Context and objectives

Upcoming temporal and spatial HR satellites such as Venus and Sentinel-2 and even the Landsat Data Continuity Mission (LDCM) will provide very valuable data for land-cover and vegetation monitoring. One of the ways to improve the temporal resolution for these satellites is to merge their data with higher temporal resolution systems. For now, these other systems will fatally have a lower spatial resolution or a limited field of view.Past research works have developed fusion approaches for using the synergy between HR resolution and mid- to low-resolution images. One of the conclusions of these works was that the resolution ratio between the images to fuse need to be not too far apart. The increased resolution of Proba-V with respect to the Vegetation sensor seems to be well suited for this kind of applications.The goal of this project is to assess the usefulness of these techniques for the joint use of Proba-V data and Venus/Sentinel-2/LDCM images for land-cover monitoring. As a result of the proposed work, one can expect an algorithm for the generation of land-cover maps and time profiles of surface reflectances with a spatial resolution of 10 to 30 m. with an update frequency of about 10 days. Particular attention will be paid to the different spectral resolutions of the sensors used.

Project outcome

Expected scientific results

The review and comparison of methods for the joint use of Poba-V data together with high geometrical and temporal resolution sensors as Venµs and Sentinel-2.
The generation of simulated datasets representative of Proba-V data over sites where other sources of imagery and ground data are available.
The development of new methods combining signal processing (interpolation, deconvolution, unmixing) and rigorous physical models (radiative transfer, canopy properties, soil/vegetation/atmosphere transfer).
The implementation of the selected methods and the validation of the produced software through its integration in the ORFEO Toolbox.