General three-layer scattering model for forest parameter estimation using single-baseline polarimetric interferometry synthetic aperture radar data

Nghia Pham Minh; Bin Zou; Yan Zhang; Vannhu Le

doi:10.1117/1.JRS.9.096043

28 May 2015 General three-layer scattering model for forest parameter estimation using single-baseline polarimetric interferometry synthetic aperture radar data

Nghia Pham Minh, Bin Zou, Yan Zhang, Vannhu Le

Author Affiliations +

Journal of Applied Remote Sensing, Vol. 9, Issue 1, 096043 (May 2015). https://doi.org/10.1117/1.JRS.9.096043

Abstract

The random volume over ground (RVoG) model has been extensively applied to polarimetric interferometry SAR (PolInSAR) data for the retrieval of forest geophysical parameters. The complex interferometric coherence of the RVoG model was originally derived in a simplified way by neglecting one of the two possible contributions of the ground response: direct return from the ground or double-bounce interaction with the stems or trunks. In many cases, their influence depends on both the system and scene parameters, and none of them should be ignored a priori. Therefore, a more general model accounting for the simultaneous retrieval of the both ground contributions should be considered. Based on the characteristics of the scattering progress in the forest area, a general three-layer scattering model (GTLSM) is proposed to extract forest parameters using L-band single-baseline PolInSAR data. The proposed model assumes the vertical structural forest composed of three layers: canopy, tree-trunk, and ground layer, which account for the simultaneous effects of three scattering components on complex coherence. The GTLSM performance is evaluated with simulated data from PolSARProSim software and spaceborne data acquired by the SIR-C/X-SAR system. Experimental results indicate that forest parameters could be effectively extracted by the proposed GTLSM.

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Nghia Pham Minh, Bin Zou, Yan Zhang, and Vannhu Le "General three-layer scattering model for forest parameter estimation using single-baseline polarimetric interferometry synthetic aperture radar data," Journal of Applied Remote Sensing 9(1), 096043 (28 May 2015). https://doi.org/10.1117/1.JRS.9.096043

Published: 28 May 2015

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