The Earth Observation (EO) Group is a research unit within the Department of Physics and Technology at UiT The Arctic University of Norway. We work in the field of satellite, airborne and drone remote sensing applied to Earth observation. Our focus is on the development of new techniques for processing EO data, including algorithm design, image analysis tools, advanced statistics, pattern recognition and signal processing. These methods are applied to synthetic aperture radar (SAR) imagery, SAR and laser altimetry, and optical remote sensing instruments, with science objectives mainly focused on the Arctic Ocean and other Norwegian priority areas.
The EO Group is host to several externally-funded research projects focused on the remote sensing of sea ice properties (ice types, thickness, roughness) and ocean applications (waves in ice, oil spills) in the Arctic. These projects aim to improve our understanding of important geophysical processes, support better monitoring capabilities, and upgrade forecasting in the Arctic.
We offer a selection of interesting Master's projects in Earth observation.
All vacant positions in the EO group, including PhD projects, are advertised on Jobbnorge.
The Earth Observation Laboratory is involved in a wide range of projects covering the entire spectrum from basic to applied research. Here is a selection of some of the current larger projects.
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)
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)
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
Host: UiT The Arctic University of Norway
PI: Malin Johansson
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
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
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
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
Past projects
The EO-group offers several thesis projects for both students of the fully integrated master's program (30sp) and the 2-year master's program in Physics (60sp). Thesis projects are supervised by our staff members and are directly related to the work we are doing in the group. We gladly welcome student suggestions for projects in any topic related to earth observation. Please contact our staff members to discuss your project ideas. If you do not have a specific topic in mind, feel free to look at the proposed projects here.
Under the Antarctic ice sheet lies a hidden network of lakes and rivers driving ice dynamics. This MSc research project offers you the chance to explore the subglacial hydrology of Antarctica using Interferometric Synthetic Aperture Radar (InSAR). Understanding this hydrological system is crucial for predicting sea-level change and assessing impacts of different climate scenarios. Despite the challenges posed by the thick ice cover, recent studies using Sentinel-1 C-band InSAR timeseries have successfully detected subglacial flow paths, lakes, and water fluxes. This study will focus on assessing the capability of L-band InSAR in detecting and mapping subglacial water and comparing this with C-band InSAR. L-band's longer wavelength is expected to provide superior coherence over time, making it valuable for characterizing slower and larger movements of subglacial meltwater. With this project you'll help us prepare for future L-band satellite missions like NASA-ISRO's NISAR (launching in 2025, with an explitic Antarctic focus) and ESA’s ROSE-L.
Contact: Malin (malin.johansson@uit.no), Jelte van Oostveen (jeoo@norceresearch.no)
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)
Sea ice thickness is estimated using radar-satellites by measuring how far the floating ice sticks out of the water; this involves measuring the elevation of the floating ice surface, and the elevation of nearby open water. The difference is known as the "ice freeboard". The technique requires the "clean" reflection of radar pulses from one surface type: ice or water. It also helps when the ice surface is floating further above the waterline, with freeboards.
Arctic sea ice is becoming thinner and more mobile as the atmosphere warms, and these changes will continue over the 21st Century. This raises the question of if, and when, Arctic freeboards will become too small to measure with existing approaches. So what is the future of freeboard in the Arctic Ocean? This project will analyse sea ice and snow thickness data in projections from the latest generation of climate models to determine how Arctic sea ice freeboard will evolve over the 21st Century.
Because the sea ice is also becoming more mobile, gaps in the sea ice called "leads" are becoming increasingly common. This raises the question of whether it's becoming harder to reflect radar from pulses sea ice floes alone, without contamination from nearby water. To assess the future of this challenge, this project will also analyse radar data from the CryoSat-2 altimeter from different sea ice thicknesses and types. We know the "ice of the future" is younger and thinner, so is this ice harder to measure than the existing older, thicker ice?
The future of radar altimetry in the Arctic is bound up in the future of sea ice freeboard and mobility.
Your results will be relevant to the long-term planning and strategy of Earth-Observing organisations such as the European Space Agency and NASA.
Contact: Robbie Mallet (robbie.d.mallett@uit.no)
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:
In the Barents Sea hydrocarbons (oil and natural gas) are stored in the seabed, and methane gas and oil is naturally seeping out and rising to the ocean surface. Known hot spots for such oil releases are Hopendjupet and the area outside Prins Karls Forland. These oil seepages can be observed in synthetic aperture radar (SAR) images.
It's common that these slicks have a drift pattern that has the shape of spirals (see figure). These spirals are partially caused by inertial oscillations. The frequency of these depends (to first order) on the latitude and to second order on the stratification. The frequency is possible to derive from, e.g., the Norwegian Norkyst-800 or Barents 2.5 model. The amplitude however will be inferred from the SAR images and within this project it’ll be investigated how well the amplitude of the near-intertial waves is resolved in the models.
Radarsat-2 image (left) with naturally occurring seepages shown as dark spirals, and Sentinel-1 SAR image (right) with overlayed areas showing the slick detections during one week.
The supervision will be shared between UiT and the Meteorological Institute.
Contact: Malin Johansson (malin.johansson@uit.no)
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.
Data:
Contact: Anthony Doulgeris (anthony.p.doulgeris@uit.no)
Separation between sea ice and open water in fjords in Svalbard is challenging. Wind conditions are ever changing, the sea ice is forming in-situ and is drifting.
We have established a time series starting in 2014 with Sentinel-1 data for three fjords on Svalbard, Hornsund, Kongsfjorden and Rijpfjorden.
The goal here is to train a neural network into automatically separating open water from sea ice. Though the challenging wind conditions and the low signal of thin nice means that some images had to be removed due to poor quality. It's important that an AI based system can learn why these images were considered poor.
Alternatively can the project focus on the melting snow cover on the sea ice. Information about wet snow cover on shore (from the same Sentinel-1 time series https://doi.org/10.3389/feart.2022.868945 ) exist and be used as a proxy to derive melting snow on the sea ice.
Contact: Malin Johansson (malin.johansson@uit.no)
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)