Inversion algorithms for remote sensing of sea ice

Veysoglu, M.E.; Ewe, Hong Tat; Jordan, Arthur K.; Shin, R.T.; Kong, Jin Au

doi:10.1109/igarss.1994.399203

Cited by 9 publications

(6 citation statements)

References 2 publications

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“…where |ψ| 2 n is the dense medium phase correction factor and S is the Stokes' matrix for Mie scatterers with the Close Spacing Amplitude Correction [9]. From the previous equation, |ψ| 2 n can be further expressed as:…”

Section: Rt-dmpact Forward Modelmentioning

confidence: 99%

“…With the increasing awareness on global climate change and the fact that sea ice, covering up to 25% of the earth's surface, plays a critical role in balancing the world climate, many studies are being directed towards the sea ice extent and the heat exchange between the ocean and the atmosphere [1]. Yet, such research can be both costly and dangerous, due to the extremity of the polar region's climate and weather [2]. The application of microwave remote sensing in the polar region offers a practical means to monitor and retrieve data from the harsh continent.…”

Section: Introductionmentioning

confidence: 99%

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An Inverse Model for Sea Ice Thickness Retrieval Using Active Microwave Remote Sensing

Lee¹,

Lim²,

Ewe³

et al. 2008

PIERS Online

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Sea ice encompasses a large area within the polar region and greatly influences the earth's climate system. One particular sea ice parameter of interest in understanding the dynamics of the sea ice cover and the heat exchange between the ocean and the atmosphere is its thickness. Due to this, there has been an increase in interest towards research in the polar region. Yet the harsh environment proves a great challenge to scientists doing research in those regions. The use of microwave remote sensing to retrieve physical data of the polar region, in particular sea ice thickness serves as a practical solution to the problem. In this paper, an RT-DMPACT Inverse Model to retrieve sea ice thickness from active microwave remote sensing data is presented. The inverse model is a combination of the Radiative Transfer Theory with Dense Medium Phase and Amplitude Correction Theory (RT-DMPACT) forward model and the Levenberg-Marquardt Optimization algorithm. The RT-DMPACT forward model is an improved forward model and is applied to generate the radar backscatter data, where the DMPACT is included to account for the close spacing effect among the scatterers within the medium. The Levenberg-Marquardt Optimization algorithm is then applied to improve on the set of input parameters until the sea ice thickness can be estimated. Data from ground truth measurements carried out in Ross Island, Antarctica, such as sea ice surface roughness and temperature, together with radar backscatter data extracted from purchased satellite images, are used as inputs to estimate the sea ice thickness in an area. The estimated sea ice thickness is then compared with the ground truth measurement data to verify its accuracy. The results from the simulation show promise towards the use of the RT-DMPACT inverse model to retrieve sea ice thickness from actual conditions in the polar region.

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Section: Rt-dmpact Forward Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An Inverse Model for Sea Ice Thickness Retrieval Using Active Microwave Remote Sensing

Lee¹,

Lim²,

Ewe³

et al. 2008

PIERS Online

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Section: A Radiative Transfer-thermodynamic Inverse Model For Thicknmentioning

confidence: 99%

“…Recently, ice-thickness reconstruction algorithms based on the combined use of sea ice electromagnetic scattering models, time-series remote-sensing data, and a parametric estimation technique have been developed [52], [86], [87], [99], [100]. Veysoglu et al [99], [100] have developed an inversion algorithm using passive microwave measurements of sea ice. They have shown that, by incorporating a Stefan's growth model [9] into the sea ice inverse scattering problem, the thickness estimation can be constrained sufficiently to predict more accurately the evolution of sea ice growth.…”

Section: A Radiative Transfer-thermodynamic Inverse Model For Thicknmentioning

confidence: 99%

Inverse electromagnetic scattering models for sea ice

Golden

Borup

Cheney

et al. 1998

IEEE Trans. Geosci. Remote Sensing

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Inverse scattering algorithms for reconstructing the physical properties of sea ice from scattered electromagnetic field data are presented. The development of these algorithms has advanced the theory of remote sensing, particularly in the microwave region, and has the potential to form the basis for a new generation of techniques for recovering sea ice properties, such as ice thickness, a parameter of geophysical and climatological importance. Moreover, the analysis underlying the algorithms has led to significant advances in the mathematical theory of inverse problems. In particular, the principal results include the following.

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“…Inverse algorithms for sea ice thickness retrieval based on a combination of the Radiative Transfer Theory, the Thermodynamic Ice Growth Model and the Levenberg-Marquardt Optimization Algorithm has been proposed [4][5][6]. The models use time-series electromagnetic scattering data to retrieve sea ice thickness.…”

Section: Introductionmentioning

confidence: 99%

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

Lee

Lim²,

Ewe³

2011

PIER

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Abstract-In this study, an inverse microwave scattering model for sea ice has been developed for the purpose of sea ice thickness retrieval using radar backscatter data. The model is loosely based on the Radiative-Transfer-Thermodynamic Inverse Model for Sea Ice Thickness Retrieval from Time-Series Scattering Data. The developed inverse model is a combination of the Radiative Transfer Theory with Dense Medium Phase and Amplitude Correction Theory (RT-DMPACT) forward model and the Levenberg-Marquardt Optimization algorithm. Using input data from ground truth measurements carried out in Ross Island, Antarctica, together with radar backscatter data extracted from purchased satellite images, the sea ice thickness of an area is estimated using the inverse model developed. The estimated sea ice thickness is then compared with the ground truth measurement data to verify its accuracy. The results have shown good promise, with successful estimation of the sea ice thickness within ±0.15 m of the actual measurement. A theoretical analysis has also revealed that the model faces difficulty once the sea ice thickness exceeds 1.7 m. This can be considered in the future development and improvement of the model.

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Inversion algorithms for remote sensing of sea ice

Cited by 9 publications

References 2 publications

An Inverse Model for Sea Ice Thickness Retrieval Using Active Microwave Remote Sensing

An Inverse Model for Sea Ice Thickness Retrieval Using Active Microwave Remote Sensing

Inverse electromagnetic scattering models for sea ice

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

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