Optimal Compact Polarimetric Parameters and Texture Features for Discriminating Sea Ice Types during Winter and Advanced Melt
C-band synthetic aperture radar (SAR) is widely used for sea ice monitoring and operational activities. The RADARSAT Constellation Mission (RCM), with its anticipated launch in 2018, will provide hybrid compact polarimetric (CP) C-band SAR data offering near-polarimetric capabilities at large image...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2018-07-01
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| Series: | Canadian Journal of Remote Sensing |
| Online Access: | http://dx.doi.org/10.1080/07038992.2018.1527683 |
| _version_ | 1797661145108054016 |
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| author | Sasha Nasonova Randall K. Scharien Torsten Geldsetzer Stephen E. L. Howell Desmond Power |
| author_facet | Sasha Nasonova Randall K. Scharien Torsten Geldsetzer Stephen E. L. Howell Desmond Power |
| author_sort | Sasha Nasonova |
| collection | DOAJ |
| description | C-band synthetic aperture radar (SAR) is widely used for sea ice monitoring and operational activities. The RADARSAT Constellation Mission (RCM), with its anticipated launch in 2018, will provide hybrid compact polarimetric (CP) C-band SAR data offering near-polarimetric capabilities at large image acquisition widths suitable for achieving operational and scientific objectives in the Arctic. Although C-band SAR is effective for sea ice monitoring, it is difficult to implement during advanced melt, when the sea ice cover is melting and covered by melt ponds. Ice type separability during winter (pre-melt) and advanced melt conditions was assessed using Kolmogorov–Smirnov statistical separability analyses and Support Vector Machine supervised classifications of RCM parameters simulated from 2 winter and 2 advanced melt RADARSAT-2 scenes. Through a detailed analysis of the 2 advanced melt scenes, it was found that the steep incidence angle (22.3–24.2°) simulated RCM CP parameters provide improved ice type separability during the advanced melt period compared with shallow incidence angles (39.6–42.2°). With respect to classification, an overall accuracy of 77.06% was found for a scene comprising first-year and multiyear ice types, and a higher overall accuracy of 85.91% was achieved by including gray level co-occurrence matrix parameters in the classification. |
| first_indexed | 2024-03-11T18:41:14Z |
| format | Article |
| id | doaj.art-cd3133b6530041ec9f9c6a65cf2d0351 |
| institution | Directory Open Access Journal |
| issn | 1712-7971 |
| language | English |
| last_indexed | 2024-03-11T18:41:14Z |
| publishDate | 2018-07-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Canadian Journal of Remote Sensing |
| spelling | doaj.art-cd3133b6530041ec9f9c6a65cf2d03512023-10-12T13:36:22ZengTaylor & Francis GroupCanadian Journal of Remote Sensing1712-79712018-07-0144439041110.1080/07038992.2018.15276831527683Optimal Compact Polarimetric Parameters and Texture Features for Discriminating Sea Ice Types during Winter and Advanced MeltSasha Nasonova0Randall K. Scharien1Torsten Geldsetzer2Stephen E. L. Howell3Desmond Power4University of VictoriaUniversity of VictoriaUniversity of VictoriaEnvironment and Climate Change CanadaC-CoreC-band synthetic aperture radar (SAR) is widely used for sea ice monitoring and operational activities. The RADARSAT Constellation Mission (RCM), with its anticipated launch in 2018, will provide hybrid compact polarimetric (CP) C-band SAR data offering near-polarimetric capabilities at large image acquisition widths suitable for achieving operational and scientific objectives in the Arctic. Although C-band SAR is effective for sea ice monitoring, it is difficult to implement during advanced melt, when the sea ice cover is melting and covered by melt ponds. Ice type separability during winter (pre-melt) and advanced melt conditions was assessed using Kolmogorov–Smirnov statistical separability analyses and Support Vector Machine supervised classifications of RCM parameters simulated from 2 winter and 2 advanced melt RADARSAT-2 scenes. Through a detailed analysis of the 2 advanced melt scenes, it was found that the steep incidence angle (22.3–24.2°) simulated RCM CP parameters provide improved ice type separability during the advanced melt period compared with shallow incidence angles (39.6–42.2°). With respect to classification, an overall accuracy of 77.06% was found for a scene comprising first-year and multiyear ice types, and a higher overall accuracy of 85.91% was achieved by including gray level co-occurrence matrix parameters in the classification.http://dx.doi.org/10.1080/07038992.2018.1527683 |
| spellingShingle | Sasha Nasonova Randall K. Scharien Torsten Geldsetzer Stephen E. L. Howell Desmond Power Optimal Compact Polarimetric Parameters and Texture Features for Discriminating Sea Ice Types during Winter and Advanced Melt Canadian Journal of Remote Sensing |
| title | Optimal Compact Polarimetric Parameters and Texture Features for Discriminating Sea Ice Types during Winter and Advanced Melt |
| title_full | Optimal Compact Polarimetric Parameters and Texture Features for Discriminating Sea Ice Types during Winter and Advanced Melt |
| title_fullStr | Optimal Compact Polarimetric Parameters and Texture Features for Discriminating Sea Ice Types during Winter and Advanced Melt |
| title_full_unstemmed | Optimal Compact Polarimetric Parameters and Texture Features for Discriminating Sea Ice Types during Winter and Advanced Melt |
| title_short | Optimal Compact Polarimetric Parameters and Texture Features for Discriminating Sea Ice Types during Winter and Advanced Melt |
| title_sort | optimal compact polarimetric parameters and texture features for discriminating sea ice types during winter and advanced melt |
| url | http://dx.doi.org/10.1080/07038992.2018.1527683 |
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