Satellite Underflight Utility for Thermal Sensor Harmonization

TL;DR

This study uses underflight data from Landsat 8 and 9 to identify optimal scenes for thermal sensor calibration validation, demonstrating that scenes with less than 5% RMSD in TOA radiance are reliable for cross-calibration.

Contribution

It introduces a method to select suitable scenes for thermal sensor calibration validation using underflight data, establishing RMSD thresholds for scene reliability.

Findings

Scenes with RMSD < 5% are optimal for cross-validation.

Agreement between Landsat 8 and 9 TIRS sensors is within 0.123 K and 0.066 K.

Scene selection criteria are robust across various land types and conditions.

Abstract

Underflight maneuvers provide a unique opportunity to harmonize calibration of on-orbit sensors. Due to their similar sensor technologies, their near-identical transmission profiles, orbital properties and platform operations, the underflight data of Landsat 8 and 9 instruments stand out as a qualifier to test proposed metrics, methods, and the extent over which to compare two independently calibrated sensors across their similar operating bandpasses. This study performed a pixel-to-pixel comparison of thermal imagery of TIRS and TIRS-2 (aboard Landsat 8 and 9, respectively) during their five-day underflight maneuver in November 2021, with the ultimate goal of identifying the key site/scene-selection criteria for a subset of images that are suitable for radiative calibration validation purposes. If a group of near-coincidentally observed images by two identical underflying sensors fail to show consistent Top-of-Atmosphere (TOA) Brightness Temperatures for the same exact geographical locations, then the scenes with those shared properties and/or observing conditions will prove unreliable for cross calibration validation of less-similar underflying sensor pairs. This study demonstrates that near-coincidental images with Root Mean Square Deviations (RMSDs) of less than 5\% between their TOA radiances are optimum candidates for cross-validation of radiative calibration between two independently calibrated sensors. This criterion is shown to be reliable for coincidental acquisitions with a wide range of overlapping area, terrain type, land-to-water fraction and cloud coverage. Important considerations include any time gap between near-coincident acquisitions as well as the application of pixel quality masks. The analysis of the selected underflight scenes demonstrated an agreement between the TIRS on Landsat 8 and 9 to within 0.123 K and 0.066 K for the 10.9um and 12.0um bands respectively.