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Verification of Downscaling Method for Near-Surface Freeze/Thaw State Monitoring in Genhe Area of China

机译:中国根河地区近地表冻融状态监测降尺度方法的验证

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The high-resolution freeze/thaw (F/T) monitoring plays an important role in studying carbon-nitrogen cycle, soil erosion and climate change in Genhe, China. In this paper, high-resolution downscaled land surface temperature (LST) retrieved from AMSR2 [1] were obtained from previous study [1]. And then were used to downscale the passive microwave (PMW) brightness temperature (TB) from 0.25° to 0.01° through downscaling method of PMW TB [2]. Finally, the downscaled TB data and F/T discriminant function algorithms [3], [4] were adopted to discriminate the surface freeze/thaw status. A comparison between high-resolution F/T state and soil temperature measured at 0~5 cm over Genhe area turned out that the F/T discriminant function algorithm [3] has a total classification accuracy higher than and 70%, and the improved F/T discriminant function algorithm [4] has a total classification accuracy higher than and 60%. From the perspective of orbit, both algorithms had freezing distinguished accuracy high than 90% at ascending and descending orbits. At last, we discussed and analyzed the possible problems of F/T discriminant function algorithms and downscaling method of TB.
机译:高分辨率的冻融(F / T)监测在研究中国根河市的碳-氮循环,土壤侵蚀和气候变化方面发挥着重要作用。本文从先前的研究[1]中获得了从AMSR2 [1]检索的高分辨率低尺度地表温度(LST)。然后通过PMW TB的缩减方法将被动微波(PMW)的亮度温度(TB)从0.25°缩减至0.01°[2]。最后,采用缩小的TB数据和F / T判别函数算法[3],[4]来判别表面冻结/融化状态。根河地区高分辨率F / T状态与土壤温度在0〜5 cm处的比较表明,F / T判别函数算法[3]的总分类准确率高于5%和70%,改进后的F / T判别函数算法[4]的总分类准确率高于60%和60%。从轨道的角度来看,两种算法在上升和下降轨道上的冻结识别精度均高于90%。最后,我们讨论并分析了F / T判别函数算法和TB降尺度方法可能存在的问题。

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