Late summer sea ice segmentation with multi-polarisation SAR features in C- and X-band

Published version. Source at http://doi.org/10.5194/tcd-9-4539-2015 . In this study we investigate the potential of sea ice segmentation by C- and X-band multi-polarisation synthetic aperture radar (SAR) features during late summer. Five high-resolution satellite SAR scenes were recorded in the Fram...

Full description

Bibliographic Details
Main Authors: Fors, Ane Schwenke, Brekke, Camilla, Doulgeris, Anthony Paul, Eltoft, Torbjørn, Renner, Angelika, Gerland, Sebastian
Format: Article in Journal/Newspaper
Language:English
Published: The European Geosciences Union 2015
Subjects:
Online Access:https://hdl.handle.net/10037/9073
https://doi.org/10.5194/tcd-9-4539-2015
Description
Summary:Published version. Source at http://doi.org/10.5194/tcd-9-4539-2015 . In this study we investigate the potential of sea ice segmentation by C- and X-band multi-polarisation synthetic aperture radar (SAR) features during late summer. Five high-resolution satellite SAR scenes were recorded in the Fram Strait covering iceberg- fast first-year and old sea ice during a week with air temperatures varying around zero degrees Celsius. In situ data consisting of sea ice thickness, surface roughness and aerial photographs were collected during a helicopter flight at the site. Six polarimetric SAR features were extracted for each of the scenes. The ability of the individual SAR features to discriminate between sea ice types and their temporally consistency were examined. All SAR features were found to add value to sea ice type discrimination. Relative kurtosis, geometric brightness, cross-polarisation ratio and co-polarisation correlation angle were found to be temporally consistent in the investigated period, while co-polarisation ratio and co-polarisation correlation magnitude were found to be temporally inconsistent. An automatic feature-based segmentation algorithm was tested both for a full SAR feature set, and for a reduced SAR feature set limited to temporally consistent features. In general, the algorithm produces a good late summer sea ice segmentation. Excluding temporally inconsistent SAR features improved the segmentation at air temperatures above zero degrees Celsius.