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Journal of Applied Remote Sensing

General three-layer scattering model for forest parameter estimation using single-baseline polarimetric interferometry synthetic aperture radar data
Author(s): Nghia Pham Minh; Bin Zou; Yan Zhang; Vannhu Le
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Paper 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 <italic<a priori</italic<. 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.

Paper Details

Date Published: 28 May 2015
PDF: 18 pages
J. Appl. Remote Sens. 9(1) 096043 doi: 10.1117/1.JRS.9.096043
Published in: Journal of Applied Remote Sensing Volume 9, Issue 1
Show Author Affiliations
Nghia Pham Minh, Le Quy Don Technical Univ. (Vietnam)
Bin Zou, Harbin Institute of Technology (China)
Yan Zhang, Harbin Institute of Technology (China)
Vannhu Le, Harbin Institute of Technology (China)


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