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Landsat 9 Thermal Infrared Sensor 2 (TIRS-2) Stray Light Mitigation and Assessment

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The Thermal Infrared Sensor 2 (TIRS-2) payload for the Landsat 9 mission closely follows the design of the TIRS instrument currently flying aboard Landsat 8. The TIRS-2 instrument, however, incorporates… Click to show full abstract

The Thermal Infrared Sensor 2 (TIRS-2) payload for the Landsat 9 mission closely follows the design of the TIRS instrument currently flying aboard Landsat 8. The TIRS-2 instrument, however, incorporates an important design change to mitigate the stray light issue that plagued the TIRS instrument. Shortly after launch of Landsat 8 in 2013, calibration errors due to stray light artifacts were observed in Earth imagery from TIRS with magnitudes of 4% (10.8 μm band) and 8% (12.0 μm band). Out-of-field scans of the Moon were conducted to map the angles from which off-axis radiance was detected on the focal plane arrays. Optical modeling, constrained by reverse ray traces of the lunar data, identified the primary scattering sources within the TIRS telescope and these results informed the locations and design of mitigating baffles for TIRS-2. The effect of the modifications to the TIRS-2 instrument were tested pre-flight through the thermal vacuum (TVAC) characterization tests and the optical models were updated to be consistent with the measured data. Preliminary assessments indicated at least an order of magnitude reduction of the total signal due to scattering in TIRS-2. On-orbit lunar scans provided the final confirmations and demonstrated that the new design changes to TIRS-2 have reduced the primary out-of-field scattering by over 40x from the original TIRS design bringing the total scattering to 1% or less. More importantly, Earth imagery produced by Landsat 9 TIRS-2 do not show any stray light related artifacts, as was prevalent in the Landsat 8 TIRS imagery.

Keywords: tirs instrument; sensor tirs; design; stray light; thermal infrared; infrared sensor

Journal Title: IEEE Transactions on Geoscience and Remote Sensing
Year Published: 2022

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