A Study of an Inversion Model for Sea Ice Thickness Retrieval in Ross Island, Antarctica

Lee, Yu Jen; Lim, W. L.; Ewe, Hong Tat

doi:10.2528/pier10100411

Cited by 13 publications

(7 citation statements)

References 20 publications

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“…Details of the formulation can be found in Chuah et al [9] . This radiative transfer equation has been solved up to second order [1] . The solution terms of the equation were then grouped into three major scattering terms contributing to the backscattering return.…”

Section: Model Formulationmentioning

confidence: 99%

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Remote sensing backscattering model for sea ice: Theo-retical modelling and analysis

Syahali¹,

Hong²

2013

APS

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Remote sensing has been used in Antarctic studies as an earth observation technique to study the polar region. A remote sensing forward model is an important tool in polar research to study and understand scattering mechanisms and sensitivity of physical parameters of snow and sea ice. In this paper, a reliable theoretical model to study sea ice is developed. The theoretical model in a prior work was improved by including multiple-surface scattering, based on an existing integral equation model and additional second-order surface-volume scattering. This model is applied to a desalinated ice layer above thick saline ice and analyzed using different frequencies, bottom surface roughness and sea-ice layer thickness. Improvement in calculation of the backscattering coefficient of the sea-ice layer is investigated for both co-polarized and cross-polarized returns. The effect on each scattering mechanism is also investigated, to understand in more detail the effect of surface multiple scattering and second-order surface-volume scattering. Comparisons are also made with field measurement results, to validate the theoretical model. Results show improvement in the total backscattering coefficient for cross-polarized return in the studied range, suggesting that multiple-surface scattering and surface-volume scattering up to second order are important scattering mechanisms in the sea-ice layer and should not be ignored in polar research.

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Section: Model Formulationmentioning

confidence: 99%

“…To achieve this, a reliable forward model should be developed. A remote sensing forward model is also important in polar research to study the sensitivity of physical parameters in this topic, for use in the development of an inverse model of parameter retrieval using microwave remote sensing [1] .…”

Section: Introduction*mentioning

confidence: 99%

Remote sensing backscattering model for sea ice: Theo-retical modelling and analysis

Syahali¹,

Hong²

2013

APS

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“…It is important to develop such forward models to understand various scattering mechanisms in the medium and how microwave interacts with different configuration of the medium for better interpretation of satellite images. In addition, they are also crucial towards the development of inverse models for the purpose of parameter retrieval using microwave remote sensing [7]. The traditional Radiative Transfer theory is based on the energy transport equation which was developed to treat propagation and scattering problems in the atmosphere.…”

Section: Introductionmentioning

confidence: 99%

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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“…However, the theoretical models have two main limitations: 1) They adopt simplifying assumptions in the modeling of real phenomena, which may result in deviations from correct estimations; and 2) they neglect sensor noise, calibration errors, and local propagations that may produce variability of the relations between the target variables and the features in different regions of the feature space. The first issue can be mitigated by increasing the complexity of the model, which results in the reduction of generalization ability [15], whereas the second issue can be addressed by applying a statistical component to the estimation obtained by the theoretical model [23]. However, often, the results are not satisfactory.…”

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confidence: 97%

A Novel Hybrid Method for the Correction of the Theoretical Model Inversion in Bio/Geophysical Parameter Estimation

Castelletti

Pasolli

Bruzzone

et al. 2016

IEEE Trans. Geosci. Remote Sensing

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This paper presents a novel hybrid method to the estimation of bio/geophysical parameters, which models and corrects deviations from correct target values when theoretical electromagnetic models are used for the inversion process. The proposed hybrid method integrates theoretical models with empirical observations associated to a few field reference samples. This is achieved based on two steps. In the first step, deviations between estimations obtained by a theoretical model and empirical observations are initially computed. Then, deviations associated to unlabeled samples (for which reference measures are not existing) are characterized based on two different strategies: 1) the global deviation bias strategy (which assumes that the deviations of samples are constant within the input space); and 2) the local deviation bias strategy (which assumes that the deviations of samples are variable within different portions of the input space). In the second step, the theoretical model estimates of unlabeled samples are corrected based on the estimated deviations. The experimental analysis carried out in the context of soil moisture content retrieval from microwave remotely sensed data confirms the effectiveness of the proposed hybrid estimation method.Index Terms-Biophysical parameter estimation, empirical models, hybrid model, remote sensing, theoretical electromagnetic models.

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A Study of an Inversion Model for Sea Ice Thickness Retrieval in Ross Island, Antarctica

Cited by 13 publications

References 20 publications

Remote sensing backscattering model for sea ice: Theo-retical modelling and analysis

Remote sensing backscattering model for sea ice: Theo-retical modelling and analysis

Multilayer Model Formulation and Analysis of Radar Backscattering From Sea Ice

A Novel Hybrid Method for the Correction of the Theoretical Model Inversion in Bio/Geophysical Parameter Estimation

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