Retrieval of Volume Scatterer Information Using Three-component Decompostion Model, Based on Compact Polarimetry

DISCLAIMER This document describes work undertaken as part of a programme of study at the Faculty of Geo-Information Science and Earth Observation of the University of Twente. All views and opinions expressed therein remain the sole responsibility of the author, and do not necessarily represent those of the Faculty. i " Let my urge for triumph in life be dedicated to those who made me " realize my existence " and gave me " faith and constant support " to succeed in life " 03:17:11 ii iii ABSTRACT Forest monitoring has become an important necessity nowadays for forest management authorities to prevent deforestation, human encroachment and even for researchers to understand forest dynamics and to develop advanced technology for monitoring forest ecology and resources with less effort. Radar remote sensing employing polarimetric techniques has proved its capability in monitoring these aspects. The high demand and stringent availability of the fully-polarimetric data from very few SAR sensors has made researchers think about using low cost, low power dual-polarimetric systems to reproduce the fully-polarimetric data through compact polarimetric techniques. The purpose of this research is to explore the prospective of the compact polarimetric technique in (π/4) mode to derive and reproduce the pseudo-quadrature polarized data from the dual-polarimetric scattering vectors, based on coherency matrix approach, thereby using to study and assess the effect of volume scattering contribution of tree leaves, trunk and ground from the Sal forests of Barkot, Dehradun and the ecologically important Mangrove forests of the Sundarbans. The three-component scattering model was used to decompose the reproduced coherency matrix to study the volume scattering information from the forest scatterers. The data used for this study was ALOS PALSAR fully-polarimetric L-band data. The methodology applied for this study used the polarization state extrapolation algorithm, developed for covariance matrix approach which was modified to transform the reconstructed covariance matrix to coherency matrix for compact polarimetric (π/4) mode. The reconstructed coherency matrix was then decomposed using the Freeman and Durden decomposition model, and compared against the original fully-polarimetric data. Different data analysis including entropy, total power, diagonal elements of the coherency matrices and polarization signature were carried out to investigate and study the variation between the original and the reconstructed data. The volume scatterer contribution from both the forested areas was validated against the fully-polarimetric data using the cross-polarized multi look image as the reference data. The results show the potential of the …