GPS raw data (control points and ground control points) from the Liguria Region, Borghetto Santo Spirito, Italy


Autoria(s): Casella, E; Rovere, Alessio; Pedroncini, Andrea; Mucerino, Luigi; Cusati, Luis Alberto; Vacchi, Matteo; Ferrari, Marco; Firpo, M
Cobertura

MEDIAN LATITUDE: 44.114427 * MEDIAN LONGITUDE: 8.247597 * SOUTH-BOUND LATITUDE: 44.113510 * WEST-BOUND LONGITUDE: 8.246600 * NORTH-BOUND LATITUDE: 44.115490 * EAST-BOUND LONGITUDE: 8.248760 * DATE/TIME START: 2013-04-13T00:00:00 * DATE/TIME END: 2013-04-13T00:00:00

Data(s)

02/07/2014

Resumo

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.

Formato

application/zip, 2 datasets

Identificador

https://doi.pangaea.de/10.1594/PANGAEA.847710

doi:10.1594/PANGAEA.847710

Idioma(s)

en

Publicador

PANGAEA

Relação

A picture of two Unmanned Aerial Vehicles (UAVs) (URI: http://store.pangaea.de/Publications/Casella_etal_2014/mmc2.pdf)

Direitos

CC-BY: Creative Commons Attribution 3.0 Unported

Access constraints: unrestricted

Fonte

Supplement to: Casella, E; Rovere, Alessio; Pedroncini, Andrea; Mucerino, Luigi; Cusati, Luis Alberto; Vacchi, Matteo; Ferrari, Marco; Firpo, M (2014): Study of wave runup using numerical models and low-altitude aerial photogrammetry: A tool for coastal management. Estuarine, Coastal and Shelf Science, 149, 160-167, doi:10.1016/j.ecss.2014.08.012

Palavras-Chave #15 Apr DEM value; Diff; Difference; Difference between 15 Apr and GPS; Familiy ID; FID; FILT_POS; GNSS_Heigh; HDOP; Height; HEIGHT above ground; Horizontal dilution of precision; Horizontal precision (m); Latitude; LATITUDE; Longitude; LONGITUDE; Max; Number of filtered positions; PDOP; Position dilution of precision; Precip; Precision; RMSE; Root mean square error; SampleID; Sample ID; Standard deviation; Std dev; Surface elevation; Surf elev; UTM east; UTM Easting, Universal Transverse Mercator; UTM north; UTM Northing, Universal Transverse Mercator; UTM Zone; UTM Zone, Universal Transverse Mercator; Vertical precision (m)
Tipo

Dataset