A semi-automated data integration workflow to enable high-throughput crop modelling
Crop simulation models are important tools for yield projection and analysis but are rarely
used for real-time decision support due to persistent bottlenecks in data management and processing workflows to generate input datasets. We present a blueprint for a semi-automated data management workflow that enables high-throughput simulation, integrating diverse source data into a rapid, scalable pipeline. The modular workflow leverages established standards in geospatial science, agronomy, and crop modeling to assemble high-quality inputs for crop models. The blueprint outlines the technical requirements to operationalize crop models, enabling broader applications as decision-support tools.
- Publication type
- Conference contributions
- Title
- A semi-automated data integration workflow to enable high-throughput crop modelling
- Media
- Datenräume in der Land-, Forst- und Ernährungswirtschaft: Chancen für die Zukunft und aktuelle Herausforderungen; Referate der 46. GIL-Jahrestagung, 24. - 25. Februar 2026, Soest, Deutschland
- Authors
- Benjamin M.L. Leroy, Sebastian Burkhart , Joseph Gitahi, Marija Knezevic, Andreas Donauauer, Muhammad Arslan, David Gackstetter, Giada Matheisen, Sentholt Asseng, Thomas Kolbe, Patrick Noack
- Publisher
- J. Dörr, T. Steckel, A. Wübbeke, V. Kruder-Motsch, C. Meltebrink, M. Gültas, H. Floto
- Pages
- 360 - 365
- Publication date
- 25.02.2026