MRNIDX - Marine Data Index: Database Description, Operation, Retrieval, and Display

1982 ◽  
Author(s):  
Valerie F. Paskevich
Keyword(s):  
Marine Data

Advanced mid-water tools for 4D marine data fusion and analysis

OCEANS 2009 ◽  
2009 ◽  
Author(s):  
Maurice Doucet ◽  
Colin Ware ◽  
Roland Arsenault ◽  
Tom Weber ◽  
Mashkoor Ahmad Malik ◽  
...  
Keyword(s):  
Data Fusion ◽  
Marine Data

scholarly journals Internet of Underwater Things and Big Marine Data Analytics—A Comprehensive Survey

2021 ◽  
pp. 1-1
Author(s):  
Mohammad Jahanbakht ◽  
Wei Xiang ◽  
Lajos Hanzo ◽  
Mostafa Rahimi Azghadi
Keyword(s):  
Data Analytics ◽  
Comprehensive Survey ◽  
Marine Data

Elastic Least-Squares Imaging in Tilted Transversely Isotropic Media for Multicomponent Land and Pressure Marine Data

2020 ◽  
Vol 41 (4) ◽  
pp. 805-833 ◽  
Author(s):  
Jidong Yang ◽  
Biaolong Hua ◽  
Paul Williamson ◽  
Hejun Zhu ◽  
George McMechan ◽  
...  
Keyword(s):  
Least Squares ◽  
Transversely Isotropic ◽  
Transversely Isotropic Media ◽  
Isotropic Media ◽  
Marine Data

Restricted model domain time Radon transforms

Geophysics ◽  
2016 ◽  
Vol 81 (6) ◽  
pp. A17-A21 ◽  
Author(s):  
Juan I. Sabbione ◽  
Mauricio D. Sacchi
Keyword(s):  
Inverse Problem ◽  
Seismic Data ◽  
Computational Cost ◽  
Synthetic Data ◽  
Model Space ◽  
Radon Transforms ◽  
Iterative Solver ◽  
Hard Thresholding ◽  
Restricted Model ◽  
Marine Data

The coefficients that synthesize seismic data via the hyperbolic Radon transform (HRT) are estimated by solving a linear-inverse problem. In the classical HRT, the computational cost of the inverse problem is proportional to the size of the data and the number of Radon coefficients. We have developed a strategy that significantly speeds up the implementation of time-domain HRTs. For this purpose, we have defined a restricted model space of coefficients applying hard thresholding to an initial low-resolution Radon gather. Then, an iterative solver that operated on the restricted model space was used to estimate the group of coefficients that synthesized the data. The method is illustrated with synthetic data and tested with a marine data example.

Design of Marine Data Warehouse ETL System

2014 ◽  
Vol 668-669 ◽  
pp. 1374-1377 ◽  
Author(s):  
Wei Jun Wen
Keyword(s):  
Decision Making ◽  
Data Quality ◽  
Data Warehouse ◽  
Environmental Data ◽  
Data Sources ◽  
Quality Data ◽  
Critical Step ◽  
Marine Data ◽  
Data Extracting ◽  
Marine Environmental

ETL refers to the process of data extracting, transformation and loading and is deemed as a critical step in ensuring the quality, data specification and standardization of marine environmental data. Marine data, due to their complication, field diversity and huge volume, still remain decentralized, polyphyletic and isomerous with different semantics and hence far from being able to provide effective data sources for decision making. ETL enables the construction of marine environmental data warehouse in the form of cleaning, transformation, integration, loading and periodic updating of basic marine data warehouse. The paper presents a research on rules for cleaning, transformation and integration of marine data, based on which original ETL system of marine environmental data warehouse is so designed and developed. The system further guarantees data quality and correctness in analysis and decision-making based on marine environmental data in the future.

scholarly journals High-resolution marine data and transient simulations support orbital forcing of ENSO amplitude since the mid-Holocene

2021 ◽  
Vol 268 ◽  
pp. 107125
Author(s):  
Matthieu Carré ◽  
Pascale Braconnot ◽  
Mary Elliot ◽  
Roberta d’Agostino ◽  
Andrew Schurer ◽  
...  
Keyword(s):  
High Resolution ◽  
Orbital Forcing ◽  
Transient Simulations ◽  
Marine Data

3D deghosting for full-azimuth and ultra-long offset marine data

2014 ◽  
Author(s):  
Qiaofeng Wu* ◽  
Chang-Chun Lee ◽  
Wei Zhao ◽  
Ping Wang ◽  
Yunfeng Li
Keyword(s):  
Long Offset ◽  
Marine Data

Surface-related multiple elimination on wide-tow marine data

2002 ◽  
Vol 21 (8) ◽  
pp. 787-790 ◽  
Author(s):  
Mohamed T. Hadidi ◽  
Anatoly I. Baumstein ◽  
Young C. Kim
Keyword(s):  
Marine Data ◽  
Multiple Elimination

scholarly journals Streamlining Data and Service Centers for Easier Access to Data and Analytical Services: The Strategy of ODATIS as the Gateway to French Marine Data

2020 ◽  
Vol 7 ◽  
Author(s):  
Sabine Schmidt ◽  
Gilbert Maudire ◽  
Cécile Nys ◽  
Joël Sudre ◽  
Valérie Harscoat ◽  
...  
Keyword(s):  
Data Availability ◽  
Research Infrastructure ◽  
Observation Data ◽  
Use Of Data ◽  
Frequency Monitoring ◽  
Fair Principles ◽  
Marine Data ◽  
Access To Data ◽  
Analytical Services ◽  
Induced Changes

The past few decades have seen a marked acceleration in the amount of marine observation data derived using both in situ and remote sensing measurements. For example, high-frequency monitoring of key physical-chemical parameters has become an essential tool for assessing natural and human-induced changes in coastal waters as well as their consequences on society. The number and variety of data acquisition techniques require efficient methods of improving data availability. The challenge is to make ocean data available via interoperable portals, which facilitate data sharing according to Findable, Accessible, Interoperable, and Reusable (FAIR) principles for producers and users. Ocean DAta Information and Services (ODATIS) aims to become a unique gateway to all French marine data, regardless of the discipline (e.g., physics, chemistry, biogeochemistry, biology, sedimentology). ODATIS is the ocean cluster of the Data Terra research infrastructure for Earth data, which relies on a network of data and service centers (DSC) supported by the major French oceanic research organizations (CNRS, CNES, Ifremer, IRD, SHOM; Marine Universities). ODATIS, through its components, is involved in European and international initiatives such as Copernicus, SeaDataCloud, and EMODnet. The first challenge of ODATIS is to catalog all open ocean and coastal data and facilitate data collection and access (discovery, visualization, extraction) through its web portal. A specific task is to develop tools for handling large amounts of data and generate products for policymakers, practitioners, and academics. This study presents the strategy used by ODATIS to implement the FAIR and CoreTrustSeal requirements in each of its DSCs and promote adherence within the scientific community (the main data producer) regarding the upload and/or use of data and suggestion of new products. A second challenge is to cover the end-user needs ranging from proximity to the producer to cross-analysis of data from all Earth compartments. This involves defining and organizing a classification of DSCs in the network, which will be developed within the framework of the French Data Terra research infrastructure, the only framework capable of providing the necessary IT and human resources.

scholarly journals Time series analysis of marine data: A key knowledge at the crossroads of marine sciences

2014 ◽  
Vol 130 ◽  
pp. 1-3 ◽  
Author(s):  
I. Puillat ◽  
M. Prevosto ◽  
H. Mercier ◽  
S. Thomas
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Series Analysis ◽  
Marine Data
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