Sea ice classification of TerraSAR-X ScanSAR images for the MOSAiC expedition incorporating per-class incidence angle dependency of image texture

Guo, Wenkai; Itkin, Polona; Singha, Suman; Doulgeris, Anthony P.; Johansson, Malin; Spreen, Gunnar

doi:https://doi.org/10.5194/tc-17-1279-2023

Articles | Volume 17, issue 3

https://doi.org/10.5194/tc-17-1279-2023

© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/tc-17-1279-2023

© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 17, issue 3

Research article

|

16 Mar 2023

Research article |

| 16 Mar 2023

Sea ice classification of TerraSAR-X ScanSAR images for the MOSAiC expedition incorporating per-class incidence angle dependency of image texture

Wenkai Guo, Polona Itkin, Suman Singha, Anthony P. Doulgeris, Malin Johansson, and Gunnar Spreen

Data sets

The Sea ice type product of the EUMETSAT Ocean and Sea Ice Satellite Application Facility (OSI SAF) OSI SAF https://osi-saf.eumetsat.int/products/osi-403-d

MODIS/Terra Sea Ice Extent 5-Min L2 Swath 1km, Version 61 D. K. Hall and G. A. Riggs https://doi.org/10.5067/MODIS/MOD29.061

Short summary

Sea ice maps are produced to cover the MOSAiC Arctic expedition (2019–2020) and divide sea ice into scientifically meaningful classes. We use a high-resolution X-band synthetic aperture radar dataset and show how image brightness and texture systematically vary across the images. We use an algorithm that reliably corrects this effect and achieve good results, as evaluated by comparisons to ground observations and other studies. The sea ice maps are useful as a basis for future MOSAiC studies.