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

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

doi: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.

Highlights

Polarimetric interferometric synthetic aperture radar (PolInSAR) is a type of remote sensing technique that integrates the advantage of both polarimetric SAR and interferometric SAR
In the last 15 years, many techniques have been proposed for forest height estimation using single-baseline PolInSAR images, most of which can be broken up into two categories
We proposed a forest height estimation approach from mountain forest areas using general model–based decomposition (GMBD) technique for PolInSAR image

Summary

Introduction

Polarimetric interferometric synthetic aperture radar (PolInSAR) is a type of remote sensing technique that integrates the advantage of both polarimetric SAR and interferometric SAR. In the last 15 years, many techniques have been proposed for forest height estimation using single-baseline PolInSAR images, most of which can be broken up into two categories. The second major group is based on model-based decomposition technique for PolInSAR image as introduced by BallesterBerman and Lopez-Sanchez[6] and Neuman et al.[7] The technique opened a new way for forest height estimation using the model-based decomposition technique. In this technique, they assumed that the volume contribution is a cloud of uniformly randomly distributed thin cylinders. Natural forest canopy shows preferential orientation of the branches, smaller

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