Sensitivity of Aquarius active and passive measurements temporal covariability to land surface characteristics
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Rights accessOpen Access
Active and passive microwave observations over land are affected by surface characteristics in different ways. L-band radar backscatter and radiometer measurements each have distinct advantages and problematic issues when applied to surface soil moisture estimation. Spaceborne radiometry has the advantage of better sensitivity to the geophysical parameter but suffers from coarse spatial resolution given limitations on antenna dimensions. Active sensing has the advantage of higher spatial resolution, but the measurements are, relative to radiometry, more affected by the confounding influences of scattering by vegetation and rough surfaces. Active and passive measurements can potentially span different scales and allow the combining of the relative advantages of the two sensing approaches. This strategy is being implemented in the NASA Soil Moisture Active Passive (SMAP) mission, which relies on the relationship between active and passive measurements to provide 9-km surface soil moisture estimates. The aim of this paper is to study the sensitivity of spaceborne L-band active and passive temporal covariations to land surface characteristics, in preparation for SMAP. A significant linear relationship (with slope ß) is obtained between NASA's Aquarius scatterometer and radiometer observations across major global biomes. The error in ß estimation is found to increase with land cover heterogeneity and to be unaffected by vegetation density (up to moderate densities). Results show that ß estimated with two to eight months of Aquarius measurements (depending on vegetation seasonality) reflect local vegetation cover conditions under surfaces with complex mixture of vegetation, surface roughness, and dielectric constant.
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CitationPiles, M., McColl, K.A., Entekhabi, D., Das, N., Pablos, M. Sensitivity of Aquarius active and passive measurements temporal covariability to land surface characteristics. "IEEE transactions on geoscience and remote sensing", 16 Març 2015, vol. 53, núm. 8, p. 4700-4711.