Forest Change Characterization by means of BIOMASS Pol-InSAR Measurements

Kurzfassung

Polarimetric SAR Interferometry (Pol-InSAR) [1] techniques have proven highly effective for reconstructing various forest structure parameters, such as tree height and stand density. This capability has been demonstrated across different frequency ranges, including data at high- (e.g., X-band [2]) and lower-frequency bands (e.g., L-band [3]). However, despite these initial attempts, a qualitative and quantitative assessment of forest change by means of Pol-InSAR is still missing. The main challenge remains in solving the ambiguities arising from the superposition of both structural and dielectric changes as well as characterizing the different change signatures. At the same time, ESA’s BIOMASS mission is the first spaceborne mission that will provide systematic Pol-InSAR measurements over the majority of the forested areas worldwide. The rather limited spatial resolution of BIOMASS is counterbalanced by the penetration capability at P-band when combined with multi-baseline Pol-InSAR acquisitions. In this context, this contribution introduces a framework for analyzing forest change using Pol-InSAR measurements at P-band. The approach starts with the decomposition of the forest canopy response into ground and volume components by following a two-layer model interpretation [4]. Then, a polarimetric analysis is performed over these individual, simplified, separated components. Different to previous works, which primarily focus on evaluating the polarization states associated with the maximum and minimum change [5], this analysis extends to encompass the full set of possible polarization states. The proposed methodology is applied and validated over tropical forest sites located in Gabon. Airborne campaign data acquired by the DLR’s F-SAR sensor from two campaigns, AfriSAR performed in 2016 and GabonX performed in 2023, are employed. Together with reference lidar data for validation, these datasets offer one of the first opportunities to analyze changes over a tropical forest scenario exploiting P-band data. The polarimetric analysis of the separated ground and volume components that form the forest canopy reveals two important insights. First, evaluating the individual components yields more detailed information of the forest structure compared to observing the full polarimetric signature. At P-band, the ground component, which is strongly polarized, dominates the SAR signal. In contrast, the volume component is relatively weak, homogeneous, and stable. Second, the analysis across the full range of polarization states over the normalized ground and volume components enables the identification of the dominant scattering mechanism. This finding suggests that dielectric changes (i.e., changes only in backscattered intensity) can be distinguished from structural changes. Furthermore, variations in the dominant scattering mechanisms, particularly those associated with the ground response, can potentially be linked to different types of structural changes, such as logging versus growth scenarios. The work presented in this contribution is part of the ongoing activities within the BioTomEx ESA Study, and it will be further developed and consolidated as part of the products provided by the upcoming ESA BIOMASS mission. [1] K. P. Papathanassiou and S. R. Cloude, “Single-baseline polarimetric SAR interferometry,” in IEEE Transactions on Geoscience and Remote Sensing, vol. 39, no. 11, pp. 2352-2363, Nov. 2001, DOI: 10.1109/36.964971. [2] 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. [3] 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, DOI: 10.1109/JSTARS.2018.2859050. [4] S. R. Cloude and K. P. Papathanassiou, “Three-stage inversion process for polarimetric SAR interferometry”, in IEE Proceedings-Radar, Sonar and Navigation, vol. 150, no. 3, pp. 125-134, June 2003, DOI: 10.1049/ip-rsn:20030449. [5] A. Alonso-González, C. López-Martínez, K. P. Papathanassiou and I. Hajnsek, “Polarimetric SAR Time Series Change Analysis Over Agricultural Areas,” in IEEE Transactions on Geoscience and Remote Sensing, vol. 58, no. 10, pp. 7317-7330, Oct. 2020, DOI: 10.1109/TGRS.2020.2981929.