The Effect of Topography on Target Decomposition of Polarimetric SAR Data

Sang-Eun Park

doi:10.3390/rs70504997

Abstract

Polarimetric target decomposition enables the interpretation of radar images more easily, mostly based on physical assumptions, i.e., fitting physically-based scattering models to the polarimetric SAR observations. However, the model-fitting result cannot be always successful. Particularly, the performance of model-fitting in sloping forests is still an open question. In this study, the effect of ground topography on the model-fitting-based polarimetric decomposition techniques is investigated. The estimation accuracy of each scattering component in the decomposition results are evaluated based on the simulated target matrix by using the incoherent vegetation scattering model that accounts for the tilted scattering surface beneath the forest canopy. Experimental results show that the surface and the double-bounce scattering components can be significantly misestimated due to the topographic slope, even when the volume scattering power is successfully estimated.

Highlights

In the field of remote sensing, utilization of microwave frequency with synthetic aperture radar (SAR)has many operational advantages in monitoring the Earth’s surface with its high-resolution, day and night imaging capability
The experimental analysis of topography effects on the target decomposition methods is carried out by using the simulated coherency matrix obtained from vegetation scattering model of sloping terrain [13]
This vegetation scattering model is based on the first-order solution of the radiative transfer model and considers a tilted scattering surface beneath forest canopy

Summary

Introduction

In the field of remote sensing, utilization of microwave frequency with synthetic aperture radar (SAR). SAR data provide a possibility to separate scattering contributions of different natures, which can be associated with certain elementary scattering mechanisms This specific polarimetric data processing, Remote Sens. 2015, 7 named the polarimetric target decomposition, enables interpretation of radar images more and, has been an active topic for about two decades This is mostly based on eigenvalue-eigenvector analysis [1,2,3] or on physical assumptions, i.e., fitting physically-based scattering models to the polarimetric SAR observations [4,5,6,7]. Eigenvalue-eigenvector-based decomposition is a rigorous mathematical technique leading to an understanding of averaged scattering mechanisms without symmetry constraints It is not physically based, and the interpretation of the results is not easy, especially for multiple or volume scattering problems in vegetation.

Model-Fitting-Based POLSAR Decomposition

Simulation of Polarimetric Scattering from Mountainous Forests

Changes of Scattering Mechanisms in Sloping Terrain

Effect of Range Slope on Decomposition Results

Effect of Azimuth Slope on Decomposition Results

Conclusions