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基于ETM+热红外波段的郑州地区地表温度反演算法研究.doc

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基于ETM+热红外波段的郑州地区地表温度反演算法研究.doc

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基于ETM+热红外波段的郑州地区地表温度反演算法研究.doc

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文档介绍:基于ETM+热红外波段的郑州地区地表温度反演算法研究
摘要
陆地表面温度在地一气相互作用过程中扮演着十分重要的角色,是全球变化研究的关键参数,对水文、生态、环境和生物地球化学等研究有重要意义,并且在农业气象、热惯量计算等方面也有重要的应用价值,定量精确反演陆面温度的成果将推动旱灾预报和作物缺水研究、农作物产量估算、数值天气预报、全球气候变化和全球碳平衡等领域研究的进展。因此,利用卫星遥感资料进行地表温度的反演己成为目前遥感定量研究中的重要任务之一。区域性的地表温度,是该地区热能量分布的重要参数,通过遥感影像获得是最便捷、,而从热红外遥感图像中提取出温度信息是热红外遥感技术应用的前提。本文在地表温度研究进展的理论基础上,以黄河中下游沿岸城市郑州市和开封市进行了案例研究。在遥感和GIS技术的支持下, 2001年5月10日的Landsat7ETM+热红外遥感影像数据采用单窗算法进行定量反演,得到了研究区地表温度的空间分布变化。
关键词:热红外遥感; 地表温度反演; 单窗算法;
ABSTRACT
Land surface temperature is playing a very important role in ground-atmosphere interaction. It is a key parameter in the global change studies, playing very important meanings in researches such as hydrology, ecology, environment and biological geochemistry, and there is important application value in calculating agricultural weather, hot inertia etc, Achievement of quantitative and accurate land surface promotes the process of prediction of drought disaster、study of crops,estimation on crop output, numerical weather forecast, global climatic change and global carbon balance. So it es one of important tasks in quantitative remote sensing research to make use of satellite remote sensing to retrieve land surface temperature at present. Land surface temperature (LST) is a crucial parameter in indicting thermal energy distribution, the most efficient way to acquire it is through thermal infrared remote sensing images. Thermal infrared remote sensing is an important branch of remote sensing whereas LST retrieving is the premise of it. In this paper,with the help of RS and GIS technology,Landsat7ETM+ IR images of Zhengzhou City and Kaifeng City were employed to retrieve several parameters between land and atmosphere such as surface albedo, surface emissivity Based on these parameters and other data which mainly atmosphere data, land surface temperature were calculated to study the temporal change trend and spatial distribution characters in study area.
Key words: thermal infrared remote sensing; LS