Implement different (spatial) cross-validation strategies - keep time in mind
- random (already there)
- spatial blocks
- feature space
- geographic space
- inverse sampling-intensity weighted cross-validation (ISIW-CV) on the training dataset
- space-time blocks (spatio-temporal CV)
Tian, X., De Bruin, S., Simoes, R., Isik, M. S., Minarik, R., Ho, Y.-F., . . . Hengl, T. (2025). Spatiotemporal prediction of soil organic carbon density in Europe (2000–2022) using earth observation and machine learning. PeerJ, 13, e19605. doi:10.7717/peerj.19605
De Bruin, S., Brus, D. J., Heuvelink, G. B. M., Van Ebbenhorst Tengbergen, T., & Wadoux, A. M. J. C. (2022). Dealing with clustered samples for assessing map accuracy by cross-validation. Ecological Informatics, 69, 101665. doi:10.1016/j.ecoinf.2022.101665
Ludwig, M., Moreno‐Martinez, A., Hölzel, N., Pebesma, E., & Meyer, H. (2023). Assessing and improving the transferability of current global spatial prediction models. Global Ecology and Biogeography, 32(3), 356-368. doi:10.1111/geb.13635
Nelson, J. A., Walther, S., Gans, F., Kraft, B., Weber, U., Novick, K., . . . Jung, M. (2024). X-BASE: the first terrestrial carbon and water flux products from an extended data-driven scaling framework, FLUXCOM-X. Biogeosciences, 21(22), 5079-5115. doi:10.5194/bg-21-5079-2024
Implement different (spatial) cross-validation strategies - keep time in mind
Tian, X., De Bruin, S., Simoes, R., Isik, M. S., Minarik, R., Ho, Y.-F., . . . Hengl, T. (2025). Spatiotemporal prediction of soil organic carbon density in Europe (2000–2022) using earth observation and machine learning. PeerJ, 13, e19605. doi:10.7717/peerj.19605
De Bruin, S., Brus, D. J., Heuvelink, G. B. M., Van Ebbenhorst Tengbergen, T., & Wadoux, A. M. J. C. (2022). Dealing with clustered samples for assessing map accuracy by cross-validation. Ecological Informatics, 69, 101665. doi:10.1016/j.ecoinf.2022.101665
Ludwig, M., Moreno‐Martinez, A., Hölzel, N., Pebesma, E., & Meyer, H. (2023). Assessing and improving the transferability of current global spatial prediction models. Global Ecology and Biogeography, 32(3), 356-368. doi:10.1111/geb.13635
Nelson, J. A., Walther, S., Gans, F., Kraft, B., Weber, U., Novick, K., . . . Jung, M. (2024). X-BASE: the first terrestrial carbon and water flux products from an extended data-driven scaling framework, FLUXCOM-X. Biogeosciences, 21(22), 5079-5115. doi:10.5194/bg-21-5079-2024