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Journal of Applied Remote Sensing • Open Access

Forest height estimation from mountain forest areas using general model–based decomposition for polarimetric interferometric synthetic aperture radar images
Author(s): Nghia Pham Minh; Bin Zou; Hongjun Cai; Chengyi Wang

Paper Abstract

The estimation of forest parameters over mountain forest areas using polarimetric interferometric synthetic aperture radar (PolInSAR) images is one of the greatest interests in remote sensing applications. For mountain forest areas, scattering mechanisms are strongly affected by the ground topography variations. Most of the previous studies in modeling microwave backscattering signatures of forest area have been carried out over relatively flat areas. Therefore, a new algorithm for the forest height estimation from mountain forest areas using the general model–based decomposition (GMBD) for PolInSAR image is proposed. This algorithm enables the retrieval of not only the forest parameters, but also the magnitude associated with each mechanism. In addition, general double- and single-bounce scattering models are proposed to fit for the cross-polarization and off-diagonal term by separating their independent orientation angle, which remains unachieved in the previous model-based decompositions. The efficiency of the proposed approach is demonstrated with simulated data from PolSARProSim software and ALOS-PALSAR spaceborne PolInSAR datasets over the Kalimantan areas, Indonesia. Experimental results indicate that forest height could be effectively estimated by GMBD.

Paper Details

Date Published: 18 February 2014
PDF: 19 pages
J. Appl. Rem. Sens. 8(1) 083676 doi: 10.1117/1.JRS.8.083676
Published in: Journal of Applied Remote Sensing Volume 8, Issue 1
Show Author Affiliations
Nghia Pham Minh, Harbin Institute of Technology (China)
Bin Zou, Harbin Institute of Technology (China)
Hongjun Cai, Harbin Institute of Technology (China)
Chengyi Wang, Forestry Research Institute (China)

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