Sensitivity of Compact Polarimetric SAR Parameters to Modeled Lake Ice Growth

Abstract

Synthetic aperture radar (SAR) is a valuable tool for lake ice monitoring. The recently proposed SAR configuration for Earth observation called compact polarimetric (CP) SAR could be a good compromised choice between conventional (single or dual) and fully polarimetric (FP) SAR for operational ice applications, including lake ice. Given its enhanced radar target information compared with conventional SAR systems over wider swath coverage compared with FP SAR, CP systems could play important role in the new generation of Earth observation systems. Herein, we study the evolution of CP SAR parameters from simulated CP SAR data in relation to early ice growth. Focus of the study is on four lakes located in Cornwallis Island, Canadian Central Arctic. We adopt parameters extracted from dual circular polarimetric and right circular transmit, linear (horizontal and vertical) receive configurations. In this study, we consider the ice thickness calculated from an established empirical model. Meteorological and ice climatological data were used to support the analysis. Results demonstrated a potential connection between a number of CP parameters and lake ice growth. Furthermore, we were able to highlight the relationship between the density of air bubbles in ice layer and the intensity of volume scattering mechanism, leading to the identification of lakes with increased gas production activities. Thus, differences between lakes in terms of density of air bubbles were detected and statistically evaluated. Index Terms-Bubble in lake ice, compact polarimetric (CP) synthetic aperture radar (SAR), ice thickness, lake ice.This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination.

Fine Resolution Classification of New Ice, Young Ice, and First-Year Ice Based on Feature Selection from Gaofen-3 Quad-Polarization SAR

“…It is important to reduce the parameter set and determine which parameters are optimal for sea ice classification [64]. If the spatial dimensions of the features are too small, it may not be possible to identify the characteristics of sea ice, which makes it difficult to achieve the desired classification results.…”

“…The parameters of hybrid-pol backscatter intensity contain the right-circular transmit-receive intensity (σ 0 rr ), the right-circular transmit and left-circular receive intensity (σ 0 rl ), the left-circular transmit-receive intensity (σ 0 ll ), the right-circular transmit and horizontal receive intensity (σ 0 rh ) and the right-circular transmit and vertical receive intensity (σ 0 rv ). These parameters represent the power of various transmission and reception modes [64]. They can all be simulated from the quad-pol SAR data without developing new hardware [19].…”

“…ρ rh−rv denotes the correlation coefficient between the σ 0 rh and σ 0 rv , and ρ rr−ll denotes the correlation coefficient between σ 0 rr and σ 0 ll . We calculated (R rh−rv ) as the ratio of σ 0 rh and σ 0 rv , (R rr−rl ) as the ratio of σ 0 rr and σ 0 rl , (R rl−ll ) as the ratio of σ 0 rl and σ 0 ll , and (R rr−ll ) as the ratio of σ 0 rr and σ 0 ll [64]. With the advance of hybrid-pol SAR, many decompositions have been developed [63,65].…”

“…With the advance of hybrid-pol SAR, many decompositions have been developed [63,65]. They are m − χ, m − δ, m − ψ and m − α, which have demonstrated utility in oil slick detection [66] and sea ice melt monitoring [16,64]. Here, m indicates the degree of polarization, which is the ratio of the polarized power to the total power, χ is the ellipticity, δ is the relative phase, ψ is the orientation and α is the polarization angle.…”

“…To achieve this, we analyzed the ways in which these parameters were obtained and the corresponding scattering mechanism. The quad-pol parameters can be divided into three categories [47,64]:…”