Nearshore Depth Inversion Bathymetry from Coastal Webcam: A Novel Technique Based on Wave Celerity Estimation

Nearshore bathymetry is key to most oceanographic studies and coastal engineering works. This work proposes a new methodology to assess nearshore wave celerity and infer bathymetry from video images. Shoaling and breaking wave patterns were detected on the Timestacks distinctly, and wave celerity wa...

Full description

Saved in:
Bibliographic Details
Main Authors: Umberto Andriolo, Alberto Azevedo, Gil Gonçalves, Rui Taborda
Format: Article
Language:English
Published: MDPI AG 2025-07-01
Series:Remote Sensing
Subjects:
Online Access:https://www.mdpi.com/2072-4292/17/13/2274
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1849704604102557696
author Umberto Andriolo
Alberto Azevedo
Gil Gonçalves
Rui Taborda
author_facet Umberto Andriolo
Alberto Azevedo
Gil Gonçalves
Rui Taborda
author_sort Umberto Andriolo
collection DOAJ
description Nearshore bathymetry is key to most oceanographic studies and coastal engineering works. This work proposes a new methodology to assess nearshore wave celerity and infer bathymetry from video images. Shoaling and breaking wave patterns were detected on the Timestacks distinctly, and wave celerity was estimated from wave trajectories. The wave type separation enabled the implementation of specific domain formulations for depth inversion: linear for shoaling and non-linear for breaking waves. The technique was validated over a rocky bottom using video acquisition of an online streaming webcam for a period of two days, with significant wave heights varying between 1.7 m and 3.5 m. The results were corroborated in comparison to ground-truth data available up to a depth of 10 m, yielding a mean bias of 0.05 m and a mean root mean square error (RMSE) of 0.43 m. In particular, RMSE was lower than 15% in the outer surf zone, where breaking processes occur. Overall, the depth-normalized RMSE was always lower than 20%, with the major inaccuracy due to some local depressions, which were not resolved. The developed technique can be readily applied to images collected by coastal monitoring stations worldwide and is applicable to drone video acquisitions.
format Article
id doaj-art-1cee1f0dc6434dbb96de2ec69b843759
institution DOAJ
issn 2072-4292
language English
publishDate 2025-07-01
publisher MDPI AG
record_format Article
series Remote Sensing
spelling doaj-art-1cee1f0dc6434dbb96de2ec69b8437592025-08-20T03:16:42ZengMDPI AGRemote Sensing2072-42922025-07-011713227410.3390/rs17132274Nearshore Depth Inversion Bathymetry from Coastal Webcam: A Novel Technique Based on Wave Celerity EstimationUmberto Andriolo0Alberto Azevedo1Gil Gonçalves2Rui Taborda3INESC Coimbra, Department of Electrical and Computer Engineering, Polo II, 3030-790 Coimbra, PortugalNational Laboratory for Civil Engineering, Hydraulics and Environment Department, LNEC, 1700-066 Lisbon, PortugalINESC Coimbra, Department of Electrical and Computer Engineering, Polo II, 3030-790 Coimbra, PortugalInstituto Dom Luiz, Faculdade de Ciências, Universidade de Lisboa, Campo Grande, 1749-016 Lisbon, PortugalNearshore bathymetry is key to most oceanographic studies and coastal engineering works. This work proposes a new methodology to assess nearshore wave celerity and infer bathymetry from video images. Shoaling and breaking wave patterns were detected on the Timestacks distinctly, and wave celerity was estimated from wave trajectories. The wave type separation enabled the implementation of specific domain formulations for depth inversion: linear for shoaling and non-linear for breaking waves. The technique was validated over a rocky bottom using video acquisition of an online streaming webcam for a period of two days, with significant wave heights varying between 1.7 m and 3.5 m. The results were corroborated in comparison to ground-truth data available up to a depth of 10 m, yielding a mean bias of 0.05 m and a mean root mean square error (RMSE) of 0.43 m. In particular, RMSE was lower than 15% in the outer surf zone, where breaking processes occur. Overall, the depth-normalized RMSE was always lower than 20%, with the major inaccuracy due to some local depressions, which were not resolved. The developed technique can be readily applied to images collected by coastal monitoring stations worldwide and is applicable to drone video acquisitions.https://www.mdpi.com/2072-4292/17/13/2274coastal hydrodynamicsbeachremote sensingvideo monitoringTimestack images
spellingShingle Umberto Andriolo
Alberto Azevedo
Gil Gonçalves
Rui Taborda
Nearshore Depth Inversion Bathymetry from Coastal Webcam: A Novel Technique Based on Wave Celerity Estimation
Remote Sensing
coastal hydrodynamics
beach
remote sensing
video monitoring
Timestack images
title Nearshore Depth Inversion Bathymetry from Coastal Webcam: A Novel Technique Based on Wave Celerity Estimation
title_full Nearshore Depth Inversion Bathymetry from Coastal Webcam: A Novel Technique Based on Wave Celerity Estimation
title_fullStr Nearshore Depth Inversion Bathymetry from Coastal Webcam: A Novel Technique Based on Wave Celerity Estimation
title_full_unstemmed Nearshore Depth Inversion Bathymetry from Coastal Webcam: A Novel Technique Based on Wave Celerity Estimation
title_short Nearshore Depth Inversion Bathymetry from Coastal Webcam: A Novel Technique Based on Wave Celerity Estimation
title_sort nearshore depth inversion bathymetry from coastal webcam a novel technique based on wave celerity estimation
topic coastal hydrodynamics
beach
remote sensing
video monitoring
Timestack images
url https://www.mdpi.com/2072-4292/17/13/2274
work_keys_str_mv AT umbertoandriolo nearshoredepthinversionbathymetryfromcoastalwebcamanoveltechniquebasedonwavecelerityestimation
AT albertoazevedo nearshoredepthinversionbathymetryfromcoastalwebcamanoveltechniquebasedonwavecelerityestimation
AT gilgoncalves nearshoredepthinversionbathymetryfromcoastalwebcamanoveltechniquebasedonwavecelerityestimation
AT ruitaborda nearshoredepthinversionbathymetryfromcoastalwebcamanoveltechniquebasedonwavecelerityestimation