2011elib (German Aerospace Center)Open access

MULTIBASELINE POLARIMETRIC SAR INTERFEROMETRY FOREST HEIGHT INVERSION APPROACHES

Seung-Kuk Lee, Florian Kugler, Konstantinos Papathanassiou, Irena Hajnsek

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Abstract

Polarimetric SAR interferometry (Pol-InSAR) is a radar remote sensing technique that is sensitive to the vertical distribution of scattering processes in volumes. The Random Volume over Ground (RVoG) model is a powerful tool used to invert forest height from Pol-InSAR data. But Pol-InSAR inversion performance depends critically on uncompensated decorrelation contributions (i.e. temporal decorrelation in repeat pass system) and the height sensitivity of the effective baseline, represented by the vertical wavenumber . To overcome these constraints a multibaseline Pol-InSAR inversion approach could be an effective solution. In this paper, different approaches for combining multibaseline Pol-InSAR inversion results are proposed and discussed. Multibaseline Pol-InSAR data acquired by DLR’s E-SAR system over the Traunstein forest during the TempoSAR 2008 campaign are used.

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Polarimetric SAR interferometry (Pol-InSAR) is a radar remote sensing technique that is sensitive to the vertical distribution of scattering processes in volumes. The Random Volume over Ground (RVoG) model is a powerful tool used to invert forest height from Pol-InSAR data. But Pol-InSAR inversion performance depends critically on uncompensated decorrelation contributions (i.e. temporal decorrelation in repeat pass system) and the height sensitivity of the effective baseline, represented by the vertical wavenumber . To overcome these constraints a multibaseline Pol-InSAR inversion approach could be an effective solution. In this paper, different approaches for combining multibaseline Pol-InSAR inversion results are proposed and discussed. Multibaseline Pol-InSAR data acquired by DLR’s E-SAR system over the Traunstein forest during the TempoSAR 2008 campaign are used.

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Available abstract

Polarimetric SAR interferometry (Pol-InSAR) is a radar remote sensing technique that is sensitive to the vertical distribution of scattering processes in volumes. The Random Volume over Ground (RVoG) model is a powerful tool used to invert forest height from Pol-InSAR data. But Pol-InSAR inversion performance depends critically on uncompensated decorrelation contributions (i.e. temporal decorrelation in repeat pass system) and the height sensitivity of the effective baseline, represented by the vertical wavenumber . To overcome these constraints a multibaseline Pol-InSAR inversion approach could be an effective solution. In this paper, different approaches for combining multibaseline Pol-InSAR inversion results are proposed and discussed. Multibaseline Pol-InSAR data acquired by DLR’s E-SAR system over the Traunstein forest during the TempoSAR 2008 campaign are used.

Key concepts: Decorrelation, Interferometric synthetic aperture radar, Remote sensing, Polarimetry, Interferometry, Inversion (geology), Geology, Synthetic aperture radar

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