6 resultados para Aerial Vehicle

em Publishing Network for Geoscientific


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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.

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The observed changes in physical properties of sea ice such as decreased thickness and increased melt pond cover severely impact the energy budget of Arctic sea ice. Increased light transmission leads to increased deposition of solar energy in the upper ocean and thus plays a crucial role for amount and timing of sea-ice-melt and under-ice primary production. Recent developments in underwater technology provide new opportunities to study light transmission below the largely inaccessible underside of sea ice. We measured spectral under-ice radiance and irradiance using the new Nereid Under-Ice (NUI) underwater robotic vehicle, during a cruise of the R/V Polarstern to 83°N 6°W in the Arctic Ocean in July 2014. NUI is a next generation hybrid remotely operated vehicle (H-ROV) designed for both remotely piloted and autonomous surveys underneath land-fast and moving sea ice. Here we present results from one of the first comprehensive scientific dives of NUI employing its interdisciplinary sensor suite. We combine under-ice optical measurements with three dimensional under-ice topography (multibeam sonar) and aerial images of the surface conditions. We investigate the influence of spatially varying ice-thickness and surface properties on the spatial variability of light transmittance during summer. Our results show that surface properties such as melt ponds dominate the spatial distribution of the under-ice light field on small scales (<1000 m**2), while sea ice-thickness is the most important predictor for light transmission on larger scales. In addition, we propose the use of an algorithm to obtain histograms of light transmission from distributions of sea ice thickness and surface albedo.

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On the basis of aerial photographs of sea ice floes in the marginal ice zone (MIZ) of Prydz Bay acquired from December 2004 to February 2005 during the 21st Chinese National Antarctic Research Expedition, image processing techniques are employed to extract some geometric parameters of floes from two merged transects covering the whole MIZ. Variations of these parameters with the distance into the MIZ are then obtained. Different parameters of floe size, namely area, perimeter, and mean caliper diameter (MCD), follow three similar stages of increasing, flat and increasing again, with distance from the open ocean. Floe shape parameters (roundness and the ratio of perimeter to MCD), however, have less significant variations than that of floe size. Then, to modify the deviation of the cumulative floe size distribution from the ideal power law, an upper truncated power-law function and a Weibull function are used, and four calculated parameters of the above functions are found to be important descriptors of the evolution of floe size distribution in the MIZ. Among them, Lr of the upper truncated power-law function indicates the upper limit of floe size and roughly equals the maximum floe size in each square sample area. L0 in the Weibull distribution shows an increasing proportion of larger floes in squares farther from the open ocean and roughly equals the mean floe size. D in the upper truncated power-law function is closely associated with the degree of confinement during ice breakup. Its decrease with the distance into MIZ indicates the weakening of confinement conditions on floes owing to wave attenuation. The gamma of the Weibull distribution characterizes the degree of homogeneity in a data set. It also decreases with distance into MIZ, implying that floe size distributes increase in range. Finally, a statistical test on floe size is performed to divide the whole MIZ into three distinct zones made up of floes of quite different characteristics. This zonal structure of floe size also agrees well with the trends of floe shape and floe size distribution, and is believed to be a straightforward result of wave-ice interaction in the MIZ.