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| Main Authors: | , , , , , , , |
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| Format: | Dataset Open Access |
| Language: | en |
| Published: |
PANGAEA
2014
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| Subjects: | |
| Online Access: | https://doi.org/10.1594/PANGAEA.847710 |
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| _version_ | 1867170468393385984 |
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| author | Casella, Elisa Rovere, Alessio Pedroncini, Andrea Mucerino, Luigi Cusati, Luis Alberto Vacchi, Matteo Ferrari, Marco Firpo, M |
| author_facet | Casella, Elisa Rovere, Alessio Pedroncini, Andrea Mucerino, Luigi Cusati, Luis Alberto Vacchi, Matteo Ferrari, Marco Firpo, M |
| collection | Datos científicos de ciencias marinas y ambientales |
| contents | Monitoring the impact of sea storms on coastal areas is fundamental to study beach evolution and the vulnerability of low-lying coasts to erosion and flooding. Modelling wave runup on a beach is possible, but it requires accurate topographic data and model tuning, that can be done comparing observed and modeled runup. In this study we collected aerial photos using an Unmanned Aerial Vehicle after two different swells on the same study area. We merged the point cloud obtained with photogrammetry with multibeam data, in order to obtain a complete beach topography. Then, on each set of rectified and georeferenced UAV orthophotos, we identified the maximum wave runup for both events recognizing the wet area left by the waves. We then used our topography and numerical models to simulate the wave runup and compare the model results to observed values during the two events. Our results highlight the potential of the methodology presented, which integrates UAV platforms, photogrammetry and Geographic Information Systems to provide faster and cheaper information on beach topography and geomorphology compared with traditional techniques without losing in accuracy. We use the results obtained from this technique as a topographic base for a model that calculates runup for the two swells. The observed and modeled runups are consistent, and open new directions for future research. |
| format | Dataset Open Access |
| id | pangaea_https___doi_org_10_1594_PANGAEA_847710 |
| institution | PANGAEA |
| language | en |
| publishDate | 2014 |
| publisher | PANGAEA |
| record_format | pangaea |
| spellingShingle | GPS raw data (control points and ground control points) from the Liguria Region, Borghetto Santo Spirito, Italy Casella, Elisa Rovere, Alessio Pedroncini, Andrea Mucerino, Luigi Cusati, Luis Alberto Vacchi, Matteo Ferrari, Marco Firpo, M Monitoring the impact of sea storms on coastal areas is fundamental to study beach evolution and the vulnerability of low-lying coasts to erosion and flooding. Modelling wave runup on a beach is possible, but it requires accurate topographic data and model tuning, that can be done comparing observed and modeled runup. In this study we collected aerial photos using an Unmanned Aerial Vehicle after two different swells on the same study area. We merged the point cloud obtained with photogrammetry with multibeam data, in order to obtain a complete beach topography. Then, on each set of rectified and georeferenced UAV orthophotos, we identified the maximum wave runup for both events recognizing the wet area left by the waves. We then used our topography and numerical models to simulate the wave runup and compare the model results to observed values during the two events. Our results highlight the potential of the methodology presented, which integrates UAV platforms, photogrammetry and Geographic Information Systems to provide faster and cheaper information on beach topography and geomorphology compared with traditional techniques without losing in accuracy. We use the results obtained from this technique as a topographic base for a model that calculates runup for the two swells. The observed and modeled runups are consistent, and open new directions for future research. |
| title | GPS raw data (control points and ground control points) from the Liguria Region, Borghetto Santo Spirito, Italy |
| topic | |
| url | https://doi.org/10.1594/PANGAEA.847710 |