The use of GPS buoys in the determination of oceanic variables

Cardellach, Estel; Behrend, Dirk; Ruffini, Giulio; Rius, A.

doi:10.1186/bf03352340

Cited by 12 publications

(7 citation statements)

References 7 publications

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“…Collected data are analyzed using a precise point positioning (PPP) strategy of GIPSY/OASIS-II (Zumberge et al, 1997), which has been used in many geodetical and geophysical applications (e.g. Ohtani et al, 2000;Shoji et al, 2000;Behrend et al, 2000;Gradinarsky et al, 2000;Becker et al, 2000;Aonashi et al, 2000;Takiguchi et al, 2000;Cardellach et al, 2000). Figure 3 shows an example of time series of ITRF97 coordinates derived at station AKT0.…”

Section: Datamentioning

confidence: 99%

Strain accumulation in and around Ou Backbone Range, northeastern Japan as observed by a dense GPS network

et al. 2014

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A dense GPS network was established in 1997 around Ou Backbone Range (OBR), northeastern Japan, by deploying 28 continuous GPS stations to complement the sparse portion of GEONET operated by the Geographical Survey Institute of Japan. The aim of the network is to investigate the present surface deformation and understand the relationship between earthquake occurrence and the deformation process of the island-arc crust. Our GPS data are analyzed using a precise point positioning strategy of GIPSY/OASIS-II. Results of GEONET in daily SINEX files have been supplied by the GSI. Producing grid data of horizontal velocities and taking spatial derivatives, we derived a map of strain rate distribution. The results show that the region between 38.8• and 39.8• N in the OBR experiences notable concentration of east-west contraction. The region coincides with the area of active seismicity, including the focal areas of large earthquakes occurring in 1896 (M7.2), 1900 (M7.0), 1962 (M6.5), 1970 (M6.2), and 1998 (M6.1). Observed strain is larger than can be explained by the total moment release of earthquakes that occurred in the same period as this study. Possible sources of strain concentration may be viscoelastic deformation due to large earthquakes and/or aseismic slip along the deeper extension of the active faults.

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Section: Datamentioning

confidence: 99%

Strain accumulation in and around Ou Backbone Range, northeastern Japan as observed by a dense GPS network

et al. 2014

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“…Bin size, total number of bins, and reporting mode can all be modified remotely through an RS-232 interface. Investigations of global positioning system (GPS) based solutions, similar to work at Ohio State University, the National Cheng Kung University in Taiwan and collaborative efforts in South Korea are ongoing [7]- [10]. c) Flotation Hull: The flotation hull is a 1.2 m (4 ft) diameter foam-infused fiberglass frame with aluminum radiation sensor (see Table I).…”

Section: A Buoy Platformmentioning

confidence: 99%

The Upper-Great Lakes Observing System

Brown

Purcell

Meadows

2010

Oceans 2010 MTS/Ieee Seattle

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This paper reports an overview of the University of Michigan's Upper-Great Lakes Observing System (U-GLOS) program, as well as the design, construction, and testing of offshore buoy platforms, communication schemes, and a shorebased server system. Since 2003, the University of Michigan's Marine Hydrodynamics Laboratories (MHL) has partnered with local communities, as well as Northwestern Michigan's College Water Studies Institute, DTE, Alliance for Coastal Technologies, Michigan Sea Grant, and the Grand Traverse Band of Ottawa and Chippewa Indians to develop the U-GLOS program that exists today. The U-GLOS program now includes both land and offshore platforms that monitor environmental conditions and report, in real-time, the results to a publicly accessible web site. Each station measures a wide range of properties including air temperature, wind speed, wind gusts, solar radiation, humidity, and more. Buoy stations also measure water temperature (thermistor array), directional and non-directional wave characteristics. Ongoing scientific and engineering research is discussed, as well as an overview of available data products, quality control and quality assurance algorithms, and conformity to the National Data Buoy Center (NDBC) standards.

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“…From the kinematic positioning results, other information can also be obtained. On the other hand, there are many algorithms used to separate ocean surface parameters from the GPS positioning results such as those as based on stationary stochastic process and non-stationary stochastic process, and Fourier transform and wavelet transform and so on [2,5,22] . In this paper, the main GPS data process techniques will be introduced and their corresponding pros and cons for sea level monitoring are also discussed.…”

Section: Introductionmentioning

confidence: 99%

“…Not only does GPS supply position for ocean navigation but also other related information because of its high precision kinematic positioning mode. Over the past decades, GPS buoy has been used to measure sea level, sea wave, ocean tide, atmospheric parameter and other physical conditions together with other sensors to serve as offshore wave, tsunami, tide observation [2,6,13,17,18] , altimeter range measurements calibration and some other ocean surface monitoring system [8,14,16,19] . As an efficient way to obtain the position, there are many kinds of GPS kinematic positioning methods, such as the conventional GPS RTK, network GPS and precise point positioning techniques.…”

Section: Introductionmentioning

confidence: 99%

Ocean surface monitoring based on GPS kinematic positioning

Chen

2009

SPIE Proceedings

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In this paper, the conventional GPS kinematic positioning method and precise point positioning method for ocean surface monitoring are briefly presented and their corresponding pros and cons for sea level monitoring are also discussed. Then, algorithms for ocean surface parameter estimation from the GPS height component are introduced, which uses the spectral analysis method to extract sea level tide and sea wave parameters. A 48 hours GPS field data set by GPS buoy is used to evaluate the methods presented here. First, the height component analysis is performed to obtain the low-frequency and high-frequency signals which consist of ocean tide and wave components. Then, a wavelet transformation is performed to the high frequency series in order to detect the main wave period of about 10 second. The results show that GPS kinematic positioning technique can not only be used for ocean positioning but can also be used to monitor the ocean surface.

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The use of GPS buoys in the determination of oceanic variables

Cited by 12 publications

References 7 publications

Strain accumulation in and around Ou Backbone Range, northeastern Japan as observed by a dense GPS network

Strain accumulation in and around Ou Backbone Range, northeastern Japan as observed by a dense GPS network

The Upper-Great Lakes Observing System

Ocean surface monitoring based on GPS kinematic positioning

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