Title :
Polarimetric-interferometric boreal forest scattering model for BIOMASS end-to-end simulator
Author :
Soja, Maciej J. ; Ulander, Lars M. H.
Author_Institution :
Chalmers Univ. of Technol., Gothenburg, Sweden
Abstract :
A polarimetric-interferometric forward model (FM) for extended covariance matrix modeling is presented. The FM has been designed to be used within the end-to-end simulator for BIOMASS, a new ESA satellite mission aiming at the global mapping of above-ground forest biomass with P-band synthetic aperture radar (SAR). The FM uses linear regression models for prediction of backscatter intensity and HH-VV correlation coefficient, and the random volume over ground (RVoG) model for the prediction of the interferometric correlation coefficients. For boreal forest, parameter values for these sub-models have been derived using polarimetric-interferometric SAR data acquired within the BioSAR 2007 campaign over the Swedish test site Remningstorp. The FM is evaluated qualitatively in a boreal forest scenario through a side-by-side comparison with BioSAR 2007 data. The general agreement is good, although there are regions with structures which cannot be reproduced by the model, probably due to insufficient forest description by the input parameters.
Keywords :
covariance matrices; radar interferometry; radar polarimetry; synthetic aperture radar; vegetation; AD 2007; BIOMASS end-to-end simulator; BioSAR campaign; BioSAR data; ESA satellite mission; HH-VV correlation coefficient; P-band SAR; P-band synthetic aperture radar; RVoG model; Remningstorp; Swedish test site; above-ground forest biomass global mapping; backscatter intensity prediction; boreal forest scenario; extended covariance matrix modeling; input parameter; insufficient forest description; interferometric correlation coefficient prediction; linear regression model; polarimetric-interferometric FM; polarimetric-interferometric SAR data; polarimetric-interferometric boreal forest scattering model; polarimetric-interferometric forward model; random volume over ground model; sub-model parameter value; Biological system modeling; Biomass; Coherence; Covariance matrices; Data models; Frequency modulation; Synthetic aperture radar; BIOMASS; extended covariance matrix; forward model;
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2014 IEEE International
Conference_Location :
Quebec City, QC
DOI :
10.1109/IGARSS.2014.6946611