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OpenSWAP, an open architecture, low cost class of autonomous surface vehicles for geophysical surveys in the shallow water environment

Articolo
Data di Pubblicazione:
2020
Abstract:
OpenSWAP is a class of innovative open architecture, low cost autonomous vehicles for geological/geophysical studies of shallow water environments. Although they can host different types of sensors, these vehicles were specifically designed for geophysical surveys, i.e., for the acquisition of bathymetric and stratigraphic data through single- and multibeam echosounders, side-scan sonars, and seismic-reflection systems. The main characteristic of the OpenSWAP vehicles is their ability of following pre-defined routes with high accuracy under acceptable weather and sea conditions. This would open the door to 4D (repeated) surveys, which constitute a powerful tool to analyze morphological and stratigraphic changes of the sediment/water interface and of the shallow substratum eventually caused by sediment dynamics (erosion vs. deposition), slumps and gravitative failures, earthquakes (slip along seismogenic faults and secondary effects of shaking), tsunamis, etc. The low cost and the open hardware/software architectures of these systems, which can be modified by the end users, lead for planning and execution of cooperative and adaptive surveys with different instruments not yet implemented or tested. Together with a technical description of the vehicles, we provide different case studies where they were successfully employed, carried out in environments not, or very difficultly accessed through conventional systems.
Tipologia CRIS:
01.01 Articolo in rivista
Keywords:
Autonomous Surface Vehicles (ASV); marine geophysics; shallow water environments; repeated 4D surveys; NAIADI Project (New Autonomous; automatIc systems for the study AnD monitoring of aquatic envIronments)
Elenco autori:
Stanghellini, Giuseppe; Gasperini, Luca
Autori di Ateneo:
GASPERINI LUCA
STANGHELLINI GIUSEPPE
Link alla scheda completa:
https://iris.cnr.it/handle/20.500.14243/377981
Pubblicato in:
REMOTE SENSING (BASEL)
Journal
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