Forest height estimation from mountain forest areas using general model–based decomposition for polarimetric interferometric synthetic aperture radar images

Nghia Pham Minh; Bin Zou; Hongjun Cai; Chengyi Wang

doi:10.1117/1.JRS.8.083676

18 February 2014 Forest height estimation from mountain forest areas using general model–based decomposition for polarimetric interferometric synthetic aperture radar images

Nghia Pham Minh, Bin Zou, Hongjun Cai, Chengyi Wang

Author Affiliations +

Journal of Applied Remote Sensing, Vol. 8, Issue 1, 083676 (February 2014). https://doi.org/10.1117/1.JRS.8.083676

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.

CC BY: © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

Citation Download Citation

Nghia Pham Minh, Bin Zou, Hongjun Cai, and Chengyi Wang "Forest height estimation from mountain forest areas using general model–based decomposition for polarimetric interferometric synthetic aperture radar images," Journal of Applied Remote Sensing 8(1), 083676 (18 February 2014). https://doi.org/10.1117/1.JRS.8.083676

Published: 18 February 2014

ACCESS THE FULL ARTICLE

JOURNAL ARTICLE
19 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY