Forest structure observation using interferometric and tomographic synthetic aperture radar measurements: Current understanding and open questions

Kurzfassung

Nowadays two remote sensing techniques allow the realization of 3D forest structure measurements over large areas overcoming spatial and temporal limitations of field inventory plots and terrestrial laser scanning: Lidar (in full-waveform and high-density discrete-return airborne or spaceborne configurations) and Synthetic Aperture Radar (SAR). In particular, for SAR configurations, (Polarimetric) SAR Interferometry ((Pol-)InSAR) [1] and SAR Tomography (TomoSAR) [2] are two techniques that can extract 3D structure information related not only to height, but also to structure intended as the 3D size, location and arrangements of trees, trunks and branches. (Pol-)InSAR has been demonstrated in several experiments for the estimation of forest height and horizontal structure parameters associated e.g. to stand density index especially for high-frequency data [3]. TomoSAR is an imaging technique that reconstructs the full 3D distribution of the radar reflectivity. Despite the lack of a clear physical interpretation of the reconstructed reflectivity and its (ambiguous) dependency on the electromagnetic properties of the forest elements, a framework for qualitative and quantitative forest structure characterization from (low frequency) tomographic SAR measurements has been proposed recently in [4]-[5] in correspondence of structure indices already established in forestry and ecology studies. In this context, the availability of Pol-InSAR and TomoSAR measurements within the BIOMASS mission is a unique opportunity for a low-frequency, spatially continuous, 3D structure characterization at a global scale by exploiting a fully resolved information along the height dimension. Supported by experimental results from dedicated airborne campaigns and spaceborne acquisitions, this presentation critically reviews and discusses the current understanding and the open questions in (Pol-)InSAR / TomoSAR structure characterization in terms of the ecological significance of the defined indices, their sensitivity to different ecological structure types and gradients as a function of the implemented resolutions, and the robustness to reflectivity variations not relevant to structure (e.g. induced by spatial changes of the dielectric properties of the forest volume caused by rain or temperature gradients). Potentials for characterizing structure changes in time are addressed as well. [1] K. Papathanassiou, S. Cloude, “Single-baseline polarimetric SAR interferometry,” IEEE Transactions on Geoscience and Remote Sensing, vol. 39, no. 11, pp. 2352-2363, Nov. 2001. [2] A. Reigber and A. Moreira, "First demonstration of airborne SAR tomography using multibaseline L-band data," IEEE Transactions on Geoscience and Remote Sensing, vol. 38, no. 5, pp. 2142-2152, Sept. 2000 [3] C. Choi, M. Pardini, M. Heym and K. P. Papathanassiou, "Improving Forest Height-To-Biomass Allometry With Structure Information: A Tandem-X Study," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 14, pp. 10415-10427, 2021. [4] M. Tello, V. Cazcarra-Bes, M. Pardini and K. Papathanassiou, “Forest Structure Characterization From SAR Tomography at L-Band,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 11, no. 10, pp. 3402-3414, Oct. 2018. [5] M. Pardini, M. Tello, V. Cazcarra-Bes, K. P. Papathanassiou and I. Hajnsek, “L- and P-Band 3-D SAR Reflectivity Profiles Versus Lidar Waveforms: The AfriSAR Case,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 11, no. 10, pp. 3386-3401, Oct. 2018.