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RELIABILITY MEASURES FOR SEA ICE MOTION RETRIEVAL FROM
SYNTHETIC APERTURE RADAR IMAGES
ABSTRACT
Sea ice motion is triggered by wind and ocean currents.Its magnitude and direction can
be automatically retrievedusing pairs of satellite images acquired over the same area.However,
external reference data for validation of drift retrievals,such as tracks from buoys, are sparse.
Information about thereliability of the retrieved ice drift field is crucial for applicationssuch as
operational sea ice mapping or validation of computermodels for simulations of sea ice
dynamics. In this paper, weintroduce an intrinsic measure based on the properties of radarimage
pairs to assess the reliability of the retrieved ice driftvectors. The proposed method combines
different parameters,e.g., correlation coefficient and two textural quantities, to
provideinformation about the suitability of sub image regions for pattern matching. In this way,
we generate a quality parameter [calledconfidence factor (CFA)] for the calculated ice drift
velocities. TheCFA is compared to results obtained by “back matching.” Thelatter requires that
the drift field is computed twice usingthe image pair, first in sequential and then in reversed
order.For stable ice conditions, the results show that areas regardedas unreliable by the CFA
compare well with the areas revealing larger differences from back matching.

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  • 1. RELIABILITY MEASURES FOR SEA ICE MOTION RETRIEVAL FROM SYNTHETIC APERTURE RADAR IMAGES ABSTRACT Sea ice motion is triggered by wind and ocean currents.Its magnitude and direction can be automatically retrievedusing pairs of satellite images acquired over the same area.However, external reference data for validation of drift retrievals,such as tracks from buoys, are sparse. Information about thereliability of the retrieved ice drift field is crucial for applicationssuch as operational sea ice mapping or validation of computermodels for simulations of sea ice dynamics. In this paper, weintroduce an intrinsic measure based on the properties of radarimage pairs to assess the reliability of the retrieved ice driftvectors. The proposed method combines different parameters,e.g., correlation coefficient and two textural quantities, to provideinformation about the suitability of sub image regions for pattern matching. In this way, we generate a quality parameter [calledconfidence factor (CFA)] for the calculated ice drift velocities. TheCFA is compared to results obtained by “back matching.” Thelatter requires that the drift field is computed twice usingthe image pair, first in sequential and then in reversed order.For stable ice conditions, the results show that areas regardedas unreliable by the CFA compare well with the areas revealing larger differences from back matching.