An Automatic Procedure for Dune Foot Position Detection: Application to the Dutch Coast

Diamantidou, Eleni; Santinelli, Giorgio; Giardino, Alessio; Stronkhorst, J.; Vries, Sierd de

doi:10.2112/jcoastres-d-19-00056.1

Cited by 7 publications

(16 citation statements)

References 17 publications

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“…The comparable results between the second derivative method and the machine learning method of pybeach indicate that the results converge for two different methods when applied to a large dataset. It is expected that other methods based on the profile slope 19 – 23 , 32 would generate similar results. However, methods that use distinctly different calculation techniques, like those based on volume 24 , profile shape 33 and, especially, based on vegetation 14 , 25 might show varying results and would be interesting to explore in future studies.…”

Section: Methodsmentioning

confidence: 96%

“…Among the slope-based methods, which are most commonly used, the second derivative method was selected. In a previous study, this method was applied to the Jarkus dataset and showed robust results compared to in situ visual observations 32 . Additionally, the recent, innovative and well-documented pybeach method based on machine learning was added to diversify the analysis in an effort to increase the confidence in the observed dune toe development trends.…”

Section: Methodsmentioning

confidence: 98%

“…Therefore, methods based on digital elevation models (DEMs) 28 – 30 and vegetation 14 , 25 were excluded. Applicable methods include those based on profile slope 19 – 23 , 32 , profile volume 24 and profile shape 33 . Among the slope-based methods, which are most commonly used, the second derivative method was selected.…”

Section: Methodsmentioning

confidence: 99%

“…The second derivative method was developed and tested by Diamantidou et al (2020) using the Jarkus dataset. A comparison with in situ visual observations showed that the method selects the dune toe consistently 32 . An example of measured profiles and derived dune toes is presented in Fig.…”

Section: Introductionmentioning

confidence: 98%

“…It should be noted that the available methods have varying degrees of subjectivity depending on user input 26 . The results presented in this research were obtained by analysing dune toes extracted with the second derivative method 32 from the Dutch Jarkus dataset. Additionally, the machine learning method of pybeach 31 was used to verify that a different extraction method gives similar results.…”

Section: Introductionmentioning

confidence: 99%

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Sea level rise outpaced by vertical dune toe translation on prograding coasts

IJzendoorn

Vries

Hallin

et al. 2021

Sci Rep

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Sea level is rising due to climate change and is expected to influence the development and dynamics of coastal dunes. However, the anticipated changes to coastal dunes have not yet been demonstrated using field data. Here, we provide evidence of dune translation that is characterized by a linear increase of the dune toe elevation on the order of 13–15 mm/year during recent decades along the Dutch coast. This rate of increase is a remarkable 7–8 times greater than the measured sea level rise. The observed vertical dune toe translation coincides with seaward movement of the dune toe (i.e., progradation), which shows similarities to prograding coasts in the Holocene both along the Dutch coast and elsewhere. Thus, we suspect that other locations besides the Dutch coast might also show such large ratios between sea level rise and dune toe elevation increase. This phenomenon might significantly influence the expected impact of sea level rise and climate change adaptation measures.

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Section: Methodsmentioning

confidence: 96%

Section: Methodsmentioning

confidence: 98%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Sea level rise outpaced by vertical dune toe translation on prograding coasts

IJzendoorn

Vries

Hallin

et al. 2021

Sci Rep

Self Cite

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Dune toe dynamics along the urbanised macro‐tidal coast of Belgium

Strypsteen

Dan

Verwaest

et al. 2023

Earth Surf Processes Landf

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The dynamics of the dune toe along the urbanised 65 km macro‐tidal coast of Belgium has been examined based on (bi‐)annual cross‐shore profiles derived from airborne LiDAR surveys conducted between 2000 and 2019. Results indicate that the average dune toe level is located at +5.9 m Tweede Algemene Waterpassing (TAW, Belgian Ordnance Datum), which is 1 m lower than the conventional dune toe level. However, this level is not static but rather increasing over time with an average rate of 2.3 cm/year, making it comparable with coastal areas along western Europe. Both landward retreat and seaward progradation of the dune toes are observed, with rates up to 2 m/year. The analysis revealed that dune growth is primarily facilitated by the development of incipient or embryonic dunes, new foredunes and modifications to the stoss slope of the original dune profile. Half of the sea‐fronting dunes were observed to be developed by brushwood fences, which had a positive effect on dune growth. At some locations, incipient dune development and shoreline progradation were observed seaward of old foredunes. Other dune regions were characterised by natural dune blowouts and management activities for recreational purposes. Dune toe reinforcements were implemented in the west to stabilise the dune toe and prevent erosion by waves. However, it was noted that if the adjacent beach accreted because of natural growth or periodic nourishment, incipient dunes could form in front of the reinforcement.

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