Work package 2 – Sea Ice, Iceberg and Growler Remote Sensing

The objective of this work package is to further develop remote sensing methodologies and algorithms to enable detailed characterisation and mapping of Arctic sea ice conditions, and to provide improved detection and characterisation of icebergs and growlers. Within this WP CIRFA develops algorithms for:

  • Classification and characterisation of sea ice
  • Estimation of sea ice drift velocity field
  • Iceberg and growler detection and characterisation

SAR data will be the key data source in this WP as the signatures of radar backscatter from sea ice and ice objects, such as icebergs, are highly correlated with physical ice properties such as salinity, temperature, wetness, thickness, roughness and degree of deformation. Studies will focus on the analysis of polarimetric parameters and decomposition techniques, on tracking ice drift and variations of sea ice conditions, and on multivariate statistical properties and anomaly detection. An important aspect of this study is the use of multi-frequency radar data and their fusion with optical and IR instrument data for sea ice applications.

The methodologies, tools and products developed within WP2 will be integrated with the modelling activities of WP5 to produce information products for the pilot services of WP7.


WP2 members

Prof. Torbjørn Eltoft

Centre leader, UiT
+47 776 45184

Adjunct Prof. Wolfgang Dierking

WP2 leader, AWI/UiT
+49 471 4831 1714

Jack Christopher Landy


Satellite laser and radar altimetry to study the physical properties of polar sea ice and oceans

Laust Færch

PhD fellow, UiT

Mapping and Modeling of Iceberg Occurrences in the Barents Sea

Anna Telegina

PhD fellow, UiT

Multi-temporal remote sensing of dynamic Arctic phenomena

Wenkai Guo

Post Doc, UiT

Cross-platform application of a sea ice classification method for detecting deformed ice

Anca Cristea

Post Doc, NPI

Sea ice classification from multimodal remote sensing data

Polona Itkin


Sea ice deformation and its impact on the sea ice mass balance

Johannes Lohse

Post Doc, UiT
+47 776 45180

Automated Classification of Sea Ice Types in SAR Imagery

Saloua Chlaily

Post Doc, UiT

Automised Large-scale Sea Ice Characterisation and Mapping

Eduard Khachatrian

PhD Fellow

Multimodal Integrated Remote Sensing for Arctic Sea Ice monitoring

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