Limits of Soil Moisture Retrieval at L-Band over Bare and Vegetated Fields using Airborne Polarimetric D-InSAR

Abstract

Observing changes in soil moisture with differential Synthetic Aperture Radar (SAR) interferometry (D-InSAR) has gained relevance due to shorter satellite revisit times, bigger swath widths, higher spatial resolution of SAR systems, and the introduction of L-band satellites. The geometric configuration of D-InSAR mitigates topographic effects, baseline-induced distortions, and geometric decorrelation.

In this context, the separation of volume, surface and dihedral scattering in the SAR signal is essential for limiting uncertainty in the accurate estimation of soil moisture. Using D-InSAR recent soil moisture forward models are able to account for varying soil states and surface and subsurface volume scattering combinations, although they assume the absence of topographical variations and vegetation between acquisitions [1], [2]. Whereas former can be approximately removed by using phase triplets, separating above ground volume from surface scattering remains a challenge. To address this, polarimetric information has been shown to be sensitive to vegetation [3].

To enhance soil moisture estimation we combine existing D-InSAR electromagnetic forward models with polarimetric information. Here, the copolar phase differences (CPD) [4] can been used to counteract the need of auxiliary geometries and fully-polarimetric systems. CPD has been shown to be highly sensitive to volume scattering due to the structural anisotropy of vegetation.

This analysis will focus on quantifying the performance of Zwieback et al. [2] at L-Band and HH/VV polarizations by deploying it on the recent AgriROSE-L dataset [5]. The limits of the model will be explored in respect to its parameterization, the degree of vegetation and numerous soil moisture levels. First, we test the model performance over bare ground. Secondly, we analyze the value of CPD for identifying vegetated and non-vegetated pixels. Third, we provide a first approach of integrating a CPD indicator into current soil moisture forward models.

References

[1] F. De Zan, A. Parizzi, P. Prats-Iraola, and P. López-Dekker, “A SAR interferometric model for soil moisture,” IEEE Transactions on Geoscience and Remote Sensing, 2013.

[2] S. Zwieback, S. Hensley, and I. Hajnsek, “A polarimetric first-order model of soil moisture effects on the DInSAR coherence,” Remote Sensing, vol. 7, no. 6, pp. 7571–7596, 2015.

[3] G. Anconitano, M. Lavalle, M. A. Acuña, and N. Pierdicca, “Sensitivity of polarimetric SAR decompositions to soil moisture and vegetation over three agricultural sites across a latitudinal gradient,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 17, pp. 3615–3634, 2023.

[4] V. Brancato and I. Hajnsek, “Analyzing the influence of wet biomass changes in polarimetric differential SAR interferometry at L-band,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 11, no. 5, pp. 1494–1508, 2018.

[5] H. I. Schauer, N. Basargin, and I. Hajnsek, “Airborne L-Band soil moisture retrieval over agricultural areas in preparation for ESA ROSE-L mission,” 2025.