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Jagdhuber, Thomas; Konings, Alexandra G.; McColl, Kaighin A.; Alemohammad, Seyed Hamed; Das, Narendra Narayan; Montzka, Carsten; Link, Moritz; Akbar, Ruzbeh und Entekhabi, Dara (2019): Physics-Based Modeling of Active and Passive Microwave Covariations Over Vegetated Surfaces. In: IEEE Transactions on Geoscience and Remote Sensing, Bd. 57, Nr. 2: S. 788-802

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Abstract

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.

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