Speaker
Description
Understanding forest structural dynamics is crucial for accurate forest biomass estimation, ecosystem monitoring, and carbon cycle modelling. The launch of the European Space Agency’s (ESA) BIOMASS mission on April 29, 2025, opened a new era as the first spaceborne P-band synthetic aperture radar (SAR) continuously operating in quad-polarimetric, multi-baseline interferometric, and tomographic modes [1]. Thanks to its long wavelength (~70 cm), P-band SAR can penetrate dense forest canopies and reach the ground, resulting in complex scattering interactions. However, the physical interpretation of such P-band images, even in the context of polarimetric SAR time series, remains challenging due to the complexity of the scattering interaction that lifts the scattering entropy [2, 3, 4]. To resolve this the combination of polarimetric and interferometric (Pol-InSAR) information, sensitive to the vertical distribution of the scatters, can be exploited to decompose the total radar return into its round and volume components [5, 6].
In this contribution, we exploit 3-day repeat-pass Pol-InSAR BIOMASS acquisitions to isolate and interpret the polarimetric signature of the ground scattering component. The rapid environmental and weather changes (e.g., water level fluctuations and rain events) visible in the BIOMASS data induce complex temporal decorrelation patterns that vary spatially across consecutive 3-day interferograms making conventional multi-baseline ground-volume separation techniques suboptimum [7]. To overcome this, a single-baseline, model-based approach based on the Random Volume over Ground (RVoG) formulation [8] is employed, tailored to the BIOMASS revisit cycle. Following the ground and volume separation, the recovered ground scattering matrix is decomposed into direct surface and ground-trunk dihedral interaction components. The relative weight between these signatures yields direct physical insight into horizontal (ground) and vertical (canopy) forest structure.
The proposed methodology was validated during the BIOMASS In Orbit Commissioning phase over vegetated coastal and riverine ecosystems, such as the Congo River Delta. In these environments, conventional PolSAR images failed to reflect rapid hydrological dynamics, and interferometric coherence maps alone presented ambiguous interpretations. By isolating the ground signature, the recovered polarimetric change mechanisms successfully disentangled and explained the underlying decorrelation patterns, explicitly recovering tide-induced scattering dynamics beneath dense mangrove and forest canopies [9]. Building on these results, a first large scale analysis is performed and presented, including country wide tropical forest regions, such as Gabon and the Amazonian forest. The structural signature of different forest types and disturbance regimes is analysed and discussed.
REFERENCES
[1] K. Scipal et al., “BIOMASS: ESA’s P-Band SAR Mission,” in Proceedings of the IEEE, doi: 10.1109/JPROC.2026.3687416.
[2] S. R. Cloude and E. Pottier, “An entropy based classification scheme for land applications of polarimetric SAR,” IEEE Trans. Geosci. Remote Sens., vol. 35, no. 1, pp. 68–78, Jan. 1997.
[3] S. Cloude, “A Physical Approach to POLSAR Time Series Change Analysis,” IEEE Geosci. Remote Sens. Lett., vol. 19, pp. 1–4, 2022.
[4] A. Alonso-González, C. López-Martínez, K. P. Papathanassiou, and I. Hajnsek, “Polarimetric SAR Time Series Change Analysis Over Agricultural Areas,” IEEE Trans. Geosci. Remote Sens., vol. 58, no. 10, pp. 7317–7330, Oct. 2020.
[5] K. P. Papathanassiou and S. R. Cloude, “Single-baseline polarimetric SAR interferometry,” IEEE Trans. Geosci. Remote Sens., vol. 39, no. 11, pp. 2352–2363, Nov. 2001.
[6] A. Alonso-Gonzalez and K. P. Papathanassiou, “Multibaseline Two Layer Model PolInSAR Ground and Volume Separation,” in Proc. EUSAR 2018, Jun. 2018.
[7] S. Tebaldini, “Single and Multipolarimetric SAR Tomography of Forested Areas: A Parametric Approach,” IEEE Trans. Geosci. Remote Sensing, vol. 48, no. 5, pp. 2375-2387, May 2010.
[8] A. Alonso-González, N. Romero-Puig, C. López-Martínez and K. P. Papathanassiou, “Polarimetric Ground and Volume Decomposition Based on the PolInSAR Two-Layer Model,” in IEEE Trans. Geosci. Remote Sensing, vol. 64, pp. 5209914-5209914, 2026
[9] N. Romero-Puig, M. Pardini, R. Guliaev and K. P. Papathanassiou, “Initial P-band BIOMASS Pol-InSAR Observations for Forest Structure Mapping,” in Proc. EUSAR 2026, Jun. 2026.