Regular monitoring of grassland productivity is important for a sustainable use of their resources and understanding how ongoing and predicted extreme events impact their productivity and the adaptations needed in their management. Recognizing these issues, we propose the development of a powerful and modular digital infrastructure able to provide geospatial products in support of grassland monitoring in Serres regional unit, Greece. The current work firstly aims at providing a tool enabling rapid Earth Observation data access, handling, and pre-processing by significantly facilitating the generation of analysis-ready data using Sentinel-2 imagery data allowing to build the first version of a grassland-oriented Data Cube. The overarching objective is to develop biomass and environmental related proxies tailored to grassland ecosystems, using state-of-the-art artificial intelligence and data mining techniques to make the most out of optical high spatial resolution data for the derivation of grassland biophysical parameters and degradation indicators. The final products are summarized in a land use map area of the area derive from a convolution neural network classification algorithm, as well as a set of vegetation indices and bare soil products from the period from 2020-2022. The output will be used to provide technical recommendations to farmers to make better management decisions and will inform index-based environmental assessment, letting farmers avoiding land abandonment or overgrazing and the related consequences on landscape conservation, soil quality, and biodiversity.
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