Sentinel-2A and 2B absolute calibration monitoring

Revel, C.; Lonjou, V.; Marcq, Sébastien; Desjardins, Camille; Fougnie, Bertrand; Luche, Céline Coppolani-Delle; Guilleminot, Nicolas; Lacamp, Anne-Sophie; Lourme, E.; Miquel, C.; Lenot, Xavier

doi:10.1080/22797254.2018.1562311

Cited by 37 publications

(28 citation statements)

References 25 publications

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“…The calibration results obtained over the Libya-4 site using the OSCAR methodology confirm the slight bias between S2B and S2A as observed by [23,25], with S2B having slightly lower TOA reflectance values than S2A. The strong consistency between S2 and LS8 as reported in [23,25,26], with a slightly greater difference for the LS8 CA band (Band1, 0.443 µm) is also confirmed here. To our knowledge, cross-calibration results for Deimos-1 and PROBA-V with respect to S2 and LS8 have not been published before.…”

Section: Discussionsupporting

confidence: 86%

“…For most bands, S2A is slightly brighter than S2B. This is in line with the findings of [23]. Table 4.…”

Section: Libya-4supporting

confidence: 90%

“…Although overall the largest number of matchups are retrieved for the LCFR site, the results for all sensors show large error bars for this site. References [23,24] also reported on the difficulty of retrieving accurate results over the LCFR site. The large variation in the calibration results obtained over this site may be related to the site's heterogeneity, including sparse vegetation.…”

Section: Discussionmentioning

confidence: 99%

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Radiometric Top-of-Atmosphere Reflectance Consistency Assessment for Landsat 8/OLI, Sentinel-2/MSI, PROBA-V, and DEIMOS-1 over Libya-4 and RadCalNet Calibration Sites

Sterckx

Wolters

2019

Remote Sensing

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There is a clear trend toward the use of higher spatial resolution satellite sensors. Due to the low revisit time of these sensors and frequent cloud coverage, many applications require data from different sensors to be combined in order to have more frequent observations. This raises concerns regarding data interoperability and consistency. The initial pre-requisite is that there are no radiometric differences in top-of-atmosphere (TOA) observations. This paper aims to quantitatively assess differences in the TOA signal provided by PROBA-V, Sentinel-2A and Sentinel-2B, Landsat-8, and Deimos-1 by using observations over both the Libya-4 desert calibration site and the RadCalNet sites. The results obtained over the Libya-4 site indicate that for all sensors investigated, the inter-sensor deviations are negligible, i.e., within ±2% for comparable spectral bands, with the exception of the Deimos-1 Green band. Clear BRDF (bi-directional reflectance distribution function) effects were observed over the RadCalNet sites, thereby preventing consistent conclusions on inter-sensor deviations from being made. In order to fully explore the potential of the RadCalNet sites, it is recommended that BRDF characterizations be additionally incorporated into the RadCalNet simulations and made publicly available through the distribution portal.

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Section: Discussionsupporting

confidence: 86%

“…For most bands, S2A is slightly brighter than S2B. This is in line with the findings of [23]. Table 4.…”

Section: Libya-4supporting

confidence: 90%

Section: Discussionmentioning

confidence: 99%

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Radiometric Top-of-Atmosphere Reflectance Consistency Assessment for Landsat 8/OLI, Sentinel-2/MSI, PROBA-V, and DEIMOS-1 over Libya-4 and RadCalNet Calibration Sites

Sterckx

Wolters

2019

Remote Sensing

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“…DCCs are widely used for long-term calibration monitoring (e.g., [9][10][11]) and interband monitoring of medium-and high-resolution. optical payloads (e.g., [12,13]), notably owing to the whiteness of their reflectance spectrum from the visible to the near-infrared. The fact that they are white, bright, and opaque provides the best conditions to avoid the propagation of modelling assumptions and associated uncertainties in the analysis as much as possible.…”

Section: Introductionmentioning

confidence: 99%

OLCI A/B Tandem Phase Analysis, Part 3: Post-Tandem Monitoring of Cross-Calibration from Statistics of Deep Convective Clouds Observations

Lamquin¹,

Bourg²,

Clerc³

et al. 2020

Remote Sensing

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This study is a follow-up of a full methodology for the homogenisation and harmonisation of the two Ocean and Land Colour Instrument (OLCI) payloads based on the OLCI-A/OLCI-B tandem phase analysis. This analysis provided cross-calibration factors between the two instruments with a very high precision, providing a ‘truth’ from the direct comparison of simultaneous and collocated acquisitions. The long-term monitoring of such cross-calibration is a prerequisite for an operational application of sensors harmonisation along the mission lifetime, no other tandem phase between OLCI-A and OLCI-B being foreseen due to the cost of such operation. This article presents a novel approach for the monitoring of the OLCI radiometry based on statistics of Deep Convective Clouds (DCC) observations, especially dedicated to accurately monitor the full across-track dependency of the cross-calibration of OLCI-A and OLCI-B. Specifically, the inflexion point of DCC reflectance distributions is used as an indicator of the absolute calibration for each subdivision of the OLCI Field-of-View. This inflexion point is shown to provide better precision than the mode of the distributions which is commonly used in the community. Excess of saturation in OLCI-A high radiances is handled through the analysis of interband relationships between impacted channels and reference channels that are not impacted by saturation. Such analysis also provides efficient insights on the variability of the target’s response as well as on the evolution of the interband calibration of each payload. First, cross-calibration factors obtained over the tandem period allows to develop and validate the approach, notably for the handling of the saturated pixels, based on the comparison with the ‘truth’ obtained from the tandem analysis. Factors obtained out of (and far from) the tandem period then provides evidence that the cross-calibration reported over the tandem period (1–2% bias between the instruments) as well as inter-camera calibration residuals persist with very similar proportions, to the exception of the 400 nm channel and with slightly less precision for the 1020 nm channel. For all OLCI channels, relative differences between the cross-calibration factors obtained from the tandem analysis and the factors obtained over the other period are below 1% from a monthly analysis, even below 0.5% from a multi-monthly analysis). This opens the way not only to an accurate long-term monitoring of the OLCI radiometry but also, and precisely targeted for this study, to the monitoring of the cross-calibration of the two sensors over the mission lifetime. It also provides complementary information to the tandem analysis as the calibration indicators are traced individually for each sensor across-track, confirming and quantifying inter-camera radiometric biases, independently for both sensors. Assumptions used in this study are discussed and validated, also providing a framework for the adaptation of the presented methodology to other optical sensors.

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“…In this special issue, we publish articles on radiometric calibration, such as Revel et al (2019) crosscalibration measurements with earlier (Spot, Landsat, Meris) and current satellite missions (Landsat-8, Sentinel-3) to ensure the S2A spectral bands absolute calibration or Barsi et al (2018) Keukelaere et al (2018) tested the performance of the iCOR model in coastal, and in inland and transitional waters. Interestingly, during the first S2VT meeting, the geometric calibration activities got a smaller exposure, and thus, we present here; Ressl and Pfeifer (2018) work, dealt with the evaluation of the PlanetDEM based Level-1C orthophotos height accuracy over a mountainous terrain.…”

Section: Copernicus Sentinel-2 Calibration and Validationmentioning

confidence: 99%