HYPSO - Space environment effects on hyperspectral imager: performing thermal experiments and modelling
- Project and Master Subjects 2024-2025
-
Past Projects
- Project and Master Subjects 2023-2024
-
Project and master assignments 2022
- Ocean Color Data Analysis
- Software Development for Optical CubeSat Payload
- Ensemble Biomass Estimation
- Topics on Hyperspectral Image Encoding
- Atmospheric Correction of HYPSO-1
- Remote sensing data fusion for algae detection
- HYPSO hyperspectral satellite data fusion with in-situ sensors
- HYPSO-1 data georectification using direct and indirect methods
- Generation and calibration of HYPSO-1 data products
- Sentinel satellite multispectral data to aid HYPSO-1 imaging
- Verification and validation of HYPSO-2 optical payload
- HYPSO-2: Designing a Software-defined-radio (SDR) application experiment for communication between on-ground sensor systems
- HYPSO-2: Designing experiment for channel characterization using the Software-defined-radio (SDR) payload in HYPSO-2
- HYPSO - Space environment effects on hyperspectral imager: performing thermal experiments and modelling
- Software Development for Optical CubeSat Payload
- Re-design and re-configuration for hardware-software test-bench for HYPSO-1 and HYPSO-2 (FlatSat)
- Automation of operations for the HYPSO-1 satellite
- HYPSO - Georeferencing, operations - Incorporating ADCS telemetry into the OPU
HYPSO – Space environment effects on hyperspectral imager: performing thermal experiments and modelling.
In January 2022 the HYPSO-1 satellite was launched. The HYPSO-1 contains a hyperspectral imager that is currently imaging the earth. In space, the satellite is exposed to an extreme environment compared to the environment on earth. The extreme temperature changes can influence the performance of the hyperspectral imager. This is because thermal expansion causes deformation of the payload, including sensitive optical components such as the lenses of the hyperspectral imager.
In this project the student will map how temperature changes affect the optical system of the hyperspectral imager. To do so, the student will perform thermal experiments with the hyperspectral imager. Moreover, the student will learn how to use an existing simulation model of the hyperspectral imager. The model results can be compared to the thermal experiments. The project can be tailored to the student. It is possible to focus more on the data processing of the temperature effects or applying machine-learning techniques on the available data, if this is of interest to the student.
For more information, or a short discussion contact esmee.oudijk@ntnu.no