVI对稀疏植被的变化非常敏感。 3.分析了高原地区植被覆盖与气候因子之间的相互关系。从三个方面分别分析了两者的关系,发现植被与气温的相互关系大于与降水的相互关系。不同植被类型的植被与气候因子的相关关系,以相关系数由大到小依次为:温带、亚热带高寒草原>温带、亚热带高寒草甸>高山灌木、稀疏植被>草原和稀疏灌木>温带丛生禾草草原>荒漠。 4.探讨了高原冬春积雪与中国东部夏季降水的关系。发现冬季雪盖增大(减少),华南大部分地区夏季降水偏少(多),而东北三省黑龙江流域夏季降水增多(减少)。高原春季雪盖对我国华北夏季降水不明显,而对黄淮地区夏季降水影响明显。春季高原雪盖增多(减少),黄淮地区夏季降水减少(增多)。 关键词:气候变化敏感因子 多源遥感数据 植被覆盖 地表温度 积雪覆盖

英文摘要

The climate is the most active part of human environment. The impact of climate change over human activity and the earth environment is increasingly notable. Therefore, the research on climate change has important scientific and practical significance. The climate change sensitive factor is able to affect and reflect climate change. Qinghai-Tibet Plateau is "the third pole of the earth". Its special landscape feature and its impact on global climate change determines the importance of the Qinghai-Tibet Plateau research. Making use of the multi-source remote sensing data, study and analyze the space-time change of sensitive factor of climate change on Qinghai-Tibet Plateau and the relationship between sensitive factor and climate change, and we draw some new conclusions. Fist of all, this dissertation reviews and analyzes the past research, and points out that researchers draw different conclusions due to different methods and data. Then, we overview the common mathematical method. According to the landscape feature and climate feature of Qinghai-Tibet Plateau. We propose that we take vegetation cover, land surface temperature and snow cover as sensitive factor of climate change. In consideration of the electromagnetic properties of the different remote sensing band, we proposed that visible light - near infrared, thermal infrared and microwave band data, the three types of remote sensing data are treated as multi-source data and are used to monitor and analyze sensitive factor of climate change on Qinghai-Tibet plateau .At last, we discuss the relationship between the sensitive factor and climate change, using mathematical statistical methods. The major contribution and conclusion of the dissertation are as follows: 1.To monitor and analyze the sensitive factor of climate change on Tibet plateau using optical remote sensing data. Vegetation cover distribution on plateau area is incrementally northwest to the southeast. On temporal change, vegetation go into the growing season in April, until October. NDVI time-serial curve shows that in August the plateau vegetation cover is in the best situation, and in December is in the worst; Thermal situation of the land surface is closely related to the surface topography, Whose isothermal line basic and landform contour line are consistent basically. Thermal situation of the land surface has a very significant seasonal variation; Snow cover covers the distribution characteristic that there is much snow in mountain and less in hinderland. On seasonal change, it shows that snow cover in winter is relatively wide, and in spring and autumn is relatively small, and there is scarcely any snow in summer. 2.To monitor and analyze the sensitive factor of climate change on Tibet plateau using microwave remote sensing data. Passive microwave remote sensing data is applied to monitor vegetation cover changes on Qinghai-Tibet Plateau. Passive microwave remote sensing data is contrast with NDVI, that shows that both can show the density of vegetation, but NDVI that the level of vegetation cover is relatively abundant. At the same time, we find that, MVI is very sensitive to the sparse vegetation changes. 3.To analyze the correlation between vegetation cover on Tibet plateau with climate factor. The both relationship is analyzed from three aspects respectively, which shows the correlation between vegetation cover with temperature is larger than that between vegetation cover with precipitation. According to correlation coefficient, the sort of relationship between different vegetation and climate factor is: temperate, subtropical alpine grassland> temperate, subtropical alpine meadow> alpine shrubs, sparse vegetation> sparse grassland and shrubs> proliferation of temperate grasses Prairie> desertification. 4.To discuss the relations between winter-spring snow cover on the plateau and the east China summer precipitation. It shows that if snow cover on the plateau in winter increase (decrease), the precipitation in summer in the most South China districts will be few (much), but the Northeast three province Heilongjiang valley will be much(few). The effect of snow cover on the plateau in spring is not obvious on the precipitation in North China in summer, but is significant on the precipitation in Huang-Huai areas in summer. If snow cover on the plateau in spring increase(decrease),the precipitation in summer in Huang-Huai areas will be few(much). KEY WORDS: sensitive factor of climate change, multi-source remote sensing data, vegetation cover, land surface temperature , snow cover

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