Speaker
Description
Polarimetric SAR Interferometry (PolInSAR) merges polarimetric SAR, offering the ability to distinguish between different scattering types within individual resolution cells, and interferometric SAR, which provides sensitivity to the vertical distribution of scatterers.
The PolInSAR two-layer model represents the signal as a combination of ground and volume contributions and has proven especially useful for modelling the signal over vegetation. Because these two components have different polarimetric and interferometric characteristics, physical parameters such as the ground phase or forest height can be extracted [1]. More recently, the model has also been used to separate and extract fully polarimetric signatures of the ground and volume as a polarimetric decomposition [2].
When several baselines are available, the vertical reflectivity profile of the vegetation can be estimated, which is equivalent to forming a synthetic aperture in the across-track dimension as in SAR tomography, converting the problem into a spectral estimation. Under the two-layer model, the vertical reflectivity of the ground and volume define their interferometric coherences, linking the polarimetric and interferometric dimensions of the data [3]. In this work we exploit the spatial variability of the volume-layer height across the image to estimate the volume reflectivity profile from a single baseline, assuming the volume profile of spatially close stands equals the same normalized profile scaled in height. The ground and volume components, together with the coherences modelled from the inverted profile, are then combined through the two-layer forward model to synthesize the full multipolarization multibaseline (MPMB) covariance matrix for an arbitrary baseline distribution. Classical tomography applied to this modelled stack then yields per-pixel tomograms.
The technique was first evaluated with airborne F-SAR data from DLR over the AfriSAR campaign at P-band. In this contribution we extend the validation to real spaceborne ESA BIOMASS data. Although a quantitative assessment against external reference profiles remains future work, the retrieved profiles reproduce known structural contrasts within the imaged area: deforestation scars are clearly separated from intact forest, and denser stands appear both taller and more polarimetrically diverse. These results demonstrate the feasibility of single-baseline tomographic reconstruction under the operational constraints of the BIOMASS interferometric phase, supporting the monitoring of forest vertical structure and its temporal evolution.
References
[1] S. Cloude and K. Papathanassiou, “Three-stage inversion process for polarimetric SAR interferometry,” IEE Proceedings-Radar, Sonar and Navigation, vol. 150, no. 3, pp. 125–134, 2003.
[2] A. Alonso-Gonzalez and K. P. Papathanassiou, “Multibaseline two layer model polinsar ground and volume separation,” in EUSAR 2018; 12th European Conference on Synthetic Aperture Radar, 2018, pp. 1–5.
[3] 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 Transactions on Geoscience and Remote Sensing, vol. 64, pp. 5209914-5209914, 2026.