PROBA-V (Project for On-Board Autonomy – Vegetation) was launched on May 7th 2013, with the objective of providing global land-coverage data continuity for the SPOT (Système Pour l’Observation de la Terre)-Vegetation user community. After more than 6 years of operations, the operational phase of PROBA-V has ended on June 30, 2020.
The reprocessing of the entire PROBA-V archive at 1 km, 300 m and 100 m resolutions to Collection 2 is currently ongoing. Compared to Collection 1, the following changes are included: (1) updated radiometric calibration, (2) a new and better cloud detection method and improved cloud shadow detections, (3) an improved atmospheric correction, (4) harmonisation of the compositing among the resolutions, (5) update of the product format and (6) a new catalogue to distribute the data.
The updates in the radiometric Instrument Calibration Parameter (ICP) ) files include the dependence on date since launch, modeled by a 2nd degree polynomial, for trending of the absolute calibration coefficients for the different strips/bands. The model also corrects for the increasing trend observed in some bands. Secondly, improvements are made in the low frequency multi-angular coefficients (i.e. equalization) for the SWIR strips of the LEFT and RIGHT camera form start of mission based on yaw manoeuvre results. In addition, a correction of inter-camera bias in the Blue band is applied.
The newly designed algorithm for cloud detection in PROBA-V data introduces major changes w.r.t. the algorithm used in Collection 1. It uses a Multi-Layer Perceptron (MLP) neural network algorithm. The training and validation data have been gathered on a much larger scale compared to Collection 1, and final performance is greatly improved compared to both Collection 0 and Collection 1. The method also removed the dependency on auxiliary input data, which was a major issue in Collection 1. The cloud shadow detection was improved by removing the 1-pixel border between cloud and cloud shadow.
As in Collection 1, the new atmospheric correction is also based on the Simplified Model for Atmospheric Correction (SMAC). Compared to the previous collections, it also includes an assessment of uncertainties of the atmospheric correction and error propagation. It uses an external dataset, namely the MERRA-2 (Modern-Era Retrospective analysis for Research and Applications, version 2) for the inputs of the atmospheric correction. A validation of the atmospheric correction was done based on the Atmospheric Correction Inter-Comparison Exercise (ACIX) approach. Validation of the atmospheric correction was done based on the ACIX approach. The results show that the TopOf-Canopy (TOC) reflectances are better characterized and that artefacts due to the image based Aerosol Optical Thickness (AOT) retrieval are removed.
The compositing method is harmonized between the different resolutions in Collection 2. Previously, for 100 m and 300 m the radiometric quality of all 4 bands were checked prior to compositing. Since the SWIR band has quite a number of defect detectors, this resulted in composites with a striping effect. For the 1 km, the SWIR radiometric quality was not checked in the compositing. This method is now applied to all resolutions.
For Collection 1, the entire archive is available in two product formats: HDF5 and GeoTIFF. For Collection 2, however, we follow the newly becoming standard which is Cloud Optimized GeoTIFF (https://www.cogeo.org/) instead of the standard GeoTIFF format. It is backwards compatible with current GeoTIFF format. The regular HDF5 format will keep on existing too. This way, the handling of files in cloud environments and visualization of the data gets easier in the future.
The PROBA-V C2 metadata will also receive a update to allow for minimum compliancy with the CEOS Analysis Ready Data for Land (CARD4L). This allows for immediate analysis and interoperability both through time and with other datasets.
The PROBA-V Collection 2 data will be ingested into a new catalogue client instead of the legacy Product Distribution Facility. The user interface will allow several functionalities, such as time series export, viewing capabilities, additional authentication options, etc.
The presentation will focus on the first four changes. Details of the adaptations, together with a summary of verification and validation results, will be presented.