WP2: Monitoring Sea Ice and Icebergs

Icon Sea ice and icebergs

The decrease of sea ice extent and thickness in the Arctic over the last decades, especially during summer months, is closely linked to climate change. The expectation of an easier access to Arctic regions has triggered considerations concerning the expansion of marine transport and the possibilities to exploit natural resources in the Arctic Ocean. Hence, satellite monitoring of the Arctic sea ice and icebergs is inevitable for evaluations of chances and risks.

At CIRFA we develop methods for information retrieval from satellite images which are tested by the Norwegian Ice Service to complement manual analysis of the images. Together, we are working towards a 24/7 automatic sea ice forecasting for the ocean and the Norwegian fjords.

Safe navigation in polar regions requires timely and accurate information about the presence and characteristics of sea ice and the occurrence of icebergs.
Image credit: Alex Perz / Unsplash
Field photography of icebergs for improving and validating methods for iceberg detection in satellite images. Image credit: William Copeland.
Researchers at CIRFA and MET are developing new ways to classify and map sea ice, and make their results available to ship captains and crews for navigation through challenging sea ice conditions. Image credit: CIRFA.

We develop and improve remote sensing methodologies and algorithms to automatically map Arctic sea-ice conditions, and provide enhanced methods for detecting icebergs. Besides synthetic aperture radar (SAR) as key data source, we also use optical and thermal satellite images, passive microwave and altimeter data.

Our studies focus on semi- and fully automated sea ice classification, retrieval of sea ice drift and deformation, observing temporal and spatial variations of sea ice conditions, and on finding optimal algorithms and radar configurations for monitoring icebergs.

The methods used include multivariate statistical analysis, anomaly detection, constant false alarm rate (CFAR) approaches, and machine learning/deep learning techniques. For validation, we use data from field measurements and generate a data base of SAR and optical images acquired over sea ice and icebergs at different seasons and meteorological conditions.

Research tasks

Development and improvement of (semi-)automated algorithms for sea ice type classification suitable for operational applications

Integration of data from new field measurement techniques (e.g. drones) into algorithm development

Retrieval and modelling of ice drift and deformation for short-term forecasting of ice conditions

Comparison and improvement of algorithms for detecting icebergs in open water and in sea ice

Team members

Wolfgang Dierking

Professor II and WP 2 leader, AWI/UiT


Professor II and WP 2 leader

Anthony Doulgeris

Professor, UiT


Employer page at UiT

WP 2 co-leader and leader of UiT`s Earth Observation group

Torbjørn Eltoft

Professor and Center Leader UiT


Remote Sensing, Signal Processing, Image Processing, Neural Networks

Jack Landy

Associate Professor


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

Truls Karlsen

PhD candidate, UiT


Multi-frequency (C- and L-band) SAR sea ice classification

Qiang Wang

Post Doc, UiT


Sea ice classification with AI methods

Debanshu Ratha

Post Doc, UiT


Radar polarimetry for sea ice applications

Eduard Khachatrian

PhD candidate, UiT


Multimodal Integrated Remote Sensing for Arctic Sea Ice monitoring

Johannes Lohse

Researcher, UiT


Automated Classification of Sea Ice Types in SAR Imagery

Polona Itkin

Researcher, UiT


Sea ice deformation and its impact on the sea ice mass balance, SiDRIFT project

Anca Cristea

Post Doc, NPI



Sea ice classification from multimodal remote sensing data

Wenkai Guo

Post Doc, UiT


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

Anna Telegina

PhD candidate, UiT


Multi-temporal remote sensing of dynamic Arctic phenomena

Laust Færch

PhD candidate, UiT


Mapping and Modeling of Iceberg Occurrences in the Barents Sea

Andrea Marinoni

Associate Professor, UiT

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