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Comparison of tropical forest Above Ground Biomass estimation techniques based on Polarimetric and Tomographic SAR data acquired at P band

Abstract : 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 Above-Ground-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 backscatterer 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.
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https://hal-univ-rennes1.archives-ouvertes.fr/hal-01770196
Contributor : Laurent Jonchère <>
Submitted on : Wednesday, April 18, 2018 - 4:40:39 PM
Last modification on : Thursday, October 15, 2020 - 3:16:59 AM

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Bassam El Hajj Chehade, Laurent Ferro-Famil, Stefano Tebaldini, Dinh Ho Tong Minh, Thuy Le Toan. Comparison of tropical forest Above Ground Biomass estimation techniques based on Polarimetric and Tomographic SAR data acquired at P band. 14th European Radar Conference (EURAD), Oct 2017, Nuremberg, Germany. ⟨10.23919/EURAD.2017.8249139⟩. ⟨hal-01770196⟩

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