Enriching Earth observation datasets through semantics for climate change applications: The EIFFEL ontology

  1. Molina, Benjamin 2
  2. Palau, Carlos E. 2
  3. Calvo-Gallego, Jaime 1
  1. 1 Universidad de Salamanca
    info

    Universidad de Salamanca

    Salamanca, España

    ROR https://ror.org/02f40zc51

  2. 2 Universidad Politécnica de Valencia
    info

    Universidad Politécnica de Valencia

    Valencia, España

    ROR https://ror.org/01460j859

Revista:
Open Research Europe

ISSN: 2732-5121

Año de publicación: 2024

Volumen: 4

Páginas: 133

Tipo: Artículo

DOI: 10.12688/OPENRESEUROPE.17992.1 GOOGLE SCHOLAR lock_openAcceso abierto editor

Otras publicaciones en: Open Research Europe

Resumen

Earth Observation (EO) datasets have become vital for decision support applications, particularly from open satellite portals that provide extensive historical datasets. These datasets can be integrated with in-situ data to power artificial intelligence mechanisms for accurate forecasting and trend analysis. However, researchers and data scientists face challenges in finding appropriate EO datasets due to inconsistent metadata structures and varied keyword descriptions. This misalignment hinders the discoverability and usability of EO data.

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Referencias bibliográficas

  • (2022), Tech rep., 10.2878/94903
  • (2022)
  • (2022)
  • R Shibasaki, (2009), Tech rep.
  • (2022)
  • (2022)
  • B Molina
  • (2022)
  • (2021)
  • (2022)
  • (2022)
  • P Patel-Schneider, (2014), pp. 261-276, 10.1007/978-3-319-11964-9_17
  • A Whitcraft, (2019), Remote Sens Environ., 235, 10.1016/j.rse.2019.111470
  • E Gerasopoulos, (2022), Environ Sci Policy., 132, pp. 296-307, 10.1016/j.envsci.2022.02.033
  • N Noy, (2001), Tech rep.
  • M Grüninger, (1995)
  • (2022)
  • A Kavvada, (2020), Remote Sens Environ., 247, 10.1016/j.rse.2020.111930
  • B Molina, (2022)