The Coastal Imaging Research Network (CIRN)

Palmsten, Margaret L.; Brodie, Katherine L.

doi:10.3390/rs14030453

Cited by 17 publications

(4 citation statements)

References 95 publications

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“…The cBathy algorithm (Holman et al [19]; https://github.com/Coastal-Imaging-Research-Network/cBathy-toolbox [44], accessed on 20 January 2020) is based on the linear wave dispersion relationship to estimate depth and thus requires a time series of images with the presence of waves in intermediate or shallow water depths. Images are typically sampled at 1 or 2 Hz over a 17 min collection to yield a burst or stack of images.…”

Section: Cbathy Algorithmmentioning

confidence: 99%

“…The cBathy algorithm, developed by Holman et al [19], is a spectral depth inversion method that is nowadays the most popular algorithm to obtain two-dimensional bathymetries from video stations [6,25,[32][33][34][35][36][37][38][39][40][41][42][43][44]. cBathy is based on the linear wave dispersion relationship, and therefore, its validity is inherently bounded to the increasing degree of wave non-linearity (finite amplitude effects) as waves approach the shore, leading to larger propagation speeds for higher waves [45,46].…”

Section: Introductionmentioning

confidence: 99%

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Video-Based Nearshore Bathymetric Inversion on a Geologically Constrained Mesotidal Beach during Storm Events

et al. 2022

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Although geologically constrained sandy beaches are ubiquitous along wave-exposed coasts, there is still a limited understanding of their morphological response, particularly under storm conditions, which is mainly due to a critical lack of nearshore bathymetry observations. This paper examines the potential to derive bathymetries from video imagery under challenging wave conditions in order to investigate headland control on morphological beach response. For this purpose, a video-based linear depth inversion algorithm is applied to three consecutive weeks of frames collected during daylight hours from a single fixed camera located at La Petite Chambre d’Amour beach (Anglet, SW France). Video-derived bathymetries are compared against in situ topo-bathymetric surveys carried out at the beginning and end of the field experiment in order to assess the performance of the bathymetric estimates. The results show that the rates of accretion/erosion within the surf zone are strongly influenced by the headland, whereas the beach morphological response can be classified into three main regimes depending on the angle of wave incidence θp: (1) under deflection configuration (θp>0°), the alongshore sediment transport was trapped at the updrift side of the headland, promoting sand accretion. (2) Under shadowed configuration (θp<0°), the interruption of the longshore current drove a deficit of sand supply at the downdrift side of the headland, leading to an overall erosion in the surf zone. (3) Under shore-normal configuration (θp=0°), rip channels developed, and up-state beach transition was observed. A comparison between video-derived bathymetries and surveys shows an overall root mean square error (RMSE) around 0.49 to 0.57 m with a bias ranging between −0.36 and −0.29 m. The results show that video-derived bathymetries can provide new insight into the morphological change driven by storm events. The combination of such inferred bathymetry with video-derived surface current data is discussed, showing great potential to address the coupled morphodynamics system under time-varying wave conditions.

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Section: Cbathy Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Video-Based Nearshore Bathymetric Inversion on a Geologically Constrained Mesotidal Beach during Storm Events

et al. 2022

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“…Once rectified, engineering-relevant information can be extracted out of the imagery, including shoreline position, sandbar position, nearshore bathymetry, and surface currents. A number of algorithms have been developed across the community, many of which are openly accessible through the Coastal Imaging Research Network (CIRN), (see Palmsten and Brodie [2022] for a review).…”

Section: Introductionmentioning

confidence: 99%

Applicability of CoastSnap, a crowd-sourced coastal monitoring approach for US Army Corps of Engineers district use

Conery,

Bruder,

Geis

et al. 2023

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This US Army Engineer Research and Development Center, Coastal and Hydraulics Laboratory, technical report details the pilot deployment, accuracy evaluation, and best practices of the citizen-science, coastal-image monitoring program CoastSnap. Despite the need for regular observational data, many coastlines are monitored infrequently due to cost and personnel, and this cell phone-image-based approach represents a new potential data source to districts in addition to providing an outreach opportunity for the public. Requiring minimal hardware and signage, the system is simple to install but requires user-image processing. Analysis shows the CoastSnap-derived shorelines compare well to real-time kinematic and lidar-derived shorelines during low-to-moderate wave conditions (root mean square errors [RMSEs] <10 m). During high-wave conditions, errors are higher (RMSE up to 18 m) but are improved when incorporating wave run-up. Beyond shoreline quantification, images provide other qualitative information such as storm-impact characteristics and timing of the formation of beach scarps. Ultimately, the citizen-science tool is a viable low-cost option to districts for monitoring shorelines and tracking the evolution of coastal projects such as beach nourishments.

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“…In addition, recent efforts have aimed to make these algorithms easy to access and use. Accessibility and use of this algorithms is facilitated by increased robustness, selfadaptation to the data, computational speed, and open availability [13,32,33]. Connecting the collection and analysis of satellite imagery to these depth inversion algorithms and their users remains an open challenge.…”

Section: Introductionmentioning

confidence: 99%

Depth Inversion from Wave Frequencies in Temporally Augmented Satellite Video

et al. 2022

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Optical satellite images of the nearshore water surface offer the possibility to invert water depths and thereby constitute the underlying bathymetry. Depth inversion techniques based on surface wave patterns can handle clear and turbid waters in a variety of global coastal environments. Common depth inversion algorithms require video from shore-based camera stations, UAVs or Xband-radars with a typical duration of minutes and at framerates of 1–2 fps to find relevant wave frequencies. These requirements are often not met by satellite imagery. In this paper, satellite imagery is augmented from a sequence of 12 images of Capbreton, France, collected over a period of ∼1.5 min at a framerate of 1/8 fps by the Pleiades satellite, to a pseudo-video with a framerate of 1 fps. For this purpose, a recently developed method is used, which considers spatial pathways of propagating waves for temporal video reconstruction. The augmented video is subsequently processed with a frequency-based depth inversion algorithm that works largely unsupervised and is openly available. The resulting depth estimates approximate ground truth with an overall depth bias of −0.9 m and an interquartile range of depth errors of 5.1 m. The acquired accuracy is sufficiently high to correctly predict wave heights over the shoreface with a numerical wave model and to find hotspots where wave refraction leads to focusing of wave energy that has potential implications for coastal hazard assessments. A more detailed depth inversion analysis of the nearshore region furthermore demonstrates the possibility to detect sandbars. The combination of image augmentation with a frequency-based depth inversion method shows potential for broad application to temporally sparse satellite imagery and thereby aids in the effort towards globally available coastal bathymetry data.

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The Coastal Imaging Research Network (CIRN)

Cited by 17 publications

References 95 publications

Video-Based Nearshore Bathymetric Inversion on a Geologically Constrained Mesotidal Beach during Storm Events

Video-Based Nearshore Bathymetric Inversion on a Geologically Constrained Mesotidal Beach during Storm Events

Applicability of CoastSnap, a crowd-sourced coastal monitoring approach for US Army Corps of Engineers district use

Depth Inversion from Wave Frequencies in Temporally Augmented Satellite Video

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