WG3 Sustainable Land Management of Complex European Landscapes

WG3 will pursue a combined exploration of the hyperspectral spaceborne missions’ data along with other available (multi-spectral) as the ESA Copernicus Sentinel-2 (S2), providing high temporal and spatial coverage. This includes the improved exploitation of cloud computing platforms and EOS data fusion, such as Sentinel-1+2, targeting the spatio-temporal mapping of multiple vegetation traits.

Objectives

To develop a validation strategy for priority vegetation products from near-term (upcoming) hyperspectral satellite missions (CHIME, ENMAP; SHALOM, SBG, FLEX) using ground-based or airborne data.
To foster the use of big data and cloud computing for data fusion, time-series forecasting, and processing of spatiotemporally continuous vegetation products.
To enhance the strategic aspects of EOS as a standard technology to support climate change, society issues, and ecosystem functions through time series of vegetation phenology, new sensor fusion approaches, and new data processing methods that are more accessible to end-users and policy makers, including the associated meanings and uncertainties of derived products.

Tasks

Training School on the use of Google Earth Engine and other cloud-based EOS data and processing web platforms. The Training School will take place during GP2.
STSMs to investigate validation strategies of hyperspectral satellite mission products. These STMs will take place during GP2 and 3.
STSMs to support climate change, society issues, ecosystem functions through time series of vegetation phenology. These STMs will take place during GP3 and GP4.
Joint uncertainty analysis and protocol standardization assessment summer school on novel and operational hyperspectral data products together with WG4.