Please use this identifier to cite or link to this item: http://hdl.handle.net/2122/14169
Authors: Palano, Mimmo* 
Pezzo, Giuseppe* 
Serpelloni, Enrico* 
Devoti, Roberto* 
D'Agostino, Nicola* 
Gandolfi, Stefano* 
Sparacino, Federica* 
Anderlini, Letizia* 
Poluzzi, Luca* 
Tavasci, Luca* 
Macini, Paolo* 
Pietrantonio, Grazia* 
Riguzzi, Federica* 
Antoncecchi, Ilaria* 
Ciccone, Francesco* 
Rossi, Giada* 
Avallone, Antonio* 
Selvaggi, Giulio* 
Title: Geopositioning time series from offshore platforms in the Adriatic Sea
Journal: Scientific Data 
Series/Report no.: /7 (2020)
Publisher: Nature P.G.
Issue Date: 4-Nov-2020
DOI: 10.1038/s41597-020-00705-w
URL: https://www.nature.com/articles/s41597-020-00705-w
Keywords: GNSS
offshore platforms
subsidence
data processing
oil/gas exploiting
Subject Classification04. Solid Earth
04.03. Geodesy 
Abstract: We provide a dataset of 3D coordinate time series of 37 continuous GNSS stations installed for stability monitoring purposes on onshore and offshore industrial settlements along a NW-SE-oriented and ~100-km-wide belt encompassing the eastern Italian coast and the Adriatic Sea. The dataset results from the analysis performed by using different geodetic software (Bernese, GAMIT/GLOBK and GIPSY) and consists of six raw position time series solutions, referred to IGb08 and IGS14 reference frames. Time series analyses and comparisons evidence that the different solutions are consistent between them, despite the use of different software, models, strategy processing and frame realizations. We observe that the offshore stations are subject to significant seasonal oscillations probably due to seasonal environmental loads, seasonal temperature-induced platform deformation and hydrostatic pressure variations. Many stations are characterized by non-linear time series, suggesting a complex interplay between regional (long-term tectonic stress) and local sources of deformation (e.g. reservoirs depletion, sediment compaction). Computed raw time series, logs files, phasor diagrams and time series comparison plots are distributed via PANGAEA ( https://www.pangaea.de ).
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