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Extraction of Antarctic Ice Features Using Hybrid Polarimetric RISAT-1 SAR Data
Compact polarimetry has gained popularity due to its advantages, such as larger swath, simple architecture and low power consumption. The backscattered signal and scattering decomposition vary for different targets based on their electrical, geometrical and structural properties. As of now, the potential of hybrid polarimetric synthetic aperture radar (SAR) data for exploring Antarctic ice features is not fully explored. Here, we present a comprehensive polarimetric feature analysis and classification results of the hybrid polarimetric dataset acquired by RISAT-1 near the Indian Antarctic research station Maitri. The single-look complex images have been subjected to polarimetric data processing for extracting Antarctic ice features using POLSARPRO software. The polarimetric coherence matrix is generated and then filtered to eliminate speckles. Raney m–χ decomposition technique has been utilized to understand the scattering mechanism of the targets. The decomposed RGB image is classified using Wishart-supervised classification, and classification accuracy is assessed using a confusion matrix. It is found that the comparatively simple hybrid polarimetric SAR provides sufficient information to detect and discriminate various Antarctic ice features. Features such as rifts, ice–rises, ice shelves and icebergs are clearly discriminated using Wishart-supervised classification. It is also found that the overall accuracy of the classification of study areas varies between 80% and 97%, suggesting a good classification outcome.
Keywords
Classification Accuracy, Confusion Matrix, Hybrid Polarimetry, Ice Features, m–χ Decomposition, Synthetic Aperture Radar Data.
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- Clausi, D. A. and Deng, H., Operational segmentation and classification of SAR sea ice imagery. In Proceedings of IEEE Workshop on Advances in Techniques for Analysis of Remotely Sensed Data, Greenbelt, MD, USA, 2003, pp. 268–275.
- Moen, M. A., Doulgeris, A. P., Anfinsen, S. N., Renner, A. H., Hughes, N., Gerland, S. and Eltoft, T., Comparison of feature based segmentation of full polarimetric SAR satellite sea ice images with manually drawn ice charts. Cryosphere, 2013, 7, 1693–1705.
- Denbina, M. and Collins, M. J., Iceberg detection using simulated dual-polarized Radarsat constellation data. Can. J. Remote Sensing, 2014, 40, 165–178.
- Dabboor, M. and Geldsetzer, T., On the classification of sea ice types using simulated Radarsat Constellation Mission (RCM) compact polarimetric SAR parameters. In Proceedings of the ASPRS 2014 Annual Conference, Louisville, Kentucky, USA, 2014, pp. 23–28.
- Dabboor, M., Montpetit, B. and Howell, S., Assessment of the high resolution SAR mode of the RADARSAT Constellation Mission for first year ice and multiyear ice characterization. Remote Sensing, 2018, 10, 594.
- Misra, T., Rana, S. S., Desai, N. M., Dave, D. B., Rajeevjyoti, Arora, R. K. and Vachchani, J. G., Synthetic aperture radar payload on-board RISAT-1: configuration, technology and performance. Curr. Sci., 2013, 104, 446–461.
- Boerner, W. M., Basic concepts in radar polarimetry (on-line); available at http://envisat.esa.int/polsarpro/Manuals/LN_Basic_Concepts.pdf
- Tomar, K. S., Hybrid polarimetric decomposition for aboveground biomass estimation using semi-empirical modelling. MS thesis submitted to the University of Twente, The Netherlands, 2015, p. 70.
- Sabry, R. and Vachon, P. W., Advanced polarimetric synthetic aperture radar (SAR) and electro-optical (EO) data fusion through unified coherent formulation of the scattered EM field. Prog. Electromagn. Res., 2008, 84, 189–203.
- Woodhouse, I. H., Introduction to Microwave Remote Sensing, CRC Press, FL, Boca Raton, USA 2006, p. 370.
- Raney, R. K., Synthetic aperture radar hybrid-quadrature-polarity method and architecture for obtaining the stokes parameters of radar backscatter. US Patent 8,258,996, 2012.
- Lee, J. S., Grunes, M. R. and De Grandi, G., Polarimetric SAR speckle filtering and its implication for classification. IEEE Trans. Geosci. Remote Sensing, 1999, 37,2363–2373.
- Farage, G., Foucher, S. and Benie, G., Comparison of PolSAR speckle filtering techniques. In Proceedings of 2006 IEEE International Symposium on Geoscience and Remote Sensing, Denver, CO, USA, 2006, pp. 1760–1763.
- Raney, R. K., Cahill, J. T., Patterson, G. W. and Bussey, D. B. J., The m–chi decomposition of hybrid dual-polarimetric radar data with application to lunar craters. J. Geophys. Res. Planets, 2012, 117, 8.
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