Soil Moisture Estimation Using Differential Radar Interferometry: Toward Separating Soil Moisture and Displacements

Differential interferometric synthetic aperture radar (DInSAR) measurements are sensitive to displacements, but also to soil moisture m
_ν
changes. Here, we analyze whether soil moisture can be estimated from three DInSAR observables without making any assumptions about its complex spatio-temporal dynamics, with the goal of removing its contribution from the displacement estimates. We find that the referenced DInSAR phase can be a suitable means to estimate m
_ν
time series up to an overall offset, as indicated by correlations with in situ measurements of 0.75-0.90 in two campaigns. However, the phase can only be referenced when no displacements (and atmospheric delays) occur or when they can be estimated reliably. We study the separability of displacements and m
_ν
using two additional DInSAR observables (closure phase and coherence magnitude) that are sensitive to m
_ν
but insensitive to displacements. However, our analyses show that neither contains enough information for this purpose, i.e., it is not possible to estimate m
_ν
uniquely. The soil moisture correction of the displacement estimates is hence ambiguous too. Their applicability is furthermore limited by their proneness to model misspecifications and decorrelation. Consequently, the separation of soil moisture changes and displacements using DInSAR observations alone is difficult in practice, and-like for mitigating tropospheric errors-additional data (e.g., external m
_ν
estimates) or assumptions (e.g., spatiotemporal patterns) are required when the m
_ν
effects on the displacement estimates are comparable to the magnitude of the movements. This will be critical when soil moisture changes are correlated with the actual displacements.