Fixed video camera systems are consistently prone to importune motions over time due to either thermal effects or mechanical factors. Even subtle displacements are mostly overlooked or ignored, although they can lead to large geo-rectification errors. This paper describes a simple and efficient method to stabilize an either continuous or sub-sampled image sequence based on feature matching and sub-pixel cross-correlation techniques. The method requires the presence and identification of different land-sub-image regions containing static recognizable features, such as corners or salient points, referred to as keypoints. A Canny edge detector ( $CED$ ) is used to locate and extract the boundaries of the features. Keypoints are matched against themselves after computing their two-dimensional displacement with respect to a reference frame. Pairs of keypoints are subsequently used as control points to fit a geometric transformation in order to align the whole frame with the reference image. The stabilization method is applied to five years of daily images collected from a three-camera permanent video system located at Anglet Beach in southwestern France. Azimuth, tilt, and roll deviations are computed for each camera. The three cameras showed motions on a wide range of time scales, with a prominent annual signal in azimuth and tilt deviation. Camera movement amplitude reached up to 10 pixels in azimuth, 30 pixels in tilt, and 0.4° in roll, together with a quasi-steady counter-clockwise trend over the five-year time series. Moreover, camera viewing angle deviations were found to induce large rectification errors of up to 400 m at a distance of 2.5 km from the camera. The mean shoreline apparent position was also affected by an approximately 10–20 m bias during the 2013/2014 outstanding winter period. The stabilization semi-automatic method successfully corrects camera geometry for fixed video monitoring systems and is able to process at least 90% of the frames without user assistance. The use of the $CED$ greatly improves the performance of the cross-correlation algorithm by making it more robust against contrast and brightness variations between frames. The method appears as a promising tool for other coastal imaging applications such as removal of undesired high-frequency movements of cameras equipped in unmanned aerial vehicles (UAVs).

In this study, three months of records (January–March 2010) that were acquired by a geodetic Global Navigation Satellite Systems (GNSS) station from the permanent network of RGP (Réseau GNSS Permanent), which was deployed by the French Geographic Institute (IGNF), located in Socoa, in the south of the Bay of Biscay, were used to determine the tide components and identify the signature of storms on the signal to noise ratio (SNR) during winter 2010. The Xynthia storm hit the French Atlantic coast on the 28th of February 2010, causing large floods and damages from the Gironde to the Loire estuaries. Blind separation of the tide components and of the storm signature was achieved while using both a singular spectrum analysis (SSA) and a continuous wavelet transform (CWT). A correlation of 0.98/0.97 and root mean square error (RMSE) of 0.21/0.28 m between the tide gauge records of Socoa and our estimates of the sea surface height (SSH) using the SSA and the CWT, respectively, were found. Correlations of 0.76 and 0.7 were also obtained between one of the modes from the SSA and atmospheric pressure from a meteorological station and a mode of the SSA. Particularly, a correlation reaches to 0.76 when using both the tide residual that is associated to surges and atmospheric pressure variation.

De Santiago, I., Morichon, D., Abadie, S., Castelle, B., Liria, P. and Epelde, I., 2013. Video observation of the morphodynamics of nearshore sandbars on a partially engineered embayed beach. Embayed beaches are prevalent environments along the northern Spanish coastline. The present work analyses the temporal and spatial variability of nearshore sandbars on the pocket beach of Zarautz using daily video observations over 2 years. This partially urbanized beach can be divided into two well defined distinct areas: a natural section backed by a sand dune system to the East and an engineered section with rigid seawalls to the West. The objective of the present work is to evaluate if the engineered and natural sections of the beach present different morphological behaviors. The video image analysis was performed in two steps: First, sand bars were characterized visually and classified following standard classification schemes. Then, the outer sand bar migration was measured using automatic bar detecti...

Accurate wave runup estimations are of great interest for coastal risk assessment and engineering design. Phase-resolving depth-integrated numerical models offer a promising alternative to commonly used empirical formulae at relatively low computational cost. Several operational models are currently freely available and have been extensively used in recent years for the computation of nearshore wave transformations and runup. However, recommendations for best practices on how to correctly utilize these models in computations of runup processes are still sparse. In this work, the Boussinesq-type model BOSZ is applied to calculate runup from irregular waves on intermediate and reflective beaches. The results are compared to an extensive laboratory data set of LiDAR measurements from wave transformation and shoreline elevation oscillations. The physical processes within the surf and swash zones such as the transfer from gravity to infragravity energy and dissipation are accurately accounted for. In addition, time series of the shoreline oscillations are well captured by the model. Comparisons of statistical values such as $R_{2\%}$ show relative errors of less than $6\%$. The sensitivity of the results to various model parameters is investigated to allow for recommendations of best practices for modeling runup with phase-resolving depth-integrated models. While the breaking index is not found to be a key parameter for the examined cases, the grid size and the threshold depth, at which the runup is computed, are found to have significant influence on the results. The use of a time series, which includes both amplitude and phase information, is required for an accurate modeling of swash processes, as shown by computations with different sets of random waves, displaying a high variability and decreasing the agreement between the experiment and the model results substantially. The infragravity swash $S_{IG}$ is found to be sensitive to the initial phase distribution, likely because it is related to the short wave envelope.

This paper examines the potential of an optical flow video-based technique to estimate wave-filtered surface currents in the nearshore where wave-breaking induced foam is present. This approach uses the drifting foam, left after the passage of breaking waves, as a quasi-passive tracer and tracks it to estimate the surface water flow. The optical signature associated with sea-swell waves is first removed from the image sequence to avoid capturing propagating waves instead of the desired foam motion. Waves are removed by applying a temporal Fourier low-pass filter to each pixel of the image. The low-pass filtered images are then fed into an optical flow algorithm to estimate the foam displacement and to produce mean velocity fields (i.e., wave-filtered surface currents). We use one week of consecutive 1-Hz sampled frames collected during daylight hours from a single fixed camera located at La Petite Chambre d’Amour beach (Anglet, SW France) under high-energy conditions with significant wave height ranging from 0.8 to 3.3 m. Optical flow-computed velocities are compared against time-averaged in situ measurements retrieved from one current profiler installed on a submerged reef. The computed circulation patterns are also compared against surf-zone drifter trajectories under different field conditions. Optical flow time-averaged velocities show a good agreement with current profiler measurements: coefficient of determination $\left(r^2\right)=$ 0.5–0.8; root mean square error $\left(\mathrm{RMSE}\right)$ = 0.12–0.24 m/s; mean error (bias) $=-0.09$ to $-0.17$ m/s; regression slope $=1\pm 0.15$; ${\mathrm{coherence}}^2$ = 0.4–0.6. Despite an underestimation of offshore-directed velocities under persistent wave breaking across the reef, the optical flow was able to correctly reproduce the mean flow patterns depicted by drifter trajectories. Such patterns include rip-cell circulation, dominant onshore-directed surface flow and energetic longshore current. Our study suggests that open-source optical flow algorithms are a promising technique for coastal imaging applications, particularly under high-energy wave conditions when in situ instrument deployment can be challenging.