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<p>The unprecedented and continuously growing volume of Earth Observation (EO) and geospatial data has necessitated a paradigm change where compute is collocated with the data archives in public clouds. However, as no single cloud platform can host all of this data, federated processing solutions that work across multiple cloud platforms are becoming increasingly relevant. A community-based approach to federated processing has started using openEO, a common Application Programming Interface (API) and set of well-defined processes that simplifies reuse and provides a valuable level of abstraction when handling large EO data volumes. We present key concepts for federated processing and related interoperability aspects based on <i>openEO Platform</i>, a federated public cloud platform.</p>

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Federated and reusable processing of Earth observation data

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年2月1日

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  • Matthias Mohr,
  • Edzer Pebesma,
  • Jeroen Dries,
  • Stefaan Lippens,
  • Bram Janssen,
  • Daniel Thiex,
  • Grega Milcinski,
  • Benjamin Schumacher,
  • Christian Briese,
  • Michele Claus,
  • Alexander Jacob,
  • Paulo Sacramento,
  • Patrick Griffiths

摘要

The unprecedented and continuously growing volume of Earth Observation (EO) and geospatial data has necessitated a paradigm change where compute is collocated with the data archives in public clouds. However, as no single cloud platform can host all of this data, federated processing solutions that work across multiple cloud platforms are becoming increasingly relevant. A community-based approach to federated processing has started using openEO, a common Application Programming Interface (API) and set of well-defined processes that simplifies reuse and provides a valuable level of abstraction when handling large EO data volumes. We present key concepts for federated processing and related interoperability aspects based on openEO Platform, a federated public cloud platform.