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Remote Sens. 2015, 7(6), 7571-7596; doi:10.3390/rs70607571

A Polarimetric First-Order Model of Soil Moisture Effects on the DInSAR Coherence

1
Institute of Environmental Engineering, ETH Zurich, Stefano-Franscini-Platz 3, 8093 Zurich, Switzerland
2
Jet Propulsion Laboratory, 4800 Oak Grove Drive, Pasadena, CA 91109, USA
3
Microwaves and Radar Institute, German Aerospace Center (DLR), P.O. Box 1116, 82230 Wessling, Germany
*
Author to whom correspondence should be addressed.
Academic Editors: Nicolas Baghdadi and Prasad S. Thenkabail
Received: 16 March 2015 / Revised: 28 May 2015 / Accepted: 29 May 2015 / Published: 8 June 2015
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Abstract

Changes in soil moisture between two radar acquisitions can impact the observed coherence in differential interferometry: both coherence magnitude |Υ| and phase Φ are affected. The influence on the latter potentially biases the estimation of deformations. These effects have been found to be variable in magnitude and sign, as well as dependent on polarization, as opposed to predictions by existing models. Such diversity can be explained when the soil is modelled as a half-space with spatially varying dielectric properties and a rough interface. The first-order perturbative solution achieves–upon calibration with airborne L band data–median correlations ρ at HH polarization of 0.77 for the phase Φ, of 0.50 for |Υ|, and for the phase triplets ≡ of 0.56. The predictions are sensitive to the choice of dielectric mixing model, in particular the absorptive properties; the differences between the mixing models are found to be partially compensatable by varying the relative importance of surface and volume scattering. However, for half of the agricultural fields the Hallikainen mixing model cannot reproduce the observed sensitivities of the phase to soil moisture. In addition, the first-order expansion does not predict any impact on the HV coherence, which is however empirically found to display similar sensitivities to soil moisture as the co-pol channels HH and VV. These results indicate that the first-order solution, while not able to reproduce all observed phenomena, can capture some of the more salient patterns of the effect of soil moisture changes on the HH and VV DInSAR signals. Hence it may prove useful in separating the deformations from the moisture signals, thus yielding improved displacement estimates or new ways for inferring soil moisture. View Full-Text
Keywords: DInSAR; InSAR; interferometry; electromagnetic model; soil moisture; deformations; displacement DInSAR; InSAR; interferometry; electromagnetic model; soil moisture; deformations; displacement
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Zwieback, S.; Hensley, S.; Hajnsek, I. A Polarimetric First-Order Model of Soil Moisture Effects on the DInSAR Coherence. Remote Sens. 2015, 7, 7571-7596.

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