Airborne L-Band Soil Moisture Retrieval over Agricultural Areas in Preparation for ESA ROSE-L Mission

Kurzfassung

Synthetic Aperture Radar (SAR) systems are a valuable resource for soil moisture monitoring. They are sensitive to dielectrics, offer high spatial resolution, and are independent of weather. Established C-band missions such as Sentinel-1 are actively used for operational soil moisture products (1). However, vegetation strongly affects the C-band, resulting in a weak ground signal under some conditions. To address this challenge, longer L-band frequencies with deeper penetration into natural media can be used to retrieve surface soil moisture (SSM) under vegetation. At the same time, a similar performance was shown for bare and sparsely vegetated soil compared to C-band. Several L-band missions, including ROSE-L, NISAR, ALOS-4, SAOCOM-2, and LuTan-1, are operational or scheduled to launch in the next years. To better understand L-band and C-band’s performance in agriculture in preparation for the ESA ROSEL mission, a new experimental F-SAR airborne campaign is conducted over the Puch test site in southern Germany between April and July 2025. With more than 20 planned flights, the campaign provides a dense time series of fully polarimetric L- and C-band acquisitions, accompanied by in situ soil moisture and vegetation measurements. The acquisition period mostly covers the full crop cycle from bare soils to fully harvested fields and the test site comprises more than 10 crop types including maize, potato, wheat, barley, rape, rye, triticale, alfalfa, and spelt. This work provides the first analysis of the new dataset and focuses on estimating SSM using differential SAR interferometry (D-InSAR). In contrast to backscatter-based methods that mainly use the signal amplitude, D-InSAR employs the phase between several acquisitions, making it especially sensitive to changes. We employ the forward model of (2) to estimate soil moisture using coherence and phase triplets. It advances former models (3) by enabling local adjustments for surface roughness and varying contributions of surface and volume scattering. We evaluate the performance of the calibrated model for both C-band and L-band data. The investigation comprises: (i) a parameter sensitivity analysis, (ii) an in-depth inquiry of coherence magnitude, coherence phase, and closure phase, and (iii) a time series analysis over the entire period. The insights represent a foundation for further D-InSAR model development in preparation for the ROSE-L mission. References (1) T. Schmidt, M. Schrön, Z. Li, et al., ”Comprehensive quality assessment of satellite-and model-based soil moisture products against the COSMOS network in Germany” Remote Sensing of Environment, vol. 301, p. 113 930, 2024. (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) F. De Zan, A. Parizzi, P. Prats-Iraola, and P. L’opez-Dekker, ”A SAR interferometric model for soil moisture,” IEEE Transactions on Geoscience and Remote Sensing, 2013