Urban beach evolution in Saint Louis, Senegal (West Africa) using shore-based camera video monitoring as a management tool
Bibliographic record
Abstract
This study investigates the effectiveness of shore-based camera video monitoring for tracking nearshore waves and morphological evolution of an urban sandy beach, Saint Louis, Senegal (West Africa) within the framework of an engineering protection project. The research aims to support coastal monitoring initiatives for erosion management by employing various methods to estimate parameters such as wave characteristics, shoreline position, and bathymetry using video cameras. Beyond the typical seasonal variations induced by the oceanic regime, video observations well capture wave variations, and show significant morphological responses, including the gradual migration of the inner sandbar from intermediate depths towards the upper beach over several months during the summer of 2021. These findings underscore the need for a deeper understanding of the mechanisms governing these exchanges, and highlight the importance of improving observations of the morphological land-sea continuum through video technology and potentially satellite tools at scarce documented sites such as encountered in developing countries. Such advances are critical to the development of more effective, data-driven coastal management strategies. • Our video observations reveal that sandbar dynamics are crucial for beach nourishment and wave energy attenuation, vital for coastal stability. • This study shows that shore-based video monitoring is a cost-effective method to monitor waves, morphology, and aid in erosion management. • Waves, shoreline, and bathymetry were monitored using camera video in Saint Louis, Senegal, as part of a coastal protection project.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".