Articles | Volume 9, issue 1
https://doi.org/10.5194/esurf-9-89-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/esurf-9-89-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
19 Feb 2021
Research article |
| 19 Feb 2021
| 19 Feb 2021
Coastal change patterns from time series clustering of permanent laser scan data
Department of Geoscience and Remote Sensing, Delft University of Technology, Delft, the Netherlands
Roderik Lindenbergh
Department of Geoscience and Remote Sensing, Delft University of Technology, Delft, the Netherlands
Sander Vos
Department of Hydraulic Engineering, Delft University of Technology, Delft, the Netherlands
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Cited
19 citations as recorded by crossref.
- Machine Learning-Based Algorithms to Knowledge Extraction from Time Series Data: A Review G. Ciaburro & G. Iannace
- Full four-dimensional change analysis of topographic point cloud time series using Kalman filtering L. Winiwarter et al.
- Long-Term Shoreline Change Monitoring Using Remote Sensing Techniques and GIS Analysis: a Case Study of Gorgan Bay, Caspian Sea (1985–2025) B. Ebadati et al.
- Temporal aggregation of point clouds improves permanent laser scanning of landslides in forested areas R. Tabernig et al.
- Identifying topographic changes at the beach using multiple years of permanent laser scanning M. Kuschnerus et al.
- Impacts of atmospheric turbulence on optic measurements over heterogeneous flat terrain: insights from large eddy simulations G. Kermarrec et al.
- Associations between the thermal spring timing variability and atmospheric teleconnection patterns over the past six decades in Finland S. Kaboli et al.
- LCD-Net: A Lightweight Remote Sensing Change Detection Network Combining Feature Fusion and Gating Mechanism W. Liu et al.
- Coastal process understanding through automated identification of recurring surface dynamics in permanent laser scanning data of a sandy beach D. Hulskemper et al.
- How Big Data Can Help to Monitor the Environment and to Mitigate Risks due to Climate Change: A review J. Montillet et al.
- py4dgeo: Open-source scientific software for topographic change analysis in 3D/4D geographic point clouds K. Anders et al.
- Statistically assessing vertical change on a sandy beach from permanent laser scanning time series M. Kuschnerus et al.
- Coastline detection in satellite imagery: A deep learning approach on new benchmark data C. Seale et al.
- A high-resolution 4D terrestrial laser scan dataset of the Kijkduin beach-dune system, The Netherlands S. Vos et al.
- WRBSNet: A Novel Sea–Land Segmentation Network With a Wider Range of Batch Sizes Y. Li et al.
- Navigating coastal resilience: Exploring population density and coastal distance dynamics along the gold coast J. Murphy et al.
- Non-uniform dune development in the presence of standalone beach buildings S. Vos et al.
- Permanent Laser Scanner and Synthetic Aperture Radar Data: Correlation Characterisation at a Sandy Beach V. Di Biase et al.
- Permanent terrestrial laser scanning for near-continuous environmental observations: Systems, methods, challenges and applications R. Lindenbergh et al.
19 citations as recorded by crossref.
- Machine Learning-Based Algorithms to Knowledge Extraction from Time Series Data: A Review G. Ciaburro & G. Iannace
- Full four-dimensional change analysis of topographic point cloud time series using Kalman filtering L. Winiwarter et al.
- Long-Term Shoreline Change Monitoring Using Remote Sensing Techniques and GIS Analysis: a Case Study of Gorgan Bay, Caspian Sea (1985–2025) B. Ebadati et al.
- Temporal aggregation of point clouds improves permanent laser scanning of landslides in forested areas R. Tabernig et al.
- Identifying topographic changes at the beach using multiple years of permanent laser scanning M. Kuschnerus et al.
- Impacts of atmospheric turbulence on optic measurements over heterogeneous flat terrain: insights from large eddy simulations G. Kermarrec et al.
- Associations between the thermal spring timing variability and atmospheric teleconnection patterns over the past six decades in Finland S. Kaboli et al.
- LCD-Net: A Lightweight Remote Sensing Change Detection Network Combining Feature Fusion and Gating Mechanism W. Liu et al.
- Coastal process understanding through automated identification of recurring surface dynamics in permanent laser scanning data of a sandy beach D. Hulskemper et al.
- How Big Data Can Help to Monitor the Environment and to Mitigate Risks due to Climate Change: A review J. Montillet et al.
- py4dgeo: Open-source scientific software for topographic change analysis in 3D/4D geographic point clouds K. Anders et al.
- Statistically assessing vertical change on a sandy beach from permanent laser scanning time series M. Kuschnerus et al.
- Coastline detection in satellite imagery: A deep learning approach on new benchmark data C. Seale et al.
- A high-resolution 4D terrestrial laser scan dataset of the Kijkduin beach-dune system, The Netherlands S. Vos et al.
- WRBSNet: A Novel Sea–Land Segmentation Network With a Wider Range of Batch Sizes Y. Li et al.
- Navigating coastal resilience: Exploring population density and coastal distance dynamics along the gold coast J. Murphy et al.
- Non-uniform dune development in the presence of standalone beach buildings S. Vos et al.
- Permanent Laser Scanner and Synthetic Aperture Radar Data: Correlation Characterisation at a Sandy Beach V. Di Biase et al.
- Permanent terrestrial laser scanning for near-continuous environmental observations: Systems, methods, challenges and applications R. Lindenbergh et al.
Saved (final revised paper)
Latest update: 18 May 2026
Short summary
Sandy coasts are areas that undergo a lot of changes, which are caused by different influences, such as tides, wind or human activity. Permanent laser scanning is used to generate a three-dimensional representation of a part of the coast continuously over an extended period. By comparing three unsupervised learning algorithms, we develop a methodology to analyse the resulting data set and derive which processes are dominating changes in the beach and dunes.
Sandy coasts are areas that undergo a lot of changes, which are caused by different influences,...
