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Comparison of tropical forest above ground biomass estimation techniques based on polarimetrie and tomographic SAR data acquired at P band

To understand and quantify the role of forests on carbon cycle and its impact on climate change, it is critical to accurately quantify and monitor changes in forest AboveGround-Biomass (AGB). New advances in radar technologies have enabled the development of methods to map forest structure in 3-D. These techniques are based on the use of Polarimetric SAR Tomography (PolTomSAR) that enables the estimation of vertical profiles through a tridimensional (3-D) mapping of the backscattered power. The estimated vertically-spaced slices of backscattered power may contain information relative to two uncorrelated layers: the ground defined as a surface backscat-terer and the canopy modeled with its volume vertical structure. Thus, an accurate AGB information may be extracted from the power measured at a domain adapted to the canopy layer and less affected by the ground echo mainly due to the double bounce contribution. An algebraic synthesis of the forest allows a Sum of Kronecker Product (SKP2-) decomposition of the data covariance matrix which makes possible a polarimetric filtering of the ground echo. Moreover, the processing of a vertical domain adapted to the TomSAR vertical resolution and to the tree height allows a spatial filtering of the ground echo. The proposed tomographic biomass estimator is compared to the existing ones using P-band data acquired by the SETHI sensor over the Paracou data site in French Guiana in 2009.