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  1. NTNU SmallSat Lab For Students Past Projects
  2. Project and master assignments 2022
  3. Generation and calibration of HYPSO-1 data products

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Generation and calibration of HYPSO-1 data products

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  • Project and Master Subjects 2025-2026
  • Past Projects
    • Project and Master Subjects 2024-2025
    • 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
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Generation and calibration of HYPSO-1 data products

The HYPSO-1 mission is collecting hyperspectral data across the world. We want to develop a pipeline to generate common satellite data products from the downlinked HYPSO-1 data, so that the data can be further used to answer scientific questions. 

The HYPSO-1 cubesat was launched in January 2022, and is now in-orbit gathering lots of hyperspectral data. Hyperspectral datacubes are downlinked to the ground station, and conversion from raw data to common satellite data products, such as top-of-atmosphere radiance, ocean surface reflectance etc., is an important step as it makes the data available for the scientists to use.  

The task for this project is to build a pipeline which automatically generates the desired data product based on the incoming data and satellite metadata. The steps in the pipeline includes radiometric calibration and image correction, geo-referencing, atmospheric correction amongst others. The pipeline will also be tested, and should calculate the uncertainties related the final data products. 

For more information or questions, contact Joe Garrett (joseph.garrett@ntnu.no) or Marie Bøe Henriksen (marie.b.henriksen@ntnu.no) 

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