E-graze data cube for regular monitoring of grasslands: a case study in Greece

Eleni Kalopesa; Nikolaos Tsakiridis; Nikiforos Samarinas; George Zalidis; Nikolaos Tziolas

doi:10.1117/12.2683149

21 September 2023 E-graze data cube for regular monitoring of grasslands: a case study in Greece

Eleni Kalopesa, Nikolaos Tsakiridis, Nikiforos Samarinas, George Zalidis, Nikolaos Tziolas

Author Affiliations +

Proceedings Volume 12786, Ninth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2023); 127861T (2023) https://doi.org/10.1117/12.2683149
Event: Ninth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2023), 2023, Ayia Napa, Cyprus

Abstract

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.

Citation Download Citation

Eleni Kalopesa, Nikolaos Tsakiridis, Nikiforos Samarinas, George Zalidis, and Nikolaos Tziolas "E-graze data cube for regular monitoring of grasslands: a case study in Greece", Proc. SPIE 12786, Ninth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2023), 127861T (21 September 2023); https://doi.org/10.1117/12.2683149

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KEYWORDS

Data modeling

3D modeling

Vegetation

Sustainability

Artificial intelligence

Modeling

Spatial resolution

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