Multi-angle image analysis and what we can learn about the atmosphere
- Project and Master Subjects 2025-2026
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Past Projects
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Project and Master Subjects 2024-2025
- Improving Images for Climate Action
- Every Variable Everywhere All at Once
- Protecting Water Resources through Machine Learning and Hyperspectral Imaging in Remote Sensing CubeSats
- More Effective Earth Observation for Climate Action Through Learned Data Compression in CubeSats
- Mitigating Camera Artifacts in HYPSO Data for Improved Climate Monitoring
- Characterization of High-resolution Spectral Imager
- A Foundational Unmixing Model for the HYPSO satellites
- Hyper/Multispectral image fusion with HYPSO-2
- Game theory applied to energy optimal satellite attitude control
- Mu-analysis for agile satellite attitude control maneuvers
- Randomized optimization applied to super-agile satellite operations
- Modelling super-agile satellite operations for optimization
- Enabling high-accuracy HYPSO image georeferencing by high-accuracy satellite pose estimation through postprocessing of satelitte sensor data
- High-accuracy attitude determination of Earth observation satellites
- Agile Earth Observation Satellite simulation studies
- Multi-angle image analysis and what we can learn about the atmosphere
- GNSS-R: Simulator design of a GNSS-Reflectometry small satellite
- GNSS-R: GNSS jamming and spoofing source localization from a small satellite
- GNSS-R: Maritime Surveillance using GNSS-Reflectometry
- Project and Master Subjects 2023-2024
- Project and master assignments 2022
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Project and Master Subjects 2024-2025
Multi-angle image analysis and what we can learn about the atmosphere
Background
Light leaving the earth to be sensed by Earth observation satellites (EOSs) consists of two parts: Light reflected from the earth's surface, and light scattered by the atmosphere. Usually, the light scattered by the atmosphere is an undesirable but unavoidable aspect of the satellite data, that most attempt to remove from the data. These atmospheric correction or compensation methods depend on accurate atmospheric modelling. With a global view taking images of locations all around the globe, satellites also take images of many different atmospheric conditions, some of which are only possible to determine when measured from many different viewing angles.
Impact
Space technology plays a crucial role in achieving various Sustainable Development Goals set by the UN. The NTNU SmallSat Lab's HYPSO satellites, HYPSO-1 launched in 2022 and with a successor planned for summer 2024, utilize hyperspectral imagers to capture detailed information beyond the visible. This data allows us to detect and monitor water bodies like oceans, fjords, and lakes, including vital yet potentially harmful algae. The HYPSO satellites also contribute to climate change studies by imaging the Arctic region. Ultimately, HYPSO aims to play a role in achieving Climate Action, Preserving Life Below Water, and ensure access to Clean Water and Sanitation. This project has the potential to improve atmospheric compensation methods for HYPSO and in general hyperspectral satellite data.
Project Focus
The HYPSO-1 satellite has the capability of taking an image of the same location from multiple angles. The hypothesis is that by combining these images, properties of the atmosphere can be inferred, that inform and improve atmospheric modelling and compensation methods. Thus, the focus will lie on HYPSO data analysis and atmospheric modelling.
Tasks and Expected Outcomes
The candidate will learn about existing atmospheric modelling and compensation methods, via a guided literature review, and about hyperspectral data in general and from the HYPSO satellites. As the project progresses, the candidate can define their own tasks and goals, which may include extraction of atmospheric properties from multi-angle images, and using atmospheric compensation algorithms. The work will most likely be carried out using either Matlab or Python.
Who We Are Looking For
We are seeking a highly motivated final year student in Cybernetics, Electronics, or a related field with an interest in math, physics, and modelling. Previous experience is not mandatory. The project will be adapted to the student's background and goals.
How we work
At the NTNU SmallSat Lab we encourage collaboration and try to get our group to help each other. To facilitate this, we encourage the students to meet us in the lab as well as arrange common lunches and workshops where the students and supervisors can learn from each other.
For further information, please contact the following.
Dennis D. Langer - https://www.ntnu.no/ansatte/dennis.d.langer
Sivert Bakken - https://www.ntnu.no/ansatte/sivert.bakken