Impact of characterization on cross-calibration performance for multispectral sensors with SI-traceable satellite mission TRUTHS
Author(s)
Type
Journal Article
Abstract
A new generation of satellites designed for low-uncertainty, SI-traceable measurements—termed
“SITSats”—marks a major advancement in Earth observation (EO) capability. These missions aim to enhance the performance and interoperability of the EO “system of systems.” Among them, the ESA Earth Watch Traceable Radiometry Underpinning Terrestrial- and Helio-Studies (TRUTHS) mission is designed
to serve as a “gold-standard” radiometric reference for cross-calibrating EO sensors in the solar reflective domain. In this work, uncertainties in cross-calibration comparisons arising from sensor characterization and design are investigated. A processing chain to prepare collocated data for uncertainty-quantified comparison is presented. This includes steps to perform spectral band adjustment and spatial resampling. Using the TRUTHS hyperspectral imaging spectrometer (HIS)
as the reference and Sentinel-2 multispectral imager (MSI) as the target, a simulation study based on high-resolution imagery assesses achievable comparison performance. A subset of uncertainty effects driven by sensor characterization is propagated through the spectral and spatial processing using a Monte Carlo approach. Sentinel-2 data are assumed at 10-m resolution, which is most sensitive to the errors considered. The results highlight the importance of sensor characterization, particularly inherent in-flight wavelength knowledge for target sensors, in such comparisons. Results from the simulation analysis give uncertainty estimates (k = 1) of 0.31% (blue), 0.50% (green), and 0.23% (red) for the combined error effects
arising from sensor characterization and geolocation uncertainty for comparisons over the Libya-4 desert pseudo-invariant calibration sites (PICS) using an instantaneous 205-m square comparison region. Results for more heterogeneous scenes, such as rainforest, still achieve uncertainties of 0.6%–1.2% for the red–green–blue (RGB) bands over a 200 × 200 m area. The uncertainty is driven largely by the spectral component—up to 1% due to the inherent Sentinel-2 wavelength knowledge of 1 nm across various representative scenes outside of the atmospheric absorption bands. While the impact of these uncertainties may decrease when considering a diverse range of scene types, they
introduce systematic errors when scenes share similar spectral characteristics. The impact of some uncertainty contributions, for example, geolocation uncertainty, is shown to be substantially reduced by aggregating samples over larger regions or over longer time periods. This analysis supports the development of low-uncertainty, ideally SITSat-enabled intercalibration
approaches needed to ensure radiometric consistency acrossmmissions for generating long-term climate data records.
“SITSats”—marks a major advancement in Earth observation (EO) capability. These missions aim to enhance the performance and interoperability of the EO “system of systems.” Among them, the ESA Earth Watch Traceable Radiometry Underpinning Terrestrial- and Helio-Studies (TRUTHS) mission is designed
to serve as a “gold-standard” radiometric reference for cross-calibrating EO sensors in the solar reflective domain. In this work, uncertainties in cross-calibration comparisons arising from sensor characterization and design are investigated. A processing chain to prepare collocated data for uncertainty-quantified comparison is presented. This includes steps to perform spectral band adjustment and spatial resampling. Using the TRUTHS hyperspectral imaging spectrometer (HIS)
as the reference and Sentinel-2 multispectral imager (MSI) as the target, a simulation study based on high-resolution imagery assesses achievable comparison performance. A subset of uncertainty effects driven by sensor characterization is propagated through the spectral and spatial processing using a Monte Carlo approach. Sentinel-2 data are assumed at 10-m resolution, which is most sensitive to the errors considered. The results highlight the importance of sensor characterization, particularly inherent in-flight wavelength knowledge for target sensors, in such comparisons. Results from the simulation analysis give uncertainty estimates (k = 1) of 0.31% (blue), 0.50% (green), and 0.23% (red) for the combined error effects
arising from sensor characterization and geolocation uncertainty for comparisons over the Libya-4 desert pseudo-invariant calibration sites (PICS) using an instantaneous 205-m square comparison region. Results for more heterogeneous scenes, such as rainforest, still achieve uncertainties of 0.6%–1.2% for the red–green–blue (RGB) bands over a 200 × 200 m area. The uncertainty is driven largely by the spectral component—up to 1% due to the inherent Sentinel-2 wavelength knowledge of 1 nm across various representative scenes outside of the atmospheric absorption bands. While the impact of these uncertainties may decrease when considering a diverse range of scene types, they
introduce systematic errors when scenes share similar spectral characteristics. The impact of some uncertainty contributions, for example, geolocation uncertainty, is shown to be substantially reduced by aggregating samples over larger regions or over longer time periods. This analysis supports the development of low-uncertainty, ideally SITSat-enabled intercalibration
approaches needed to ensure radiometric consistency acrossmmissions for generating long-term climate data records.
Date Issued
2025-12-04
Date Acceptance
2025-11-13
Citation
IEEE Transactions on Geoscience and Remote Sensing, 2025, 63
ISSN
0196-2892
Publisher
Institute of Electrical and Electronics Engineers
Journal / Book Title
IEEE Transactions on Geoscience and Remote Sensing
Volume
63
Copyright Statement
© 2025 The Authors. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/
License URL
Subjects
Calibration
climate
cross-calibration
DESERT SITES
Earth
Earth observation (EO)
Engineering
Engineering, Electrical & Electronic
Geochemistry & Geophysics
hyperspectral
Hyperspectral imaging
Imaging Science & Photographic Technology
intercalibration
INTERCALIBRATION
interoperability
Measurement uncertainty
Monitoring
multispectral imager (MSI)
Physical Sciences
Radiometry
RADIOMETRY
Remote Sensing
Satellite broadcasting
Science & Technology
sensor characterization
Sensor phenomena and characterization
Sensors
Sentinel-2
SI-traceable
SI-traceable satellite (SITSat)
Technology
Traceable Radiometry Underpinning Terrestrial- and Helio-Studies (TRUTHS)
uncertainty
Uncertainty
UNCERTAINTY
Publication Status
Published
Article Number
5654016
Date Publish Online
2025-11-17