Articles | Volume 18, issue 2
https://doi.org/10.5194/essd-18-1275-2026
https://doi.org/10.5194/essd-18-1275-2026
Data description article
 | 
19 Feb 2026
Data description article |  | 19 Feb 2026

Soil surface change data of high spatio-temporal resolution from the plot to the catchment scale

Lea Epple, Oliver Grothum, Anne Bienert, and Anette Eltner

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Cited articles

Batista, P. V., Davies, J., Silva, M. L., and Quinton, J. N.: On the evaluation of soil erosion models: Are we doing enough?, Earth-Sci. Rev., 197, 102898, https://doi.org/10.1016/j.earscirev.2019.102898, 2019. 
Blanch, X., Guinau, M., Eltner, A., and Abellan, A.: A cost-effective image-based system for 3D geomorphic monitoring: An application to rockfalls, Geomorphology, 449, 109065, https://doi.org/10.1016/j.geomorph.2024.109065, 2024. 
Blanch, X., Jäschke, A., Elias, M., and Eltner, A.: Subpixel Automatic Detection of GCP Coordinates in Time-Lapse Images Using a Deep Learning Keypoint Network, IEEE Trans. Geosci. Remote Sens., 63, 1–14, https://doi.org/10.1109/TGRS.2024.3514854, 2025. 
Ehrhardt, A., Deumlich, D., and Gerke, H. H.: Soil Surface Micro-Topography by Structure-from-Motion Photogrammetry for Monitoring Density and Erosion Dynamics, Front. Environ. Sci., 9, https://doi.org/10.3389/fenvs.2021.737702, 2022. 
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Short summary
The present study offers a unique, nested, high-resolution dataset that captures soil surface changes every 20 seconds during rainfall events, as well as over seasonal variations, across a range of spatial scales – plot, slope, and catchment. It was collected over a period of 3.5 years and facilitated by a camera-based approach. This open-access resource assists scientists in evaluating and refining existing models, improving process understanding, and training artificial intelligence.
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