Coastal process understanding through automated identification of recurring surface dynamics in permanent laser scanning data of a sandy beach

Hulskemper, Daan; Antolínez, José A. Á.; Lindenbergh, Roderik; Anders, Katharina

doi:10.5194/esurf-14-329-2026

Articles | Volume 14, issue 3

https://doi.org/10.5194/esurf-14-329-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/esurf-14-329-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 14, issue 3

Research article

| Highlight paper

|

08 May 2026

Research article | Highlight paper |

| 08 May 2026

Coastal process understanding through automated identification of recurring surface dynamics in permanent laser scanning data of a sandy beach

Daan Hulskemper, José A. Á. Antolínez, Roderik Lindenbergh, and Katharina Anders

Data sets

Grouped 4D Objects-By-Change of a Sandy Beach Derived from the Noordwijk Permanent Laser Scanning Dataset Daan Hulskemper et al. https://doi.org/10.4121/7cf573ec-ce73-4dcf-86ea-553f159c417c

4D spatio-temporal laser scan dataset of the beach-dune system in Noordwijk, NL Sander Vos et al. https://doi.org/10.4121/1AAC46FB-7900-4D4C-A099-D2CE354811D2.V2

Model code and software

py4dgeo: library for change analysis in 4D point clouds Bernhard Höfle et al. https://github.com/3dgeo-heidelberg/py4dgeo

Editorial statement

Hulskemper et al. report on a data-driven investigation and predictive modelling of Earth surface dynamics captured by high-resolution 4D remote sensing datasets. Their study shows how to integrate massive remote sensing observations to increase our process understanding in coastal morphodynamic research.