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HPC-Enabled Geoprocessing Services Cases: EUXDAT, EOPEN, and CYBELE European Frameworks

Authors:
Jose Miguel Montanana Aliaga
Antonio Hervas
Dennis Hoppe

Keywords: High-Performance Computing; Cloud Computing; Big Data; Agriculture; Land Monitoring; Machine Learning.

Abstract:
There are big challenges with a great impact on the economy that can be addressed with geoprocessing such as the improvement in agricultural productivity, design of transport networks, prediction of natural disasters, or the study of climate change. This paper introduces recent developments in three European projects in High-Performance Computing (HPC)-Enabled geoprocessing Services applied to agricultural issues. The main goals of the European Union (EU) projects EUXDAT (extreme data analytics in sustainable development), CYBELE (fostering precision agriculture and livestock farming through secure access to large-scale HPC-enabled virtual industrial experimentation environment empowering scalable big data analytics), and EOPEN (open interoperable platform for unified access and analysis of Earth observation data) are, in general, to enable the use of large HPC systems, as well as big data management and user-friendly access and visualization of the results. In addition, these three projects focus on the development of software frameworks, develop Artificial Intelligence (AI) algorithms, and fuse Earth-Observation data, such as Copernicus data, and non-Earth-Observation data, such as weather, environmental and social media information. Finally, some initial results are shown.

Pages: 70 to 74

Copyright: Copyright (c) IARIA, 2020

Publication date: March 22, 2020

Published in: conference

ISSN: 2308-393X

ISBN: 978-1-61208-762-7

Location: Valencia, Spain

Dates: from November 21, 2020 to November 25, 2020