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After the end of the ‘Satellite Pour l'Observation de la Terre’ (SPOT) VEGETATION (SPOT/VGT) mission in May/2014, the SPOT/VGT data archive, consisting of raw data coming from both the VEGETATION 1 (VGT1) and VEGETATION 2 (VGT2) instruments, was reprocessed, aiming at improved cloud screening and correcting for known artefacts such as the smile pattern in the VGT2 Blue band and the Sun-Earth distance bug in Top-of-Atmosphere reflectance calculation, with the objective of improving temporal consistency. The aim of this paper is to inform the user community of the changes in and the evaluation of the new SPOT/VGT Collection 3 (VGT-C3). The evaluation of the reprocessing is based on (i) the relative comparison between SPOT/VGT Collection 2 (VGT-C2) and VGT-C3 surface reflectances and Normalized Difference Vegetation Index (NDVI), (ii) consistency analysis between VGT1-C3 and VGT2-C3, and (iii) the comparison of the archive with external datasets from METOP/Advanced Very High Resolution Radiometer (AVHRR) and TERRA/Moderate Resolution Imaging Spectroradiometer (MODIS). Surface reflectances are slightly higher after the reprocessing, with larger differences in July compared to January, caused by the corrected Sun-Earth distance modelling. For NDVI, the overall impact of the reprocessing is relatively small and differences show no seasonality. Trends in the differences over the years are related to changes in calibration coefficients. Systematic differences between VGT1-C3 and VGT2-C3 surface reflectance are well below 1%, with largest bias between VGT1 and VGT2 for the NIR band and the NDVI (VGT2 > VGT1, especially for larger NDVI values). Both the comparison with METOP/AVHRR (surface reflectance and NDVI) and TERRA/MODIS (NDVI) reveal trends over time: systematic bias between VGT2 and METOP/AVHRR tends to decrease over time, while comparison with TERRA/MODIS indicates an increasing bias between VGT2 and MODIS. VGT2 NDVI seems to be gradually evolving to slightly larger values, which is consistent with the change in overpass time of VGT2 and the different illumination conditions caused by the orbital drift of the sensor. Results demonstrate however the SPOT/VGT-C3 archive is more stable over time compared to the previous archive, although bidirectional reflectance distribution function (BRDF) normalization is recommended in order to correct for bidirectional effects. [ABSTRACT FROM AUTHOR]

PROBA-V (PRoject for On-Board Autonomy–Vegetation) was launched in May-2013 as an operational continuation to the vegetation (VGT) instruments on-board the Système Pour l'Observation de la Terre (SPOT)-4 and -5 satellites. The first reprocessing campaign of the PROBA-V archive from Collection 0 (C0) to Collection 1 (C1) aims at harmonizing the time series, thanks to improved radiometric and geometric calibration and cloud detection. The evaluation of PROBA-V C1 focuses on (i) qualitative and quantitative assessment of the new cloud detection scheme; (ii) quantification of the effect of the reprocessing by comparing C1 to C0; and (iii) evaluation of the spatio-temporal stability of the combined SPOT/VGT and PROBA-V archive through comparison to METOP/advanced very high resolution radiometer (AVHRR). The PROBA-V C1 cloud detection algorithm yields an overall accuracy of 89.0%. Clouds are detected with very few omission errors, but there is an overdetection of clouds over bright surfaces. Stepwise updates to the visible and near infrared (VNIR) absolute calibration in C0 and the application of degradation models to the SWIR calibration in C1 result in sudden changes between C0 and C1 Blue, Red, and NIR TOC reflectance in the first year, and more gradual differences for short-wave infrared (SWIR). Other changes result in some bias between C0 and C1, although the root mean squared difference (RMSD) remains well below 1% for top-of-canopy (TOC) reflectance and below 0.02 for the normalized difference vegetation index (NDVI). Comparison to METOP/AVHRR shows that the recent reprocessing campaigns on SPOT/VGT and PROBA-V have resulted in a more stable combined time series. [ABSTRACT FROM AUTHOR]