Preprints
https://doi.org/10.5194/tc-2022-8
https://doi.org/10.5194/tc-2022-8
 
25 Feb 2022
25 Feb 2022
Status: this preprint was under review for the journal TC. A revision for further review has not been submitted.

Visual Interpretation of Synthetic Aperture Radar Sea Ice Imagery by Expert and Novice Analysts: An Eye Tracking Study

Alexandru Gegiuc1, Juha Karvonen1, Jouni Vainio2, Eero Rinne1,3, Roman Bednarik4, and Marko Mäkynen1 Alexandru Gegiuc et al.
  • 1Finnish Meteorological Institute (FMI), Marine Research, Erik Palménin aukio 1, 00560 Helsinki, Finland
  • 2Finnish Meteorological Institute (FMI), Ice Service, Erik Palménin aukio 1, 00560 Helsinki, Finland
  • 3University Centre in Svalbard (UNIS), Arctic Geophysics, Longyearbyen, Norway
  • 4University of Eastern Finland (UEF), Joensuu, Finland

Abstract. We demonstrate the use of eye tracking methodology as a non-invasive way to identify elements behind uncertainties typically introduced during the process of sea ice charting using satellite synthetic aperture radar (SAR) imagery. To our knowledge, this is the first time eye tracking is used to study the interpretation of satellite SAR images over sea ice. We describe differences and similarities between expert and novice analysts while visually interpreting a set of SAR sea ice images.

In ice charting, SAR imagery serves as the base layer for mapping the sea ice conditions. Linking the backscatter signatures in the SAR imagery and the actual sea ice parameters is a complex task which requires highly trained experts. Mapping of sea ice types and parameters in the SAR imagery is therefore subject to an analyst's performance which may lead to inconsistencies between the ice charts. By measuring the fixation duration over different sea ice types we can identify the features in a SAR image that require more cognitive effort in classification, and thus are more prone to miss-classification. Ambiguities in classification were found especially for regions less restrictive for navigation, consisting of mixed sea ice properties and uneven thicknesses. We also show that the experts are able to correctly map large sea ice covered areas only by looking at the SAR images. Based on the eye movement data, ice categories with most of the surface covered by ice, i.e. in ice charts fast ice and very close ice, were easier to classify than areas with mixed ice thicknesses such as open ice or very open ice.

Alexandru Gegiuc et al.

Status: closed (peer review stopped)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on tc-2022-8', Anonymous Referee #1, 28 Mar 2022
    • AC1: 'Reply on RC1', Alexandru Gegiuc, 22 May 2022
  • RC2: 'Comment on tc-2022-8', Anonymous Referee #2, 19 Apr 2022
    • AC2: 'Reply on RC2', Alexandru Gegiuc, 22 May 2022

Status: closed (peer review stopped)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on tc-2022-8', Anonymous Referee #1, 28 Mar 2022
    • AC1: 'Reply on RC1', Alexandru Gegiuc, 22 May 2022
  • RC2: 'Comment on tc-2022-8', Anonymous Referee #2, 19 Apr 2022
    • AC2: 'Reply on RC2', Alexandru Gegiuc, 22 May 2022

Alexandru Gegiuc et al.

Alexandru Gegiuc et al.

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Short summary
Current users of operational ice charts call for quantitative uncertainty information, which the current ice charts lack. In this work we demonstrate for the first time the use of eye tracking methodology as a non-invasive way to identify elements behind uncertainties typically introduced during the process of visual mapping of sea ice information in satellite radar imagery. Uncertainty information would increase reliability of the manually produced ice charts and increase navigation safety.