A scattering model for snow-covered sea ice

Tjuatja, S.; Fung, A.K.; Bredow, J.W.

doi:10.1109/36.158876

Cited by 43 publications

(19 citation statements)

References 16 publications

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“…The results of the comparison for sites DS-7 and DS-9 are shown in Figures 11 and 12, respectively. The parameters used in this analysis are summarized in [25,27]. The figures show that the backscattering coefficient from multilayer model using Radiative Transfer Theory agrees well with the multilayer model using the Matrix Doubling model.…”

Section: Comparison Between Different Modelsmentioning

confidence: 67%

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Multilayer Model Formulation and Analysis of Radar Backscattering From Sea Ice

Albert¹,

Lee

Ewe³

et al. 2012

PIER

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Abstract-The Antarctic continent is an extremely suitable environment for the application of remote sensing technology as it is one of the harshest places on earth. Satellite images of the terrain can be properly interpreted with thorough understanding of the microwave scattering process. The proper model development for backscattering can be used to test the assumptions on the dominating scattering mechanisms. In this paper, the formulation and analysis of a multilayer model used for sea ice terrain is presented. The multilayer model is extended from the previous single layer model developed based on the Radiative Transfer theory. The Radiative Transfer theory is chosen because of its simplicity and ability to incorporate multiple scattering effects into the calculations. The propagation of energy in the medium is characterized by the extinction and phase matrices. The model also incorporates the Dense Medium Phase and Amplitude Correction Theory (DM-PACT) where it takes into account the close spacing effect among scatterers. The air-snow interface, snow-sea ice interface and sea ice-ocean interface are modelled using the Integral Equation Method (IEM). The simulated backscattering coefficients for co-and cross-polarization using the developed model for 1 GHz and 10 GHz are presented. In addition, the simulated backscattering coefficients from the multilayer model were compared with the measurement results obtained from Coordinated Eastern Artic Experiment (CEAREX) (Grenfell, 1992) and with the results obtained from the model developed by Saibun Tjuatja (based on the Matrix Doubling method) in 1992.

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Section: Comparison Between Different Modelsmentioning

confidence: 67%

“…Further details regarding the model can be found in [18,27]. Saibun (1992) also performed the comparison study between the backscattering from their model and the backscattering from the CEAREX measurements.…”

Section: Comparison Between Different Modelsmentioning

confidence: 99%

Multilayer Model Formulation and Analysis of Radar Backscattering From Sea Ice

Albert¹,

Lee

Ewe³

et al. 2012

PIER

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“…In the matrix doubling method [15,16], the forward and backward single scattering matrices of the foam layer, and the reflection and transmission matrices of the air-foam and foam-seawater interfaces can be obtained for both incident and reversed incident directions. By combining the scattering matrices of the foam layer and the effective reflection and transmission matrices of the interfaces, the multiple operator L u of the up-welling effective emission source u u is expressed as follows:…”

Section: Emission From Foam-covered Ocean Surface: Matrix Doubling Mementioning

confidence: 99%

“…5). The emission from the foamcovered ocean surface is determined by solving the corresponding vector radiative transfer equations using the matrix doubling method [15,16]. The emission model accounts for multiple scattering within the foam layer and interactions between the foam layer and randomly rough air-foam and foam-seawater interfaces.…”

Section: Introductionmentioning

confidence: 99%

A Numerical Study on Physical Characterizations of Microwave Scattering and Emission From Ocean Foam Layer

Jiang¹,

Xu²,

Chen³

et al. 2017

PIER B

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Abstract-This paper presents a numerical study of microwave scattering and emission from a foamcovered ocean surface. The foam layer is modeled as an inhomogeneous layer with randomly rough airfoam and foam-seawater boundaries. Kelvin's Tetrakaidecahedron structure is selected as the skeleton for simulating the air bubbles in the foam layer. The electromagnetic characteristics of the foam layer, including absorption and scattering coefficients for both vertical and horizontal polarizations, are calculated using a multilevel volume UV fast algorithm to accelerate the numerical computation of three dimensional Maxwell's equations. The surface scattering at air-foam and foam-seawater interfaces is determined using the integral equation model (IEM). The microwave emission from the foam-covered ocean surface, which accounts for multiple incoherent interactions within the foam layer and between the foam and interfaces, is modeled using the vector radiative transfer approach and numerically solved using the matrix doubling method. The model analyses of volume scattering and absorption of the foam layer reveal that the volume scattering coefficient of a foam layer increases with increasing water fraction at all selected frequencies, and its polarization dependence is negligible at a water fraction less than 2%. At 10.8 GHz and 18 GHz, the H-polarized scattering coefficient is smaller than the Vpolarized scattering coefficient for a larger water fraction; the opposite occurs at 36.5 GHz, at which V polarized scattering is weaker compared to H-polarized scattering. The model analyses of emission from a foam-covered ocean surface reveal that the emissivities at all selected operating frequencies have similar dependencies with water fraction and frequency, and they exhibit different sensitivities to water fractions. Moreover, the emissivities at high operating frequencies exhibit higher sensitivities to water fractions than the lower ones.

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“…RT theoretical models have been developed and used to simulate major types of mediums such as snow, sea ice and vegetation [1][2][3][4][5][6]. For densely packed medium, two popular methods were developed which are quasicrystalline approximation (QCA) [7] and phase and amplitude correction theory [8].…”

Section: Introductionmentioning

confidence: 99%

A Study of Scattering From Snow Embedded With Non-Spherical Shapes of Scatterers With Relaxed Hierarchical Equivalent Source Algorithm (Rhesa)

Lum¹,

Ewe²,

Jiang³

2017

PIER M

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Abstract-Remote sensing has been used widely in studying the earth terrain such as snow or sea ice due to its fast, convenient and long-term monitoring capabilities. SAR images acquired could be used to analyze the condition of snow, snow water equivalent (SWE), surface roughness and others. Theoretical models have also been developed to understand how microwave interacts with the snow medium and the scatterers embedded inside the medium. Conventionally, spherical shape of scatterers is commonly used to represent the ice particles embedded inside snow where the actual shape of scatterers can vary. This paper is to present a theoretical model based on radiative transfer formulation that utilizes computational electromagnetics in the modelling of scattering from arbitrary shape of scatterers. The paper also studies the effect of scatterer shape on scattering mechanisms and total backscattering coefficient. Numerical solution of Relaxed Hierarchical Equivalent Source Algorithm (RHESA) was integrated with existing radiative transfer theoretical model to simulate a layer of random discrete snow medium. Several shapes of scatterers were simulated, and theoretical simulation were compared with ground truth measurement data with promising results.

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A scattering model for snow-covered sea ice

Cited by 43 publications

References 16 publications

Multilayer Model Formulation and Analysis of Radar Backscattering From Sea Ice

Multilayer Model Formulation and Analysis of Radar Backscattering From Sea Ice

A Numerical Study on Physical Characterizations of Microwave Scattering and Emission From Ocean Foam Layer

A Study of Scattering From Snow Embedded With Non-Spherical Shapes of Scatterers With Relaxed Hierarchical Equivalent Source Algorithm (Rhesa)

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