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首页> 外文期刊>IEEE Transactions on Geoscience and Remote Sensing. >Snowpack Density Retrieval Using Fully Polarimetric TerraSAR-X Data in the Himalayas
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Snowpack Density Retrieval Using Fully Polarimetric TerraSAR-X Data in the Himalayas

机译:在喜马拉雅山中使用全极化TerraSAR-X数据进行积雪密度反演

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This paper focuses on the development of a novel algorithm for deriving snowpack density over the snow-covered region of the Himalayas. The analysis utilizes fully polarimetric TerraSAR-X synthetic aperture radar data sets, field observations, and other ancillary information for the retrieval of snowpack density. The algorithm involves the development of a new generalized hybrid decomposition model. The generalized volume scattering parameter from the decomposition model is inverted for snow density estimation. A few field data measurements' campaigns were carried out, within near-real time of satellite passing over the area, to collect various parameters such as temperature, water content, and the density of the snowpack at varying depths. These field observations are further used for validation of the results obtained from the inversion algorithm. It is also found that the model-estimated snowpack density is highly congruent with the field-measured snowpack density. The mean absolute error of snowpack density, root-mean-square error, and index of agreement are found to be 9.9 kg/m3, 10 kg/m3, and 0.96, respectively, which are well within the acceptable range.
机译:本文重点研究一种新算法的开发,该算法可用于推算喜马拉雅山大雪覆盖地区的积雪密度。该分析利用全极化TerraSAR-X合成孔径雷达数据集,野外观测以及其他辅助信息来获取积雪密度。该算法涉及新的广义混合分解模型的开发。将来自分解模型的广义体积散射参数进行反演以进行雪密度估计。在近乎实时的卫星通过该区域的过程中,进行了一些现场数据测量活动,以收集各种参数,例如温度,水含量以及不同深度的积雪密度。这些现场观察结果进一步用于验证从反演算法获得的结果。还发现模型估计的积雪密度与现场测量的积雪密度高度一致。积雪密度的平均绝对误差,均方根误差和一致性指数为9.9 kg / m 3 ,10 kg / m 3 和0.96,分别在可接受范围内。

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