We are pleased to announce our new publication in Earth Surface Dynamics: 

“Coastal process understanding through automated identification of recurring surface dynamics in permanent laser scanning data of a sandy beach” by Daan Hulskemper, José A. Á. Antolínez, Roderik Lindenbergh, and Katharina Anders. 

The study presents a fully automated workflow for identifying and classifying recurring coastal surface dynamics from high resolution 4D laser scanning time series. By combining 4D Objects-by-Change with unsupervised machine learning methods, the approach enables the extraction and organization of thousands of short-term geomorphic processes from permanent terrestrial laser scanning observations. 

Applied to a three-year permanent laser scanning dataset from a sandy beach in the Netherlands, the method reveals characteristic patterns such as berm formation, erosion processes, and human interventions including bulldozer activity. The results demonstrate how dense 4D remote sensing datasets can improve our understanding of coastal morphodynamics and support future data driven investigations of environmental change. 

The article is available open access here: https://doi.org/10.5194/esurf-14-329-2026

Hulskemper, D., Antolínez, J. A. Á., Lindenbergh, R., & Anders, K. (2026): Coastal process understanding through automated identification of recurring surface dynamics in permanent laser scanning data of a sandy beach. Earth Surf. Dynam., 14(3), 329-359. DOI: 10.5194/esurf-14-329-2026.