Malin Johansson  –  Associate Professor

Anthony Paul Doulgeris  –  Professor

Jack Christopher Landy  –  Associate Professor

Vishnu Nandan  –  Associate Professor

Torbjørn Eltoft  –  Emeriti

Cathleen Jones

Wolfgang Fritz Otto Dierking  –  Professor

Johannes Lohse  –  Researcher

Morven Korneel Muilwijk  –  Associate Professor

Anne Braakmann-Folgmann  –  Postdoctoral Fellow

Wenkai Guo  –  Researcher

Robbie David Christopher Mallett  –  Postdoctoral Fellow

Isolde Glissenaar  –  Postdoctoral Fellow

Aliette Chenal  –  Postdoctoral Fellow

Marek Elijah Lio Muchow  –  Postdoctoral Fellow

Kai-Uwe Eiselt  –  Researcher

Truls Karlsen  –  Doctoral Research Fellow

Catherine Cecilia A Taelman  –  Doctoral Research Fellow

Madeleine Cecilia Östersund  –  Doctoral Research Fellow

Jakub Petříček  –  Doctoral Research Fellow

Francisco Amor  –  Doctoral Research Fellow

Loris Cedric Danjou  –  Doctoral Research Fellow

Lia Lechler  –  Doctoral Research Fellow

ARKTALAS 2

2024-2026

The Arctic is a complex region, encompassing different physical and biogeochemical processes and interactions among several components of the Earth system. Changes in the Arctic have a strong impact on the Earth's climate system, the global energy budget, the ocean circulation, the water cycle, gas exchanges, sea level, and biodiversity. Within the ESA ARKTALAS projects we’ll adapt existing NERSC sea ice motion algorithms to include both SAR and passive microwave data. Detection of waves in sea ice will be analysed using SAR data and couple it to in-situ data measurements. With one of the goals being to demonstrate the potential of sea ice drift and waves for science and operational use.

Funds: ESA
Web: NERSC project page
Host: The Nansen Center
PI: Johnny Johannesen (NERSC)
     Malin Johansson (UiT)

Arctic Extreme (ARCTEX)

2024-2026

Arctic climate change is making what was previously extreme more common, and what was previously impossible a reality. The Arctic's sea and land ice are tightly coupled together, and understanding this extreme behaviour requires a cross-disciplinary effort. ARCTEX (Arctic Extremes) brings together experts in sea ice and land-ice to study the drivers and effects of extreme events in the Arctic using state-of-the-art tools and data. The project has a particular focus on the balance of glacial melt and accumulation in years of exceptionally poor sea ice cover, and the power of icebergs in fjord systems to hold back the sliding of marine-terminating glaciers. This analysis uses a wide range of satellite technologies such as spaceborne radiometers, altimeters, and radar imaging systems.

Funds: ESA
Web: DTU project page
Host: DTU, Denmark
PI: Louise Sandberg Sørensen (DTU), Robbie Mallett (UiT)

HIgh Resolution LOcal sea ice MAPping (HIRLOMAP)

2024-2026

HIRLOMAP will work towards upcoming missions such as Sentinel Next Generation, and ESA’s Expansion Missions. In the development stage will different image processing and information retrieval methods be used, to test out the products on data from ESA’s Sentinel missions, as well as missions from JAXA and NASA such as ALOS-2/-4 and NISAR. The main objectives are (1) to provide local information products on scales of tens of kilometers with the highest possible spatial resolution between a few tens of meters and 5 meters which are required for special operations and applications such as listed below, and (2) to achieve higher accuracies in detection, classification, and parameter retrievals for Arctic sea ice and iceberg information product generation.

Funds: ESA

Web:  UiT Project page
Host: UiT The Arctic University of Norway
PI: Malin Johansson

Ice, Wind, Structures (Ice-wise)

2024-2028

IceWise deals with the effects of sea ice on offshore wind turbines. Europe aims to develop at least 60 GW of offshore wind in EU waters by 2030, making it one of the most important renewable energy sources for the future. This implies the installation of additional wind turbines in the Baltic Sea, where sea ice is one of the main unknowns. To reduce uncertainty in ice action estimations, improve operational planning, and standardize the design process for offshore wind turbines, IceWise combines the expertise of NTNU in ice mechanics and ice actions on offshore structures with the expertise of UiT in satellite remote sensing of sea ice. This will enable Norwegian industry to conduct world-class research.

Funds: ENERGIX-Stort program energi
Web: NFR research page
Host: UiT The Arctic University of Norway
PI: Professor Knut Vilhelm Høyland

air-snow-ice-ocean INTERactions transforming Atlantic Arctic Climate (INTERAAC)

2020-2026

The INTERAAC project assembles a complimentary team of experts from China and Norway to generate a reconciled multi-mission Climate Data Record (CDR) of sea ice properties in the Atlantic Arctic. By integrating SAR, altimetry, and field observations, we will target the inter-mission biases currently preventing detection of climate-relevant trends. Our new data will enable the investigation of coupled air-snow-ice-ocean processes driving sea ice retreat along the Atlantic Polar Front.

Funds: NFR-POLARPROG
Web: NFR research page
Host: UiT The Arctic University of Norway
PI: Jack Landy

CryoSat Thematic Products (CryoTEMPO) Summer Sea Ice

2021-2026

The Cryo-TEMPO study aims to deliver a new paradigm of simplified, harmonized, and agile CryoSat-2 products, that are easily accessible to new communities of non-altimeter experts and end-users. The project will generate six new thematic along-track products, covering Winter Sea Ice, Summer Sea Ice, Land Ice, Polar Ocean, Coastal Ocean and Inland Water, using rapidly evolving, state-of-the-art processing dedicated to each thematic area.

Funds: ESA
Web: project page
Host: Lancaster University, UK
PI: Jack Landy

Arctic Summer Sea Ice in 3D (SI/3D)

2023-2028

SI/3D will close the gap in summer sea ice thickness observations from radar altimetry, harnessing deep machine learning, modelling of the radar altimeter response, and dedicated field campaigns, to overcome the processing barriers. With this unique dataset, we will: (1) close the Arctic sea ice volume budget, pinpointing the mechanisms driving seasonal decay and breakup of the ice pack and the feedbacks of sea ice loss on Arctic temperatures, and (2) upgrade seasonal sea ice forecasts from state-of-the-art modelling systems by assimilating summer ice thickness observations.

Funds: ERC Starting Grant
Web: EU research page
Host: UiT The Arctic University of Norway
PI: Jack Landy

Antarctic Landfast Sea Ice with Satellite Observations

Antarctic sea ice plays a vital role in the climate of the Southern Ocean region and significantly impacts the global climate system. After decades of relative stability, the recent record lows in sea ice extent highlight the need for a better understanding of changes in thickness and their drivers.

This MSc project offers the opportunity to explore landfast sea ice — a coastal zone of stationary sea ice anchored to the shoreline or ice shelves — using multiple satellite-based sensors. Despite its importance, current observations and products poorly capture its thickness and variability. Improving the representation of landfast sea ice in thickness datasets is essential for making reliable estimates of the Antarctic sea ice mass balance, particularly in the context of initiatives such as SO-SIMBA (Southern Ocean Sea Ice Mass Balance Assessment). The project will assess the ability of altimetry-based sea ice thickness products to represent the spatial and temporal evolution of the landfast ice region[RR1] [MB2] . To achieve this, you will use radar and laser altimetry sea ice thickness [RR3] [MB4]  and freeboard datasets, as well as landfast ice mask products, and also explore SAR (Sentinel-1) and optical (MODIS, Sentinel-2) data. You will also assist in preparing for the next generation of altimeters.

Literature:

• Fraser, A. D., Wongpan, P., Langhorne, P. J., Klekociuk, A. R., Kusahara, K., Lannuzel, D., et al. (2023). Antarctic landfast sea ice: A review of its physics, biogeochemistry and ecology. Reviews of Geophysics, 61, e2022RG000770. https://doi.org/10.1029/2022RG000770
• Fraser, A. D., Massom, R. A., Handcock, M. S., Reid, P., Ohshima, K. I., Raphael, M. N., Cartwright, J., Klekociuk, A. R., Wang, Z., and Porter-Smith, R.: Eighteen-year record of circum-Antarctic landfast-sea-ice distribution allows detailed baseline characterisation and reveals trends and variability, The Cryosphere, 15, 5061–5077, https://doi.org/10.5194/tc-15-5061-2021, 2021.

Contacts : Marion Bocquet (mabo@norceresearch.no), Robert Ricker (rori@norceresearch.no)

SO-SIMBA project: https://so-simba.github.io

Summer sea ice density from multi-sensor airborne data

One of the largest outstanding uncertainties in state-of-the-art polar sea ice thickness datasets is the sea ice density. Satellite altimeters measure the ice freeboard, which must be converted to the ice thickness with an assumption about the ice density. So far, these assumptions have been ultra-simple, with a single ice density assumed for different sea ice types.

In this project we will work with the Alfred Wegener Institute (AWI) who have collected multi-sensor airborne datasets on their IceBird campaigns in the Arctic to estimate the sea ice density and re-evaluate the assumptions made for satellite ice thickness products. This has been tested for data in winter by Jultila et al (2022)  https://tc.copernicus.org/articles/16/259/2022/ but here we will use data from the laser scanner and "EM-bird" to produce unique measurements of sea ice density in the Arctic summer. 

Contact: Jack Landy (jack.c.landy@uit.no)

Ice berg detection using SAR

Primary Objective: To compare very high-resolution commercial SAR data with Copernicus Sentinel-1 data to determine the minimum viable iceberg size detectable with Sentinel-1.

SAR polarimetric sea ice evolution during the CIRFA 2022 cruise

In April – May 2022 CIRFA conducted a cruise to the Belgica bank area. During this cruise, in-situ data was collected to confirm sea ice types and other sea and snow surface parameters that we can observe in the satellite images. Sensors were installed on the sea ice to keep recording temperature data even after the cruise. Regular fully-polarimetric C- and L-band SAR images were collected over this area until the end of June.

Pauli images from April 11 (before the cruise), May 4 (under the cruise), and June 18 (after the cruise). The images cover in part the same area.

The data set in this project consists of primarily 11 Radarsat-2 scenes collected over fast ice in the western Fram Strait in the period April 11th to June 18th, 2022. The scenes cover several types of snow-covered sea ice areas, including level first-year ice, deformed multi-year ice, and thin young lead ice. In the first part of the time period, the area had cold winter conditions, with dry snow cover. The temperatures gradually increased through the last part of May, and towards the end of the data collection, the site area experienced warm temperatures and melting conditions. As can be seen, different ice surfaces undergo different changes, which we think are correlated to the physical structure of the surfaces.

Within this project the backscatter evolution as well as the evolution of polarimetric features from the winter season until the melt season will be investigated. The effect of the onset of melt season on different sea ice types, such as smooth and deformed, will be analyzed and if possible, connected to scattering models.

Contact: Malin Johansson (malin.johansson@uit.no)

Tracking the seasonal evolution of radar backscatter signatures from different sea ice types

Synthetic aperture radar (SAR) is the main tool for operational sea ice monitoring. Due to its all-day and all-weather imaging capability, SAR instruments can reliably provide images throughout the entire year. The radar signal that is backscattered from the sea ice and snow surface is controlled by both surface and radar parameters. The most important radar parameters are frequency, polarization, and incident angle (IA), the dominant surface parameters include small-scale roughness (on the scale of mm to dm), large-scale roughness (deformation on the scale of dm to m), and the electric properties of the ice and snow. 

For a given sea ice type, such as for example level first-year ice (FYI) or deformed multi-year ice (MYI), variations in IA and changes in the overlying snowpack during melt onset can cause large variations in the radar backscatter. In the past, these variations have mostly been investigated for stationary landfast ice. In this master project, you will study the effect of IA and seasonal changes on drifting sea ice. 

During the CIRFA-22 cruise in April and May 2022, we deployed 17 drift buoys (drifters) on the sea ice close to Greenland. The drifters sampled GPS position every 30 minutes, resulting in the drift trajectories shown in the left figure. These trajectories enable us to identify and track individual sea ice floes in a time series of overlapping Sentinel-1 SAR images and track their backscatter signature over the course of several weeks and months. The figure on the right shows an example result of HH and HV intensity time series from a MYI and an FYI floe, indicating the manually identified timing of melt onset. In this master thesis, you will use the drifter data and overlapping Sentinel-1 imagery to expand the amount of tracked ice floes, and you will identify additional ice types in the imagery and include them in the study. You will then calculate the statistical separability of the different ice types and use this to assess the results of an automated ice type classification algorithm. Finally, you will extract backscatter signature time series over the landfast ice on the Greenland coast and investigate the differences and similarities in the evolution of drift ice and landfast ice backscatter. Depending on your initial findings, progress, and personal interest, there is also the option to work on retraining the classifier to enhance its performance during the melt season. 

During this project, you will learn about sea ice types, drift, and classification, and you will gain experience in SAR image processing and interpretation. The work is directly related to several ongoing projects in the Earth Observation group, and you will have a chance to closely work with our PhD students or post-docs. 

Left: Trajectories of drifters deployed on the sea ice during the CIRFA-22 cruise in April and May 2022 (map by C. Taelman). Photograph of a drifter after its deployment in the top left corner. Right: Time series of IA-corrected backscatter from example MYI and FYI floes (from Taelman et al., 2023).

Contact: Catherine Taelman (catherine.c.taelman@uit.no) 

Literature: 

• Taelman, C., Lohse, J., Doulgeris, A.P., Johansson, M. (2023). From winter to melt season: C-band radar backscatter evolution of fast-drifting sea ice floes. Poster presentation at IGS 2023. 10.13140/RG.2.2.11564.44164 
• Lohse, J., Doulgeris, A.P., Dierking, W. (2020). Mapping sea-ice types from Sentinel-1 considering the surface-type dependent effect of incidence angle. Annals of Glaciology, 61(83), 260-270. https://doi.org/10.1017/aog.2020.45 
• Geldsetzer T., Howell, S. (2023). Incidence angle dependencies for C-band backscatter from sea ice during both the winter and melt season. IEEE Transactions on Geoscience and Remote Sensing. 10.1109/TGRS.2023.3315056 

Relevant courses

The following courses cover Earth observation and satellite remote sensing, and are lectured by the staff of the Earth Observation Laboratory. 

FYS-3001 Physics of Remote Sensing – 10 ECTS credits
FYS-3023 Applied Remote Sensing – 10 ECTS credits

The following Bachelor and Master level courses are highly relevant to our research activities, to the master projects offered, and are recommended to those who want to work with us:

FYS-2006 Signal processing – 10 ECTS credits
FYS-2010 Image analysis – 10 ECTS credits

FYS-3012 Pattern recognition – 10 ECTS credits
STA-3001 Computer-intensive statistics – 10 ECTS credits
STA-3002 Multivariable statistical analysis – 10 ECTS credits

Note that courses are given both as master level courses and Ph.D. level courses, distinguished by the course code (e.g., Fys-3xxx vs. Fys-8xxx). They are lectured together, but there might be differences in the curriculum and course requirements.

Internships

Several students have visited the Earth Observation group as interns for a few weeks or months. If you are interested in doing an internship with us, please get in touch with one of our staff members.

Examples of completed internship projects:

• 2025 – Thomas Thebault
  Application of the Radar Statistical Reconnaissance (RSR) method for understanding the coherence of nadir Ku-/Ka-band radar backscatter from Arctic sea ice 

• 2024 – Marion Dugué
  Radar terrain angle correction for glacier facies classification 
• 2024 – Clara Vydra
  Evaluation of SnowModelLG during summer 

• 2023 – Clément Stouls
  Creation of an interface that enables to easily build, deploy and run a modular workflow for remote sensing image analysis, based on the Airflow framework

• 2023 – Cora Hoppe
  Sea ice type separation using S- and L-band Synthetic Aperture Radar (SAR) - A NISAR pre-study 

• 2020 – Catherine Taelman
  Deep spectral clustering for feature selection in multimodal remote sensing data 

Previous masters projects

The section Master Thesis Proposals gives an overview of master projects currenlty offered in the Earth Observation group. Below is a list of some of the projects done in the past. 

• 2025 – Anna Odh Antarctic ice shelf response to ocean tides and atmospheric pressure variations using satellite interferometry
• 2025 – Johanna Mankova Buseth Exploring methane detection with Sentinel-2 data: capabilities for monitoring landfill emissions
• 2023 – Sander Hindenes Natural occuring oil seepages as a consequence of bottom trawling?
• 2022 – Silje Birgitte Segrem Grue Machine learning for classifying marine vegetation from hyperspectral drone data in the Norwegian coast
• 2021 – Truls Karlsen Measuring velocities of a surge type glacier with SAR interferometry using ALOS-2 data
  
• 2021 – Tora Båtvik Detection of marine plastic debris in the North Pacific Ocean using optical satellite imagery
  
• 2020 – Jarle Pedersen Automatic validation of Sentinel-1 borne snow avalanche detections

PhD fellowships

Vacant PhD positions in the Earth Observation group are advertised on Jobbnorge.