The PV-LAC project aimed at the development, testing, and validation of two advanced algorithms for the scientific exploitation of the Proba-V mission, one activity focusing on Atmospheric Correction and the other on Coastal Products.
In the first activity, an Optimal Estimation (OE) method was developed for the Atmospheric Correction of the 1 km resolution Proba-V data. The method relies on the joint aerosol optical depth and surface reflectance retrieval through the inversion of a physically-based coupled surface-atmosphere radiative transfer model. This approach was originally developed for geo-stationary satellite observations, which provide a very high temporal sampling, and was adapted to enable processing of Proba-V 1 km data. Proba-V observations are accumulated over 16 days to compose a multi-angular and multi-spectral observation vector. Within this 16-days period, surface radiative properties are assumed invariant. Additionally, the surface reflectance retrieval and associated uncertainty of the previously processed accumulation periods is used as a priori information for the inversion.
The second activity within PV-LAC focused on the exploration of Proba-V for Coastal Products generation, using only the Proba-V central camera. This camera provides observations at 100 m spatial resolution with a five-day global coverage. Although Proba-V was not conceived as an Ocean Colour (OC) mission, its specifications (spectral bands and signal-to-noise ratio) are suitable to monitor some of the key OC parameters, in particular Suspended Particulate Matter (SPM). Especially in estuarine environments, the higher spatial detail of Proba-V, combined with a sufficiently high repeat frequency, was demonstrated to be of added value to other sensors.
The project was executed between January 2016 and October 2017 and consisted of four tasks:
- Scientific review and requirements consolidation (April 2016)
- Algorithm definition (November 2016)
- Algorithm evaluation and validation (May 2017)
- Recommendations and roadmap (October 2017)