Increasing literacy, use and reuse of geospatial machine learning models

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Increasing literacy, use and reuse of geospatial machine learning models
GeoAI, Machine learning, spatio-temporal data, Open Science, reproducibility
Raul Zurita-Milla, University of Twente
24 months
tba
Funding awarded
€ 154,315

Public Summary
Geospatial machine learning (ML) models are widely used in natural and engineering science (NES). These models and the methods to develop them rapidly evolve, making it challenging to keep up with them and reap their benefits. Besides this, many NES researchers do not have the required geospatial knowledge to develop, apply and (re)use these models because “spatial is special”, and they do not know how to document their creative process, making model (re)use unnecessarily hard. To address these issues, we propose developing training modules that increase geospatial ML literacy and geospatial ML models' (re)usability.






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