Published in Preprint, 2025
Model-agnostic workflow to quantify the contributions of the modelling choices to spatial predictions
Recommended citation: Corinna Perchtold, Jeremy Rohmer, Augustin Thomas, Julie Lions. Which modelling choices shape your interpolation map? An approach based on optimal transport sensitivity analysis. Geoscientific Model Development. Submitted
Published in Spatial Statistics, 2025
Efficient bayesian spatially varying coefficients modeling for censored data using the vecchia approximation
Recommended citation: Idir Mohamed Yacine, Romary Thomas. Efficient bayesian spatially varying coefficients modeling for censored data using the vecchia approximation. Spatial Statistics. Submitted
Published in Ecological Informatics, 2025
Importance ranking of data and model uncertainties in quantile regression forest-based spatial predictions when data are sparse, imprecise and clustered
Recommended citation: Rohmer, J. (2025). Importance ranking of data and model uncertainties in quantile regression forest-based spatial predictions when data are sparse, imprecise and clustered. Ecological Informatics. doi:10.1016/j.ecoinf.2025.103459 https://www.sciencedirect.com/science/article/pii/S1574954125004686
Published in Lecture Notes in Networks and Systems, 2024
Recommended citation: Labourg, P., Destercke, S., Guillaume, R., Rohmer, J., Quost, B., Belbèze, S. (2024). Geospatial Uncertainties: A Focus on Intervals and Spatial Models Based on Inverse Distance Weighting. In: Lesot, MJ., et al. Information Processing and Management of Uncertainty in Knowledge-Based Systems. IPMU 2024. Lecture Notes in Networks and Systems, vol 1174. Springer, Cham. https://doi.org/10.1007/978-3-031-74003-9_30 https://doi.org/10.1007/978-3-031-74003-9_30
Published in SOIL, 2024
Insights into the prediction uncertainty of machine-learning-based digital soil mapping through a local attribution approach
Recommended citation: Rohmer, J., Belbeze, S., and Guyonnet, D.: Insights into the prediction uncertainty of machine-learning-based digital soil mapping through a local attribution approach, SOIL, 10, 679–697, https://doi.org/10.5194/soil-10-679-2024, 2024. https://soil.copernicus.org/articles/10/679/2024/
Published in Journal of Geochemical Exploration, 2023
A literature review of methods used to establish urban soil geochemical background
Recommended citation: Belbèze, S., Rohmer, J., Négrel, P., Guyonnet, D. (2023). Defining urban soil geochemical backgrounds: A review for application to the French context; Journal of Geochemical Exploration. 254, 107298. https://www.sciencedirect.com/science/article/abs/pii/S0375674223001450