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A multi-talented datacube: integrating, processing and presenting big geodata for the agricultural end user

Zusammenfassung

While scientific methods leveraging Earth Observation for agriculture are abundant, their actual application in Germany remains scarce. A key challenge in this context is to connect the end users to the data without the many technical obstacles. Therefore, we present a versatile platform that not only integrates and processes big geodata of highly diverse origin and type, but also provides access to these resources in ways that reflect the individual user’s requirements and expertise. Based on free and open-source software building blocks, our datacube facilitates scientific computation through R and Python environments or direct API access, including emergent technologies such as openEO, STAC, and COG. At the same time, the results are delivered to easy-to-use applications that adequately present them to non-technical experts. We detail the architecture of the system and demonstrate a use case serving computed plant vitality information directly to farmers in the field.

Beschreibung

Friedrich, Christoph; Löw, Johannes; Otte, Insa; Hill, Steven; Förtsch, Sebastian; Schwalb-Willmann, Jakob; Gessner, Ursula; Schierghofer, Christoph; Truckenbrodt, Sina; Schonert, Eric; Piernicke, Thomas; Assmann, Denise; Conrad, Christopher; Thiel, Michael (2024): A multi-talented datacube: integrating, processing and presenting big geodata for the agricultural end user. 44. GIL - Jahrestagung, Biodiversität fördern durch digitale Landwirtschaft. DOI: 10.18420/giljt2024_36. Bonn: Gesellschaft für Informatik e.V.. ISSN: 2944-7682. PISSN: 1617-5468. ISBN: 978-3-88579-738-8. pp. 251-256. Stuttgart. 27.-28. Februar 2024

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