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以各频段水平极化和垂直极化发射率间的相关关系为条件,利用被动微波数据反演地表温度.算法既解决了地表温度反演过程中发射率难以确定的问题,又克服了热红外遥感受大气影响较大的缺点,其物理意义清晰,计算简便.算法以MODIS温度产品为评价标准,对36.5 GHz和89 GHz反演结果进行分析.结果表明:89 GHz亮温数据反演精度高于36.5 GHz;与耕地和草场反演精度相比,裸土和山地反演精度较高.其原因在于高频数据穿透能力较低,能更好地表达地表温度.同时,低频数据相对高频更容易受到地表土壤水分变化的影响,发射率相对不够稳定,对反演结果有一定影响.
Based on the correlation between horizontal polarization and vertical polarization emissivity in each frequency band, the surface temperature is retrieved using passive microwave data.The algorithm not only solves the problem of difficult to determine the emissivity in the process of surface temperature inversion, but also overcomes the problems of thermal infrared The sensitivities of remote sensing to the atmosphere are clear, and its physical meaning is clear and the calculation is simple.The algorithm analyzes the inversion results of 36.5 GHz and 89 GHz based on MODIS temperature products.The results show that the precision of 89 GHz bright temperature data retrieval is high At 36.5 GHz, compared with the inversion accuracy of arable land and pasture, the precision of bare soil and mountain inversion is higher because of the lower penetrability of high-frequency data and the better expression of surface temperature. Meanwhile, the low frequency data is relatively high Frequency is more likely to be affected by the change of surface soil moisture, the emissivity is relatively not stable enough, and the inversion result will be affected to some extent.