Paving the Way to Increased Interoperability of Earth Observations Data Cubes

Gregory Giuliani, Joan Masó, Paolo Mazzetti, Stefano Nativi and Alaitz Zabala
Additional contact information
Gregory Giuliani: Institute for Environmental Sciences, University of Geneva, enviroSPACE, Bd Carl-Vogt 66, CH-1205 Geneva, Switzerland
Joan Masó: Center for Ecological Research and Forestry Applications (CREAF), Universitat Autònoma de Barcelona (UAB), 08193 Bellaterra, Barcelona, Spain
Paolo Mazzetti: National Research Council of Italy (CNR)—Institute of Atmospheric Pollution Research, Via Madonna del Piano 10, 50019 Sesto Fiorentino, Italy
Stefano Nativi: European Commission Joint Research Center (JRC), Via E. Fermi, 2749, 21027 Ispra, Italy
Alaitz Zabala: Geography Department, Universitat Autònoma de Barcelona (UAB), 08193 Bellaterra, Barcelona, Spain

Data, 2019, vol. 4, issue 3, 1-23

Abstract: Earth observations data cubes (EODCs) are a paradigm transforming the way users interact with large spatio-temporal Earth observation (EO) data. It enhances connections between data, applications and users facilitating management, access and use of analysis ready data (ARD). The ambition is allowing users to harness big EO data at a minimum cost and effort. This significant interest is illustrated by various implementations that exist. The novelty of the approach results in different innovative solutions and the lack of commonly agreed definition of EODC. Consequently, their interoperability has been recognized as a major challenge for the global change and Earth system science domains. The objective of this paper is preventing EODC from becoming silos of information; to present how interoperability can be enabled using widely-adopted geospatial standards; and to contribute to the debate of enhanced interoperability of EODC. We demonstrate how standards can be used, profiled and enriched to pave the way to increased interoperability of EODC and can help delivering and leveraging the power of EO data building, efficient discovery, access and processing services.

Keywords: Open Data Cube; remote sensing; geospatial standards; landsat; sentinel; analysis ready data (search for similar items in EconPapers)
JEL-codes: C8 C80 C81 C82 C83 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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