BIOMASS  is ESA's seventh Earth Explorer, scheduled for launch in 2023. It will collect unprecedented information about forests thanks to the first spaceborne P-band Synthetic Aperture Radar (SAR), and featuring full polarimetry. The 435 MHz carrier frequency and 6 MHz bandwidth allow maximum sensitivity to the woody elements of the trees, while complying with ITU regulations and avoiding excessively strong ionospheric effects. Its acquisition cycle is designed to acquire globally (subject to Space Object Tracking Radars restricitions, excluding North America and Europe) and in a multi-baseline repeat pass interferometric configuration. The repeat cycle is set to 3 days, guaranteeing coherence for interferometric and tomographic processing.
After the initial Commissioning Phase, dedicated to instrument and antenna calibration, the experimental Tomographic Phase will achieve one global coverage in 14/16 months. This will allow mapping forests in 3 dimensions by collecting stacks of 7 acquisitions over 18 days for each location, in ascending and descending configurations. During Tomographic Phase it will be also possible to derive a sub-canopy Digital Terrain Model (DTM) . This is fundamental to reject terrain contribution in interferometric processing , as terrain acts as a nuisance and disturbs biomass retrieval. The remainder of the mission is the main Interferometric Phase of about 5 years duration, with global coverage achieved in 7/9 months. In this case stacks are collected in dual baseline configuration over 6 days. Coverage will be built up successively, with the successive tomographic or interferometric stacks adding coverage to adjacent areas. Given the complex orbital pattern achieving global coverage over several months, significant environmental changes will occur that the estimation techniques must handle.
In this contribution we describe the Level-2 processing algorithms to estimate Forest Disturbance (FD), Forest Height (FH) and Above Ground Biomass (AGB) products from BIOMASS data . The Level-2 processor requires phase calibrated stacks generated by the BIOMASS interferometric processor and the DTM estimated in the Tomographic Phase . FD, FH and AGB products are generated at each global coverage during the mission lifetime mapping not only forest characteristics but also changes. The processing implements state-of-the-art polarimetric-interferometric techniques allowing to reject terrain signal and focus on canopy scattering. This is supported by strong evidence that in tropical forests the backscatter from the canopy region 25-35m above the ground is highly correlated with the total AGB, which can be exploited using the full power of tomography or interferometry. The actual Level-2 processor software implementation is also briefly presented, along with preliminary results on airborne campaign data.
In particular, AGB estimation results will be shown on BIOMASS-like acquisitions emulated from tropical forests campaign data. The AGB estimation performance is observed to depend on the AGB range and degrades when ground topography is significant. Good performance is achieved when the AGB interval is large (> 400 t/ha) and the average is in the interval 200–250 t/ha . The algorithm is observed to be capable of achieving a relative RMSD of 20% with respect to in situ data using only few calibration points where reference AGB is available, although retrieval accuracy was observed to depend significantly on the quality of the available calibration points. Efforts are now focused on designing the global AGB estimation scheme for BIOMASS, especially with regards to calibration and validation AGB to be used.
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 Soja, M., Quegan, S., Mariotti d’Alessandro, M. Banda, F. Scipal, K., Tebaldini, S. Ulander, L.M.H. “Mapping above-ground biomass in tropical forests with ground-cancelled P-band SAR and limited reference data”, Remote Sens. Environ. Volume 253, February 2021, 112153
 M. Mariotti d’Alessandro, S. Tebaldini, S. Quegan, M. J. Soja, L. M. H. Ulander and K. Scipal, "Interferometric Ground Cancellation for Above Ground Biomass Estimation," in IEEE Transactions on Geoscience and Remote Sensing, vol. 58, no. 9, pp. 6410-6419, Sept. 2020
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