Abstract
Video monitoring has become an indispensable tool to understand beach processes. However, the measurement accuracy derived from the images has been taken for granted despite its dependence on the calibration process and camera movements. An easy to implement self-fed image stabilization algorithm is proposed to solve the camera movements. Georeferenced images were generated from the stabilized images using only one calibration. To assess the performance of the stabilization algorithm, a second set of georeferenced images was created from unstabilized images following the accepted practice of using several calibrations. Shorelines were extracted from the images and corrected with the measured water level and the computed run-up to the 0 m contour. Image-derived corrected shorelines were validated with one hundred beach profile surveys measured during a period of four years along a 1.1 km beach stretch. The simultaneous high-frequency field data available of images and beach surveys are uncommon and allow assessing seasonal changes and long-term trends accuracy. Errors in shoreline position do not increase in time suggesting that the proposed stabilization algorithm does not propagate errors, despite the ever-evolving vegetation in the images. The image stabilization reduces the error in shoreline position by 40 percent, having a larger impact with increasing distance from the camera. Furthermore, the algorithm improves the accuracy on long-term trends by one degree of magnitude (0.01 m/year vs. 0.25 m/year).
Highlights
Video cameras have been used to monitor the beach since the eighties with the development of the ARGUS system [1]
The position of the pier corner was manually digitized in the oblique images as a mean to evaluate the performance of the stabilization algorithm (Figure 6)
The effect of the stabilization process on solving the camera movements can be appreciated by averaging the image datasets, which results in a blurred pier for non-stabilized images (NSI) and a well defined pier for stabilized images (SI)
Summary
Video cameras have been used to monitor the beach since the eighties with the development of the ARGUS system [1]. Despite the recent rise of drones [5] and satellite imagery [6,7] for coastal monitoring, the balance between the temporal and spatial resolution offered by fixed cameras during extended periods of time (years) can still provide unique information given the dynamic beach behavior. Lippmann and Holman [8] demonstrated that time-averaged images show elongated white breakerlines parallel to the coast that approximate the position of submerged bars and the shoreline. This finding triggered the study of sandbar and shoreline dynamics. Images have been used to study dynamics on shorter timescales, including the formation of finger bars [18,19], rip currents [20,21], and groundwater seepage on beaches [22,23]
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