Articles | Volume 24, issue 11
https://doi.org/10.5194/nhess-24-4145-2024
https://doi.org/10.5194/nhess-24-4145-2024
Research article
 | 
28 Nov 2024
Research article |  | 28 Nov 2024

Changing sea level, changing shorelines: integration of remote-sensing observations at the Terschelling barrier island

Benedikt Aschenneller, Roelof Rietbroek, and Daphne van der Wal

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This preprint is open for discussion and under review for Biogeosciences (BG).
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Cited articles

Adebisi, N., Balogun, A.-L., Mahdianpari, M., and Min, T. H.: Assessing the Impacts of Rising Sea Level on Coastal Morpho-Dynamics with Automated High-Frequency Shoreline Mapping Using Multi-Sensor Optical Satellites, Remote Sens.-Basel, 13, 3587, https://doi.org/10.3390/rs13183587, 2021. a
Almar, R., Boucharel, J., Graffin, M., Abessolo, G. O., Thoumyre, G., Papa, F., Ranasinghe, R., Montano, J., Bergsma, E. W. J., Baba, M. W., and Jin, F.-F.: Influence of El Niño on the Variability of Global Shoreline Position, Nat. Commun., 14, 3133, https://doi.org/10.1038/s41467-023-38742-9, 2023. a
Almeida, L. P., Almar, R., Bergsma, E. W. J., Berthier, E., Baptista, P., Garel, E., Dada, O. A., and Alves, B.: Deriving High Spatial-Resolution Coastal Topography From Sub-meter Satellite Stereo Imagery, Remote Sens.-Basel, 11, 590, https://doi.org/10.3390/rs11050590, 2019. a
Almeida, L. P., Efraim de Oliveira, I., Lyra, R., Scaranto Dazzi, R. L., Martins, V. G., and Henrique da Fontoura Klein, A.: Coastal Analyst System from Space Imagery Engine (CASSIE): Shoreline Management Module, Environ. Modell. Softw., 140, 105033, https://doi.org/10.1016/j.envsoft.2021.105033, 2021. a, b, c, d, e, f, g, h
Almonacid-Caballer, J., Sánchez-García, E., Pardo-Pascual, J. E., Balaguer-Beser, A. A., and Palomar-Vázquez, J.: Evaluation of Annual Mean Shoreline Position Deduced from Landsat Imagery as a Mid-Term Coastal Evolution Indicator, Mar. Geol., 372, 79–88, https://doi.org/10.1016/j.margeo.2015.12.015, 2016. a
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Shorelines retreat or advance in response to sea level changes, subsidence or uplift of the ground, and morphological processes (sedimentation and erosion). We show that the geometrical influence of each of these drivers on shoreline movements can be quantified by combining different remote sensing observations, including radar altimetry, lidar and optical satellite images. The focus here is to illustrate the uncertainties of these observations by comparing datasets that cover similar processes.
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