Journal article Open Access

Earth Observation Open Science: Enhancing Reproducible Science Using Data Cubes

Guiliani, Gregory; Camara, Gilberto; Killough, Brian; Minchin, Stuart


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  <identifier identifierType="URL">https://zenodo.org/record/3837365</identifier>
  <creators>
    <creator>
      <creatorName>Guiliani, Gregory</creatorName>
      <givenName>Gregory</givenName>
      <familyName>Guiliani</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0002-1825-8865</nameIdentifier>
      <affiliation>University of Geneva</affiliation>
    </creator>
    <creator>
      <creatorName>Camara, Gilberto</creatorName>
      <givenName>Gilberto</givenName>
      <familyName>Camara</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0002-3681-487X</nameIdentifier>
      <affiliation>INPE (National Institute for Space Research), Brazil</affiliation>
    </creator>
    <creator>
      <creatorName>Killough, Brian</creatorName>
      <givenName>Brian</givenName>
      <familyName>Killough</familyName>
      <affiliation>NASA</affiliation>
    </creator>
    <creator>
      <creatorName>Minchin, Stuart</creatorName>
      <givenName>Stuart</givenName>
      <familyName>Minchin</familyName>
      <affiliation>Geosciences Australia</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Earth Observation Open Science: Enhancing Reproducible Science Using Data Cubes</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2019</publicationYear>
  <subjects>
    <subject>Open science, Reproducibility, Earth observations, data cube, analysis ready data, remote sensing, satellite imagery</subject>
  </subjects>
  <dates>
    <date dateType="Issued">2019-11-05</date>
  </dates>
  <resourceType resourceTypeGeneral="Text">Journal article</resourceType>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/3837365</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.3390/data4040147</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;Earth Observation Data Cubes (EODC) have emerged as a promising solution to efficiently and effectively handle Big Earth Observation (EO) Data generated by satellites and made freely and openly available from different data repositories. The aim of this Special Issue, &amp;ldquo;Earth Observation Data Cube&amp;rdquo;, in&amp;nbsp;Data,&amp;nbsp;is to present the latest advances in EODC development and implementation, including innovative approaches for the exploitation of satellite EO data using multi-dimensional (e.g., spatial, temporal, spectral) approaches. This Special Issue contains 14 articles covering a wide range of topics such as Synthetic Aperture Radar (SAR), Analysis Ready Data (ARD), interoperability, thematic applications (e.g., land cover, snow cover mapping), capacity development, semantics, processing techniques, as well as national implementations and best practices. These papers made significant contributions to the advancement of a more Open and Reproducible Earth Observation Science, reducing the gap between users&amp;rsquo; expectations for decision-ready products and current Big Data analytical capabilities, and ultimately unlocking the information power of EO data by transforming them into actionable knowledge&lt;/p&gt;</description>
  </descriptions>
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