A Study of Dense Medium Scattering and Its Applications in Sea Ice Research in Ross Island, Antarctica Y. J. Lee1, W. K. Lim2, H. T. Ewe1 and H. T. Chuah1 1Universiti Tunku Abdul Rahman 2Multimedia University
Contents • Introduction • Development and Application of the Dense Medium Phase and Amplitude Correction Theory (DM-PACT) • Modeling of the Sea Ice and Ice Shelf • Development of Inverse Scattering Models for Sea Ice Thickness Retrieval • Conclusion
Introduction • Development of remote sensing technology – satellites and synthetic aperture radar (SAR). • Increase in use of remote sensing devices for data retrieval. • Many applications evolving with the technology. • Need for proper forward and inverse scattering models for such applications. K.M. Golden, M. Cheney, K.H. Ding, A.K. Fung, T.C. Grenfell, D. Isaacson, J.A. Kong, S.V. Nghiem, J. Sylvester, and D.P. Winebrenner, “Forward electromagnetic scattering models for sea ice,” IEEE Transactions on Geoscience and Remote Sensing, Vol. 36, No. 5, pp. 1655–1674, 1998
Development of the DM-PACT • Many forward models were developed. • Several models utilized the Radiative Transfer Theory (RTT), which can be written in the form (Chandrasekhar 1960): • I, e, P, dΩ and z arethe Stokes vector, extinction matrix, phase matrix of the medium, solid angle and vertical direction respectively. Chandrasekhar, S., Radiative Transfer. New York: Dover, 1960
Early modeling assumes a homogeneous medium – scatterers in far field from one another. • Only applies when: • Scatterers are small. • Average spacing larger than /3. • Solution: Improvements were made to the phase matrix, P, in  using the Antenna Array Theory.
The improved phase matrix, P has the following expression: • is the dense medium phase correction factor (Chuah et al. 1996) and S is the Stokes’ matrix for Mie scatterers with the Close Spacing Amplitude Correction (Fung and Eom 1985). Chuah, H.T., S. Tjuatja, A.K. Fung, and J.W. Bredow, “A phase matrix for a dense discrete random medium: evaluation of volume scattering coefficient,” IEEE Transactions on Geoscience and Remote Sensing, Vol. 34, No. 5, pp. 1137–1143, 1996 A.K. Fung, and H.J.Eom, “A study of backscattering and emission from closely packed inhomogeneous media,” IEEE Trans. Geoscience & Remote Sensing,Vol. 23, No. 5, pp. 761–767, 1985
takes into account the close spacing effect of scattering among the scatterers. • S relates the scattered intensities to the incident intensities of the scatterer.
From equation , can further be expressed as the following: • where • d is the average distance between scatterers • k is the propagation vector • l is the correlation length
The improved phase matrix – Dense Medium Phase and Amplitude Correction Theory (DM-PACT). • An analysis using the DM-PACT based on iterative solution on electrically dense medium was done (Ewe et al.). S. Tjuatja, A.K. Fung, and J. Bredow, “A scattering model for snow-covered sea ice,” IEEE Trans. Geoscience & Remote Sensing,Vol. 30, No. 4, pp. 804–810, 1992 H.T. Ewe, and H.T. Chuah, “An analysis of the scattering of discrete scatterers in an electrically dense medium,” 1998 IEEE International Geoscience and Remote Sensing Symposium Proceedings (IGARSS'98), Vol. 5, pp. 2378–2380, 1998 H.T.Ewe, and H.T. Chuah, “A Study of Dense Medium Effect Using A Simple Backscattering model,” 1997 IEEE International Geoscience and Remote Sensing Symposium Proceedings (IGARSS'97): Remote Sensing - A Scientific Vision for Sustainable Development, Vol. 3, pp. 1427–1429, 1997
Application of the DM-PACT • A backscattering model was developed (Ewe et al.) for inhomogeneous media. • Model incorporates: • Iterative solution for RTT • DM-PACT • IEM Model to characterize rough surface H.T. Ewe, M.E. Veysoglu, C.C. Hsu, R.T. Shin, and J.A. Kong, “Radiative Transfer Theory for Remote Sensing of Sea Ice”, 1994 IEEE International Geoscience and Remote Sensing Symposium Proceedings (IGARSS'94): Surface and Atmospheric Remote Sensing – Technologies, Data Analysis an Interpretation, Vol. 1, pp. 623–625, 1994 H.T. Ewe, H.T. Chuah, and A.K. Fung, “A backscatter model for a dense discrete medium: Analysis and numerical results,” Remote Sensing of Environment, Vol. 65, No. 2, pp. 195–203, 1998 Fung, A.K., Microwave Scattering and Emission Models and Their Applications, Norwood, MA: Artech House, 1994 C.Y. Hsieh, and A.K. Fung, “Application of an Extended IEM to Multiple Surface Scattering and Backscatter Enhancement,” Journal of Electromagnetic Waves and Applications, Vol. 13, No. 1, pp. 121–136, 1999 A.K. Fung, W.Y. Liu, K.S. Chen, and M.K. Tsay, “An Improved IEM Model for Bistatic Scattering from Rough Surface,” Journal of Electromagnetic Waves and Applications, Vol. 16, No. 5, pp. 689–702, 2002
Modeling of the Sea Ice and Ice Shelf • The backscattering model developed by Ewe et al. was applied to sea ice and ice shelf. • Ground truth measurement was conducted at Ross Island, Antarctica to verify the model. • Satellite images were also acquired as part of the study.
Z θ θs Air Layer Air-Sea Ice Interface Sea ice Layer Sea Ice-Ocean Interface Ocean (Lower Half Space) • Backscattering model was initially tested for single layer – sea ice. • Model configuration: M.D. Albert, T.E. Tan, H.T. Ewe, and H.T. Chuah, “A theoretical and measurement study of sea ice and ice shelf in Antarctica as electrically dense media,” Journal of Electromagnetic Waves and Applications, Vol. 19, No. 14, pp. 1973–1981, 2005
Theoretical and Measured Backscattering Coefficient Sites A – P 0 –5 –10 –15 –20 –25 –30 –35 –40 Backscattering Coefficient (dB) Measured Theoretical A B C D E F G H I J K L M N O P Sites • Simulation results:
A multilayer model was developed to take into account the snow cover on the sea ice (Mohan et al.). • Extension of the backscatter model by Ewe et al. • Results show good matching between the multilayer model, Matrix Doubling method and CEAREX measurements. Y.J. Lee, H.J. Yap, M.D. Albert, H.T. Ewe, and H.T. Chuah, “Multiyear Field Measurement and Sensitivity Study of Radar Returns in Scott Base, Antarctica,” Proceedings for the 3rd Malaysian International Seminar on Antarctica (MISA3): From the Tropics to the Poles, Sabah, Malaysia, pp. 21–28, July 2007 M.D., Albert, H.T. Ewe, and H.T. Chuah, “Understanding the Scattering Mechanism in Sea Ice and Its Relation to Remote Sensing”, Joint Scientific Committee on Antarctic Research (SCAR)-International Arctic Science Committee (IASC) Open Science Conference, St Petersburg, Russia, 8–11 July 2008
Z Sea Ice θ θs Air-Snowinterface Snow layer Snow-Sea Ice interface Sea ice Sea Ice-Ocean interface Ocean (half space) • Model configuration:
Development of Inverse Scattering Models for Sea Ice Thickness Retrieval • Many inverse models were developed to retrieve sea ice thickness. • Based on existing models, new models utilizing the RT and DM-PACT were later developed. Golden, K.M., D. Borup, M. Cheney, E. Cherkaeva, M.S. Dawson, K.H. Ding, A.K. Fung, D. Isaacson, S.A. Johnson, A.K. Jordan, J.A. Kong, R. Kwok, S.V. Nghiem, R.G. Onstott, J. Sylvester, D.P. Winebrenner, and I.H.H. Zabel, “Inverse electromagnetic scattering models for sea ice”, IEEE Transactions on Geoscience and Remote Sensing, Vol. 36, No. 5, 1675–1704, 1998
For active remote sensing: • Radiative Transfer Inverse Scattering Model (RTISM) • For passive remote sensing: • Neural Network with RT-DMPACT • Genetic Algorithm with RT-DMPACT Y.J. Lee, W.K. Lim, and H.T. Ewe, “A Study Of An Inversion Model For Sea Ice Thickness Retrieval In Ross Island, Antarctica”, Progress in Electromagnetics Research (PIER), Vol. 111, pp. 381–406, 2011 H.J. Yap, W.K. Lim, H.T. Ewe and H.T. Chuah, “Passive Microwave Remote Sensing for Sea Ice Thickness Retrieval Using Neural Network and Genetic Algorithm”, Proceedings in Progress In Electromagnetics Research Symposium (PIERS), Beijing, China, pp. 1229–1233, 23–27 March 2009 H.J. Yap, W.K. Lim, H.T. Ewe and H.T. Chuah, “Neural Network and Genetic Algorithm Inversion for Sea Ice Thickness using Passive Microwave Remote Sensing”, 4th Malaysian International Seminar on Antarctica (MISA4): Legacy of IPY to the Tropics, Petaling Jaya, Malaysia. Poster presented. 1–3 April 2009
- Radiative Transfer Inverse Scattering Model (RTISM) • Flowchart for the Radiative Transfer Inverse Scattering Model (RTISM):
Sea ice thickness retrieval using the Radiative Transfer Inverse Scattering Model (RTISM):
- Neural Network with RT-DMPACT- Genetic Algorithm with RT-DMPACT • Flowchart for the Neural Network with RT-DMPACT:
Conclusion • Improvements to the phase matrix of the Radiative Transfer equation was done. • The technique, named the DM-PACT is able to better model the inhomogeneous media. • A backscattering model was later developed based on RT and DM-PACT. • Application of the study towards the remote sensing of sea ice was done. • The backscattering model was extended to a multilayer model. • Inverse models were later developed based on the backscattering model to retrieve sea ice thickness.