首页 >  2006, Vol. 10, Issue (4) : 600-607

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引用本文:

DOI:

10.11834/jrs.20060488

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修改日期:

2005-10-25

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中国陆地区域陆表温度业务化遥感反演算法及产品运行系统
摘要:

地表温度反演的裂窗算法已成功应用于NOAA系列卫星热红外遥感数据。目前,裂窗算法中应用较为广泛的一种是Becker等人于1990年提出的局地裂窗算法,主要是通过辐射传输模型模拟不同地表条件和大气状况下,地表温度和发射率对红外辐射亮温的影响,从而发展出一个利用AVHRR4,5通道亮温数据反演地表温度的线性模型。在晴空无云和地表比辐射率能精确估算的情况下,Becker算法反演地表温度的精度在1K以内。Becker算法用Lowtran程序模拟计算地表辐射量,且模型中参数主要针对NOAA-9传感器特性得到。本文在Becker算法的基础上,针对NOAA-16/17传感器热红外通道光谱响应函数特性,利用最新的、计算光谱分辨率更高的MODTRAN程序模拟不同大气状况下,不同地表温度和发射率对NOAAAVHRR4,5通道辐射亮温响应特性的影响,改进Becker算法中模型参数,使之能适用于NOAA-16/17热红外数据。同时,本文利用植被指数NDVI,在中国陆地区域lkm分辨率最新地表分类数据的基础上,得到模型中需要的地表比辐射率参数,将改进的模型应用于1km分辨率NOAA17数据,得到了旬合成中国陆地区域范围地表温度,通过地面气象台站实测数据对比验证.取得了较好的结果。

A Modified Land Surface Temperature Split Window Retrieval Algorithm and Its Applications Over China
Abstract:

Due to the difficulties in correcting the influences of the atmosphere absorbability and the Earth surface emissivity diversification,the retrieval of LST(land surface temperature) from satellite data is a challenging task.In this paper,a modified Becker's split window LST inversion algorithm is developed for retrieving LST from the NOAA-16/17 AVHRR data.A new set of parameters for Becker's LST algorithm is proposed.The algorithm is developed from a surface brightness temperature dataset generated from the MODTRAN program,which uses a range of surface parameters and atmospheric quantities as inputs.The 10-day composites of the Channel 4 and 5 brightness temperature data of NOAA-17 AVHRR(1km resolution) are used to generate the clear-sky LST.As a validation of the algorithm,the retrieved LST is compared with MODIS LST of the same period and area.The two LST products are found to be consistent,with the absolute difference being about 2.5K for most areas.The NOAA retrieved LST is also compared with in-situ ground surface 0 cm measurements taken from 257 meteorological stations which cover overall China area for the three periods of satellite observations.The comparison shows that the correlation between the retrieved LST and in-situ measurements is over 0.90 and the RMSE(Root Mean Square Error) is about 3.4K.[WTHZ]

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