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Physics-Based Modeling of Active and Passive Microwave Covariations Over Vegetated Surfaces

机译:基于物理学的植被表面主动和被动微波协变建模

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Active and passive low-frequency microwave measurements from a number of space- and airborne instruments are used to estimate soil moisture. Each of the sensing approaches has distinct advantages and disadvantages. There is increasing interest in combining active and passive measurements in order to realize the advantages and alleviate the disadvantages. In order to combine active and passive measurements, their covariations with respect to soil moisture need to be known. The covariation is dependent on how the active and passive microwaves interact with vegetation canopy and soil surface. In this paper, we introduce a physics-based model for the covariation of active and passive microwaves over soil surfaces with vegetation cover. The analytical form for a covariation function is derived which depends on the scattering and absorption of microwaves by soil and vegetation with different orientations, structures, and water contents. The main finding is that the covariation function beta is related to the roughness and vegetation losses in the two measurements. An increase in soil roughness or in vegetation cover leads to less negative values of beta, which is pronounced for dense and moist vegetation. Both the soil and vegetation components introduce a polarization dependence of beta that is caused by polarization-induced differences in soil scattering and oriented plant structures. The forward modeled covariations are plotted together with statistically derived covariation estimates from two months of global active and passive L-band observations of the Soil Moisture Active Passive mission. The physically modeled and statistically derived estimates of covariation are comparable in magnitude and scale.
机译:来自许多空间和机载仪器的主动和被动低频微波测量被用于估计土壤湿度。每种感测方法都有各自的优点和缺点。为了实现优点和减轻缺点,越来越有兴趣将主动和被动测量相结合。为了结合主动和被动测量,需要知道它们相对于土壤水分的协变。协变取决于主动和被动微波如何与植被冠层和土壤表面相互作用。在本文中,我们介绍了一种基于物理学的模型,用于植被覆盖的土壤表面上有源微波和无源微波的协变。推导了协变函数的解析形式,该形式取决于不同方向,结构和水含量的土壤和植被对微波的散射和吸收。主要发现是,协变量函数β与两次测量中的粗糙度和植被损失有关。土壤粗糙度或植被覆盖度的增加会导致β的负值减少,这对于茂密潮湿的植被尤为明显。土壤和植被成分都引入β的极化依赖性,这是由极化引起的土壤散射和定向植物结构差异引起的。将前向建模的协变量与从土壤水分主动被动任务的两个月的全球主动和被动L波段观测值的统计得出的协变量估计值一起绘制。在物理模型上和统计上得出的协方差估算在大小和规模上都是可比的。

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