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Navigating challenges in spatial machine learning: Validation, uncertainty, algorithms, and reproducibilityOpen Access

Nowosad, Jakub; Bonannella, Carmelo; Görgen, Darius; Jemeljanova, Marta; Kattenborn, Teja; Linnenbrink, Jan; Meyer, Hanna; Nussbaum, Madlene; Patelli, Luca; Simoes, Rolf; Uuemaa, Evelyn

Research article (journal) | Peer reviewed

Details about the publication

Journal: Erdkunde
Status: Published
Release year: 2026
Language in which the publication is written: English
Keywords:  model validation; model performance metrics; uncertainty; machine learning algorithms; geospatial software; standardized protocols

Authors from the University of Münster

Görgen, Darius Andreas
Professorship of Remote Sensing and Spatial Modelling
Linnenbrink, Jan
Professorship of Remote Sensing and Spatial Modelling
Meyer, Hanna
Professorship of Remote Sensing and Spatial Modelling

Projects the publication originates from

CRC TRR 391 - A05: Deep learning in space and time
Duration: 01/10/2024 - 30/06/2028 | 1st Funding period
Funded by: DFG - Collaborative Research Centre
Type of project: Subproject in DFG-joint project hosted outside University of Münster
Preservation and RecognItion of Spatial patterns using Machine learning (PRISM)
Duration: 14/08/2024 - 13/08/2026
Funded by: EC Horizon Europe - Marie Skłodowska-Curie Actions - Postdoctoral Fellowship
Type of project: EU-project hosted at University of Münster
SPP 1374 - Subproject: Learning from the Exploratories to make prediction beyond them: AI-based mapping and explanation of grassland biodiversity and ecosystem… (BEyond)
Duration: 01/08/2023 - 31/07/2027 | 1st Funding period
Funded by: DFG - Priority Programme
Type of project: Subproject in DFG-joint project hosted outside University of Münster