Cross Calibration Over Desert Sites: Description, Methodology, and Operational Implementation

Abstract

Radiometric cross calibration of Earth observation sensors is a crucial need to guarantee or quantify the consistency of measurements from different sensors. Twenty desert sites, historically selected, are revisited, and their radiometric profiles are described for the visible to the near-infrared spectral domain. Therefore, acquisitions by various sensors over these desert sites are collected into a dedicated database, Structure d'Accueil des Données d'Etalonnage, defined to manage operational calibrations and the required SI traceability. The cross-calibration method over desert sites is detailed. Surface reflectances are derived from measurements by a reference sensor and spectrally interpolated to derive the surface and then top-of-atmosphere reflectances for spectral bands of the sensor to calibrate. The comparison with reflectances really measured provides an estimation of the cross calibration between the two sensors. Results illustrate the efficiency of the method for various pairs of sensors among AQUA-Moderate Resolution Imaging Spectroradiometer (MODIS), Environmental Satellite-Medium Resolution Imaging Spectrometer (MERIS), Polarization and Anisotropy of Reflectance for Atmospheric Sciences Couples With Observations From a Lidar (PARASOL)-Polarization and Directionality of the Earth Reflectances (POLDER), and Satellite pour l'Observation de la Terre 5 (SPOT5)-VEGETATION. MERIS and MODIS cali-brations are found to be very consistent, with a discrepancy of 1%, which is close to the accuracy of the method. A larger bias of 3% was identified between VEGETATION-PARASOL on one hand and MERIS-MODIS on the other hand. A good consistency was found between sites, with a standard deviation of 2% for red to near-infrared bands, increasing to 4% and 6% for green and blue bands, respectively. The accuracy of the method, which is close to 1%, may also depend on the spectral bands of both sensor to calibrate and reference sensor (up to 5% in the worst case) and their corresponding geometrical matching.

Copernicus Sentinel-2A Calibration and Products Validation Status

“…However, these results illustrate the good quality of S2A/MSI calibration in agreement with [35]. The results compare well with those obtained by the French Space Studies Centre (CNES) over the same PICS and the same commissioning period, but using independent desert-calibration methodology [36].…”

In-Orbit Radiometric Calibration and Stability Monitoring of the PROBA-V Instrument

“…This is explained mainly by the fact that for RED and NIR bands in particular there is a negative bias of about 4% between VGT2 and MERIS, as documented by various authors [2,[16][17][18]. For the BLUE band, the largest difference with respect to VGT-2 is observed for the PROBA-V CENTER camera and clear differences exist between the cameras.…”

Radiometric Cross-Calibration of the Chilean Satellite FASat-C Using RapidEye and EO-1 Hyperion Data and a Simultaneous Nadir Overpass Approach

“…Nevertheless, as mentioned before, MAPE, RMSE and MBE have substantially decreased after cross-calibration, meaning that the FASat-C radiances and reflectances are in good agreement with the RapidEye values. However, additional improvements in the cross-calibration method could be accomplished either by increasing the number of SNO's, when available [19,20,32], or by fitting a BRDF model to the observations of the calibration site [52,53,56]. A refinement of the SBAF retrieval scheme could also provide important advances, particularly if (1) higher spectral resolution data and TOA simulations based on in situ measurements and (2) radiative transfer modeling [21,56,61] are applied.…”