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首页> 外文期刊>Geoscience and Remote Sensing, IEEE Transactions on >Volume Scattering Modeling in PolSAR Decompositions: Study of ALOS PALSAR Data Over Boreal Forest
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Volume Scattering Modeling in PolSAR Decompositions: Study of ALOS PALSAR Data Over Boreal Forest

机译:PolSAR分解中的体积散射建模:北方森林ALOS PALSAR数据的研究

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摘要

Model-based approaches for decomposing polarimetric backscatter data from boreal forest are discussed in this paper. Several model-based decompositions are analyzed with respect for the most accurate estimation of the volume scattering component. A novel generalized model for description of the volume contribution is proposed when observed backscatter from forest indicates that media does not follow azimuthal symmetry case. The model can be adjusted to the polarimetric synthetic aperture radar (PolSAR) data itself, taking into consideration higher sensitivity of HH against VV backscattering term to the presence of canopy at L-band. The model is general enough to allow a broad range of canopies to be modeled and is shown to comply with several earlier proposed volume scattering mechanism models. It is afterward incorporated in the Freeman–Durden three-component decomposition, yielding an improved modification. The performance of the proposed modification is evaluated using multitemporal ALOS PALSAR data acquired over Kuortane area in central Finland, representing typical mixed boreal forestland. Several decompositions are also benchmarked in order to see how they satisfy physical requirements when decomposing covariance matrix into a weighted sum of individual scattering mechanism contributions. When using experimental data, the proposed decomposition is shown to better satisfy non-negativity constraints for the covariance matrix eigenvalues at each decomposition step with less additional PolSAR data averaging needed. Discussed decompositions are also evaluated for the accuracy of initial stratification based on dominating scattering mechanism using ground reference data.
机译:本文讨论了基于模型的分解北极森林反向偏振散射数据的方法。关于体积散射分量的最准确估计,分析了几种基于模型的分解。当从森林中观察到的反向散射表明介质不遵循方位角对称的情况时,提出了一种描述体积贡献的新型广义模型。考虑到HH对VV反向散射项对L波段冠层存在的更高灵敏度,可以将该模型调整为极化合成孔径雷达(PolSAR)数据本身。该模型具有足够的通用性,可以对大范围的树冠进行建模,并显示出符合几个较早提出的体积散射机制模型。之后将其合并到Freeman-Durden三组分分解中,从而产生改进的修饰。使用在芬兰中部代表典型的混交林地的库尔塔恩地区采集的多时相ALOS PALSAR数据评估了拟议修改的性能。还对一些分解进行了基准测试,以了解它们在将协方差矩阵分解为各个散射机制贡献的加权总和时如何满足物理要求。当使用实验数据时,建议的分解显示出可以更好地满足每个分解步骤中协方差矩阵特征值的非负约束,而所需的平均PolSAR数据较少。还使用地面参考数据,基于支配散射机制,评估了讨论的分解过程的初始分层准确性。

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