Evaluation of modified four-component scattering power decomposition method over highly rugged glaciated terrain

Abstract

In recent years, there has been increased utilization of fully polarimetric synthetic aperture radar (POLSAR) data to study glaciated terrain features for glaciological and climate change modelling. This article is concerned with more accurate results and appropriate analysis of POLSAR data over a highly rugged glaciated area in Himalayan region. For this purpose, the modified Yamaguchi four-component scattering power decomposition (4-CSPD) method with a rotation concept of 3 6 3 coherency matrix [T] about line of sight is evaluated. It has been found that the modified Yamaguchi 4-CSPD method significantly improved the decomposition results as compared with the original 4-CSPD by minimizing the cross-polarized Horizontal-Vertical (HV) components. This modified 4-CSPD leads to enhancement in the double bounce scattering and surface scattering components and also avoids the overestimation problem in the volume scattering component as compared with the original 4-CSPD from the sloped terrain. The significant reductions of the negative power occurrence in the surface scattering (3.9%) and the double bounce scattering (19.7%) components have also been noticed as compared with the original 4-CSPD method over the glaciated area in this part of the Indian Himalaya.

Unsupervised Classification Method for Polarimetric Synthetic Aperture Radar Imagery Based on Yamaguchi Four-Component Decomposition Model

“…If the ratio is less than −2 dB, then the volume scattering power is listed as formula (10). If the ratio is greater than −2 dB and less than 2 dB, then the volume scattering power is listed as formula (11). If the ratio is greater than 2 dB, then the volume scattering power is listed as formula (12).…”

“…This term is close to zero for most natural scenes while it is noticeable for urban areas. This helix term is brought in by the scattering matrix of helices and is related to the complicated shapes of man-made structures, which are dominant in urban areas [11].…”

“…As regards the calculation of volume scattering power, it is necessary to revamp the original scheme [11]. The calculation of volume scattering power should be based on the ratio of backscattering magnitudes of ⟨| HH | 2 ⟩ versus ⟨| VV | 2 ⟩.…”

“…This algorithm is effective and computationally efficient. A four-component scattering model was proposed to decompose polarimetric synthetic aperture radar images by Yamaguchi et al [11][12][13][14][15]. This four-component model is an extension of Freeman model and is used to deal with nonreflection symmetric scattering case.…”

Retrieval of Spatial and Temporal Variability in Snowpack Depth over Glaciers in Svalbard Using GPR and Spaceborne POLSAR Measurements

“…Recently, A global SD mapping algorithm based on Sentinel-1 dual polarization data has been proposed [16] at 1 km spatial resolution. This method depends on cross polarization variability with snow depth, which can also be affected by the polarization orientation shift due to azimuthal slopes causing large depolarizations (cross polarization term) in mountainous regions [27]. This polarization orientation shift in snow-covered mountainous terrain may be translated into snow depth inversion.…”