Data and Operational Oceanography

2016 ◽  
pp. 303-324
Author(s):  
Enrique Wulff
Keyword(s):  
Temporal Resolution ◽  
Time Frame ◽  
Research Needs ◽  
Resolution Time ◽  
Operational Oceanography ◽  
Data Products ◽  
Data Infrastructures ◽  
Reporting Frequency

Data obtained within the operational oceanography infrastructures denote a possibility of significant analysis of fisheries in the progress of the implementation of the 1995 FAO Code for Responsible Fisheries. Data products for fisheries and aquaculture cater for research needs, thereby ensuring a capacity to meet temporal resolution, time frame, reporting frequency and interoperability formats requirements. The existence of this legislation and the costs of its enforcement make that the present data infrastructures are employed under relatively precarious circumstances. This chapter provides with an overview, not exhaustive but demonstrative, of what has been achieved for data within operational oceanography addressing the needs of fisheries and aquaculture scientists.

Data and Operational Oceanography

2019 ◽  
pp. 315-336
Author(s):  
Enrique Wulff
Keyword(s):  
Temporal Resolution ◽  
Time Frame ◽  
Research Needs ◽  
Resolution Time ◽  
Operational Oceanography ◽  
Data Products ◽  
Data Infrastructures ◽  
Reporting Frequency

Data obtained within the operational oceanography infrastructures denote a possibility of significant analysis of fisheries in the progress of the implementation of the 1995 FAO Code for Responsible Fisheries. Data products for fisheries and aquaculture cater for research needs, thereby ensuring a capacity to meet temporal resolution, time frame, reporting frequency and interoperability formats requirements. The existence of this legislation and the costs of its enforcement make that the present data infrastructures are employed under relatively precarious circumstances. This chapter provides with an overview, not exhaustive but demonstrative, of what has been achieved for data within operational oceanography addressing the needs of fisheries and aquaculture scientists.

SAR, SARin, RDSAR and FF-SAR Altimetry Processing on Demand for CryoSat-2 and Sentinel-3 at ESA G-POD

2021 ◽  
Author(s):  
Jérôme Benveniste ◽  
Salvatore Dinardo ◽  
Christopher Buchhaupt ◽  
Michele Scagliola ◽  
Marcello Passaro ◽  
...  
Keyword(s):  
Geographical Area ◽  
Vertical Motion ◽  
Time Frame ◽  
Data Repository ◽  
On Demand ◽  
Area Of Interest ◽  
Range Cell ◽  
Data Products ◽  
The Status ◽  
Range Cell Migration

<p>The scope of this presentation is to feature and provide an update on the ESA G-POD/SARvatore family of altimetry services portfolio for the exploitation of CryoSat-2 and Sentinel-3 data from L1A (FBR) data products up to SAR/SARin Level-2 geophysical data products. At present, the following on-line & on-demand services compose the portfolio:</p><p>-       The SARvatore (SAR Versatile Altimetric TOolkit for Research & Exploitation) for CryoSat-2 and Sentinel-3 services developed by the Altimetry Team in the R&D division at ESA-ESRIN. These processor prototypes are versatile and allow the users to customize and adapt the processing at L1b & L2 according to their specific requirements by setting a list of configurable options. The scope is to provide users with specific processing options not available in the operational processing chains (e.g. range walk correction, stack sub-setting, extended receiving window, zero padding, high-posting rate and burst weighting at L1b & SAMOSA+, SAMOSA++ and ALES+ SAR retrackers at L2). AJoin & Share Forum (https://wiki.services.eoportal.org/tiki-custom_home.php) allows users to post questions and report issues. A data repository is also available to the Community to avoid the redundant reprocessing of already processed data (https://wiki.services.eoportal.org/tiki-index.php?page=SARvatore+Data+Repository&highlight=repository).</p><p>-       The TUDaBo SAR-RDSAR (Technical University Darmstadt – University Bonn SAR-Reduced SAR) for CryoSat-2 and Sentinel-3 service. It allows users to generate reduced SAR, unfocused SAR & LRMC data. Several configurable L1b & L2 processing options and retrackers (BMLE3, SINC2, TALES, SINCS) are available. The processor will be extended during an additional activity related to the ESA HYDROCOASTAL Project (https://www.satoc.eu/projects/hydrocoastal/) to account in the open ocean for the vertical motion of the wave particles (VMWP) in unfocused SAR and in a simplified form of the fully focused SAR called here Low Resolution Range Cell Migration Correction-Focused (LRMC-F).  </p><p>-       The ALES+ SAR for CryoSat-2 and Sentinel-3 service. It allows users to process official L1b data and produces L2 NetCDF products by applying the empirical ALES+ SAR subwaveform retracker, including a dedicated SSB solution, developed by the Technische Universität München in the frame of the ESA Sea Level CCI (http://www.esa-sealevel-cci.org/) & BALTIC+ SEAL Projects (http://balticseal.eu/).</p><p>-       The Aresys Fully Focused SAR for CryoSat-2 service. Currently under development, it will provide the capability to produce CS-2 FF-SAR L1b products thanks to the Aresys 2D transformed frequency domain AREALT-FF1 processor prototype. Output products will also include geophysical corrections and threshold peak & ALES-like subwaveform retracker estimates.</p><p>The G-POD graphical interface allows users to select, in all the services, a geographical area of interest within the time-frame related to the L1A (FBR) & L1b data products availability in the service catalogue.  </p><p>After the task submission, users can follow, in real time, the status of the processing. The output data products are generated in standard NetCDF format, therefore being compatible with the multi-mission “Broadview Radar Altimetry Toolbox” (BRAT, http://www.altimetry.info) and typical tools.</p><p>Services are open, free of charge (supported by ESA) for worldwide scientific applications and available, after registration and activation (to be requested for each chosen service to [email protected]), at https://gpod.eo.esa.int.</p>

scholarly journals An Automated Method for Annual Cropland Mapping along the Season for Various Globally-Distributed Agrosystems Using High Spatial and Temporal Resolution Time Series

2015 ◽  
Vol 7 (10) ◽  
pp. 13208-13232 ◽  
Author(s):  
Nicolas Matton ◽  
Guadalupe Canto ◽  
François Waldner ◽  
Silvia Valero ◽  
David Morin ◽  
...  
Keyword(s):  
Time Series ◽  
Temporal Resolution ◽  
Resolution Time ◽  
Automated Method ◽  
Globally Distributed ◽  
Cropland Mapping

High Spatial and Temporal Resolution Time-Series Particle Image Velocimetry

2003 ◽  
Vol 2003 (0) ◽  
pp. 145
Author(s):  
Mamoru TANAHASHI ◽  
Yuichi FUKUCHI ◽  
Gyung Min CHOI ◽  
Katsuhiko FUKUZATO ◽  
Toshio MIYAUCHI
Keyword(s):  
Time Series ◽  
Particle Image Velocimetry ◽  
Temporal Resolution ◽  
Particle Image ◽  
Resolution Time ◽  
Image Velocimetry

High Spatial and Temporal Resolution Time-Series Particle Image Velocimetry Higher than O(kHz)

2003 ◽  
Vol 2003 (0) ◽  
pp. 271-272
Author(s):  
Mamoru TANAHASHI ◽  
Yuichi FUKUCHI ◽  
Gyung Min CHOI ◽  
Katsuhiko FUKUZATO ◽  
Toshio MIYAUCHI
Keyword(s):  
Time Series ◽  
Particle Image Velocimetry ◽  
Temporal Resolution ◽  
Particle Image ◽  
Resolution Time ◽  
Image Velocimetry

scholarly journals Development of ground pipeline system for high-level scientific data products of the Hisaki satellite mission and its application to planetary space weather

2019 ◽  
Vol 9 ◽  
pp. A8 ◽  
Author(s):  
Tomoki Kimura ◽  
Atsushi Yamazaki ◽  
Kazuo Yoshioka ◽  
Go Murakami ◽  
Fuminori Tsuchiya ◽  
...  
Keyword(s):  
Solar System ◽  
Spectral Data ◽  
Temporal Resolution ◽  
Space Weather ◽  
Transport Processes ◽  
Light Curves ◽  
Pipeline System ◽  
Ancillary Data ◽  
Data Products ◽  
High Level

The Hisaki satellite is the first-ever space telescope mission dedicated to planetary sciences. Atmospheres and magnetospheres of our solar system planets are continuously monitored by the extreme ultraviolet (EUV) spectrometer onboard Hisaki. This paper describes a data pipeline system developed for processing high-level scientific and ancillary data products from the Hisaki mission. The telemetry data downlinked from the satellite are stored in a ground telemetry database, processed in the pipeline to imaging spectral data with a 1-min temporal resolution and ancillary data products, and then archived in a public database. The imaging spectra can be further reduced to higher-level data products for practical scientific use. For example, light curves of the power emitted from Jupiter’s aurora and plasma torus with a temporal resolution of 10-min can be reduced from the imaging spectral data; the reduced light curves reveal the transport processes of energy and mass in Jupiter’s magnetosphere and associated interplanetary solar wind conditions. Continuous monitoring with Hisaki will contribute considerably to our understanding of space weather relating to planets in our solar system.

Spatial Data Infrastructures

2010 ◽  
pp. 36-41 ◽  
Author(s):  
Carlos Granell ◽  
Michael Gould ◽  
Miguel Ángel Manso ◽  
Miguel Ángel Bernabé
Keyword(s):  
Information Systems ◽  
Spatial Data ◽  
Future Research ◽  
Research Needs ◽  
Distributed Information ◽  
Institutional Collaboration ◽  
Data Content ◽  
Data Infrastructures ◽  
Spatial Data Infrastructures ◽  
Geospatial Services

Geographic Information Systems (GIS) are data-centric applications that rely on the input and constant maintenance of large quantities of basic and thematic spatial data in order to be useful tools for decision- making. This chapter presents the institutional collaboration framework and the major technology components to facilitate discovery and sharing of spatial data: Spatial Data Infrastructures (SDI). We review the essential software components –metadata editors and associated catalogue services, spatial data content repositories, client applications, and middleware or intermediate geospatial services– that define SDIs as heterogeneous distributed information systems. Finally we highlight future research needs in the areas of semantic interoperability of SDI services and in improved institutional collaboration.

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