Conference Agenda

The potential of combining polarimetric interferometric (Pol-InSAR) / tomographic (TomoSAR) SAR measurements at multiple frequencies and lidar measurements towards an improved and / or more complete 3D forest structure characterization is widely recognized. Lower frequencies are more sensitive to larger (i.e. on the order of the wavelength) vegetation elements. At the same time, the reduced attenuation of the canopy increases the “visibility” of lower vegetation layers and of the ground. In contrast, with increasing frequency the sensitivity to smaller vegetation elements increases while the stronger canopy attenuation reduces the “visibility” of the ground. This complementarity of structural information content has recently become especially relevant in a context in which lidar missions like NASA’s GEDI and IceSAT-2, and SAR missions like e.g. ESA P-band BIOMASS, NASA L-band NISAR, ESA L-band ROSE-L, DLR X-band TanDEM-X are already / will be operating at the same or contiguously in time with a number of common forest structure-related objectives, but with different spatial and temporal resolutions and coverages. The development of suitable approaches able to combine multi-frequency Pol-InSAR / TomoSAR and lidar measurements critically depends on the ability to relate the underlying 3D reflectivities to each other. This is in general not established today essentially because there are no electromagnetic models that allow neither to model nor to transfer reflectivity with the required accuracy across a relevant frequency range [1].

In the absence of any model-supported way to transfer reflectivity profiles from one frequency to the other, data-driven approximations remain an appealing (and maybe the only) option. In this context, this work investigates how far polarization coherence tomography (PCT) can support this transfer. To begin with, the investigation is currently focused on the reconstruction of lidar profiles from P-band interferometric measurements (e.g. a BIOMASS-GEDI case) and vice-versa, i.e. on the reconstruction of P-band profiles from lidar ones. PCT formulates the reconstruction of vertical reflectivity profiles as a series expansion in a function basis with coefficients estimated from a limited set of Pol-InSAR measurements [2]. In the presented analysis, function bases are derived from reflectivity profiles available for each data set first [3]. Then, the basis of one data set is used to reconstruct profiles at the other from the available measurements (Pol-InSAR at P-band, full-waveforms for lidar). Finally, the ability to reconstruct specific profile parameters (e.g. the height of and the reflectivity at the canopy local maximum) is evaluated especially as a function of the number of the used basis components. Results obtained by processing real data acquired in the frame of the ESA-supported AfriSAR 2016 campaign over the forest in Mondah in Gabon are shown. During the campaign DLR’s F-SAR and NASA LVIS airborne platforms acquired P-band TomoSAR (multibaseline interferometric) and lidar waveforms, respectively, almost at the same time.

References

[1] M. Pardini, J. Armston, W Qi, S. K. Lee, M. Tello, V. Cazcarra Bes, C. Choi, K. Papathanassiou, R. O. Dubayah, L.E. Fatoyinbo, “Early Lessons on Combining Lidar and Multi-Baseline SAR Measurements for Forest Structure Characterization,” Surveys in Geophysics, vol. 40, pp. 803–837, 2019.

[2] S. R. Cloude, "Polarization coherence tomography," Radio Science, vol. 41, no. 04, pp. 1-27, Aug. 2006.

[3] R. Guliaev, M. Pardini, K. Papathanassiou, “Forest 3D Radar Reflectivity Reconstruction at X-Band Using a Lidar Derived Polarimetric Coherence Tomography Basis,” Remote Sensing, vol. 16, 2146, 2024.