VegetationDynamics - Towards automatized, scale independent, high resolution, high temporal dynamic vegetation water content monitoring 4.0 - Developing First Time Big Data EO Breakthrough Technologies for Vegetation Indices by Hybridising Sentinels 1 and 2.

Most geoscientific disciplines and information markets in the sectors of agriculture, forestry, and environmental management require quantitative measurements of vegetation water content (VWC) and biomass. Optical sensors are so far limited to derive various greenness indices and more physical optical variables, describing vegetation condition. Recent progress achieved in microwave remote sensing has changed this situation in a significant way. Microwave measurements penetrate deeply into vegetation and are very sensitive to the VWC and there is a large potential to use microwave sensors for monitoring VWC and related land cover dynamics. With the launch of Sentinel-1, providing measurements of cross-polarisation (CR) backscatter at a spatial resolution of 10m and regular temporal sampling of 3-6 days over Europe and monthly on a global scale, this situation has changed.

Within VegetationDynamics a S-1 and S-2 based vegetation water content (VWC) index has been developed. This was supported through an unparalleled global validation effort and a rigorous scientific schedule to deploy a hybrid model for the derivation of VWC. It was shown that S-1 successfully fills various data gaps in time series of S-2, as well as in areas where S-2 data has technical limitations and vice versa.