Catalogue PIGMA
Catalogue PIGMA (PIGMA)
Continents, countries, sea regions of the world.
Beach Litter - Median number of fishing and aquaculture related plastic items normalized per 100m & to 1 survey - EU-MSFD monitoring 2001/2021 v2021
This visualization product displays the fishing & aquaculture related plastic items abundance of marine macro-litter (> 2.5cm) per beach per year from Marine Strategy Framework Directive (MSFD) monitoring surveys. EMODnet Chemistry included the collection of marine litter in its 3rd phase. Since the beginning of 2018, data of beach litter have been gathered and processed in the EMODnet Chemistry Marine Litter Database (MLDB). The harmonization of all the data has been the most challenging task considering the heterogeneity of the data sources, sampling protocols and reference lists used on a European scale. Preliminary processing were necessary to harmonize all the data: - Exclusion of OSPAR 1000 protocol: in order to follow the approach of OSPAR that it is not including these data anymore in the monitoring; - Selection of MSFD surveys only (exclusion of other monitoring, cleaning and research operations); - Exclusion of beaches without coordinates; - Selection of fishing and aquaculture related plastic items only. The list of selected items is attached to this metadata. This list was created using EU Marine Beach Litter Baselines and EU Threshold Value for Macro Litter on Coastlines from JRC (these two documents are attached to this metadata); - Normalization of survey lengths to 100m & 1 survey / year: in some case, the survey length was not exactly 100m, so in order to be able to compare the abundance of litter from different beaches a normalization is applied using this formula: Number of fishing & aquaculture related plastic items of the survey (normalized by 100 m) = Number of fishing & aquaculture related items of the survey x (100 / survey length) Then, this normalized number of fishing & aquaculture related plastic items is summed to obtain the total normalized number of fishing & aquaculture related plastic items for each survey. Finally, the median abundance of fishing & aquaculture related plastic items for each beach and year is calculated from these normalized abundances of fishing & aquaculture related items per survey. Sometimes the survey length was null or equal to 0. Assuming that the MSFD protocol has been applied, the length has been set at 100m in these cases. Percentiles 50, 75, 95 & 99 have been calculated taking into account fishing & aquaculture related plastic items from MSFD data for all years. More information is available in the attached documents. Warning: the absence of data on the map doesn't necessarily mean that they don't exist, but that no information has been entered in the Marine Litter Database for this area.
Creative Commons Attribution 4.0 International
Usage is subject to mandatory citation: "This resource was generated in the framework of EMODnet Chemistry, under the support of DG MARE Call for Tender EASME/EMFF/2018/1.3.1.8 - lot4."
The data used as input for this product have been extracted from the EMODnet Chemistry Download Service: https://emodnet-chemistry.maris.nl/search
Ireland's Marine Atlas - Access to Ireland’s marine data and related information
Ireland’s Marine Atlas is developed and maintained by the Marine Institute with funding by the Government of Ireland. This work is part supported by the Irish Government and the European Maritime & Fisheries Fund as part of the EMFF Operational Programme for 2014-2020. The atlas provides a one-stop-shop to view and download marine environmental data relevant to reporting under Ireland’s Marine Strategy Framework Directive (MSFD). The aim of the European Union’s MSFD directive is to protect more effectively the marine environment across Europe through the establishment of “good marine waters”. Data in Ireland’s Marine Atlas has been guided by the European Directive on harmonising environmental data across Europe within a spatial data infrastructure known as INSPIRE. INSPIRE Data Specifications (Data Models) have been used to manage data to the categories visible under THEMES in the atlas. Many of the layers displayed in the Atlas are also used in the National Marine Planning Framework (NMPF). This framework aims to bring together all marine-based human activities, outlining the government’s vision, objectives and marine planning policies for each marine activity. The NMPF report details how these marine activities will interact with each other in an ocean space that is under increasing spatial pressure, ensuring the sustainable use of our marine resources to 2040. Please read the following information carefully as it sets out the terms and conditions that govern the use of products and services on this website. Once you have read these terms and conditions click the "Agree" button at the bottom of the page to proceed. By clicking the "Agree" button you will be deemed to have accepted the terms and conditions, our legal notices and privacy statement.
Distribution of Clupeids from CPR samples for period 3 (years 1971 to 1977) - Kriging
Fish larvae were collected by the continuous plankton recorder (CPR, operated by SAHFOS) all year long between 1951 and 2005 along transects in the Celtic Sea and English Channel. The CPR is towed by ships of opportunity at speeds of 15 to 20 knots, at an approximate depth of 10 m. Water enters the recorder through an aperture of 1.27 cm2, and is filtered through a continuously moving band of silk with an average mesh size of 270 μm.
Has to be cited this way in maps : "Source CHARM Consortium"
Has to be cited this way in bibliography : "Carpentier A, Martin CS, Vaz S (Eds.), 2009. Channel Habitat Atlas for marine Resource Management, final report / Atlas des habitats des ressources marines de la Manche orientale, rapport final (CHARM phase II). INTERREG 3a Programme, IFREMER, Boulogne-sur-mer, France. 626 pp. & CD-rom"
In all, over 50 taxonomic groups of ichthyoplankton were identified, but we focused on the 6 most abundant groups of fish larvae, clupeids (Clupeidae), Atlantic mackerel (Scomber scombrus), rocklings, horse mackerel (Trachurus trachurus), whiting (Merlangius merlangus), and gadoids (Gadidae). These were the only taxonomic groups for which we had enough positive samplings points in order to produces maps of distribution. The data are aggregated by 7 years periods (1: 1957 to 1963, 2: 1964 to 1970, 3: 1971 to 1977, 4: 1978 to 1984, 5: 1985 to 1991, 6: 1992 to 1998 and 7: 1999 to 2005) and by trimesters. The number of points by year/trimester periods is calculated. For each year/trimester period, the number of non-zero observation for each species/species group is also calculated. If this number is less than 10, the species/group species and period is plotted as a bubble plot. If it is more than 10, the sampling will be interpolated by kriging to have a presence map in the whole area
Temperature of the water column | Temperature of the water body | GHRSST JPL-L2P-MODIS_T | gov.noaa.nodc:GHRSST-JPL-L2P-MODIS_T
WMS for EMODNet Chemistry CDI services by SeaDataNet
WMS/WFS services for marine chemical datasets used in EMODNet Chemistry and provided by SeaDataNet. The data distribution is managed by the Common Data Index (CDI) Data Discovery and Access service
Tropical Cyclone Wind Radii Fixes Dataset for SMOS WIND Project
The SMOS WRF product is available in Near Real Time to support tropical cyclones (TC) forecasts. It is generated within 4 to 6 hours from sensing from the SMOS L2 swath wind speed products (SMOS L2WS NRT), in the so-called "Fix (F-deck)" format compatible with the US Navy's ATCF (Automated Tropical Cyclone Forecasting) System. The SMOS WRF "fixes" to the best-track forecasts contain : the SMOS 10-min maximum-sustained winds (in knots) and wind radii (in nautical miles) for the 34 kt (17 m/s), 50 kt (25 m/s) and 64 kt (33 m/s) winds per geographical storm quadrants, and for each SMOS pass intercepting a TC in all the active ocean basins. See the complete description the "SMOS Wind Data Service Product Description Document" ( http://www.smosstorm.org/Document-tools/SMOS-Wind-Data-Service-Documentation ).
Near-Real Time Surface Wind Speed from SMOS satellite and ancillary data on a 0.25 degree resolution grid. These data were obtained from the ESA-IFREMER-ODL SMOS Wind NRT Data Service project. Dataset accessed [YYYY-MM-DD]. DOI : 10.12770/6346cd83-026a-4bf4-b57d-1ef04de40324
WFS layers based on vocabulary P36 for EMODNet Chemistry CDI services by SeaDataNet
WMS/WFS services for marine chemical datasets used in EMODNet Chemistry and provided by SeaDataNet. The data distribution is managed by the Common Data Index (CDI) Data Discovery and Access service. The service offers layers based on the chemical observations in CDI as grouped per vocabulary P36.
BLACKSEA_CH03_Specification_1 / Oil Platform Leak Bulletin released on 11 May 2016, fast release, 24h after the incident declared on 10th May 2016 by DG MARE
Web Feature Service for Emodnet Chemistry - Marine litter
Web Feature Service for Emodnet Chemistry
GHRSST Level 2P Global Sea Surface Skin Temperature from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the NASA Aqua satellite (GDS2)
NASA produces skin sea surface temperature (SST) products from the Infrared (IR) channels of the Moderate-resolution Imaging Spectroradiometer (MODIS) onboard the Aqua satellite. Aqua was launched by NASA on May 4, 2002, into a sun synchronous, polar orbit with a daylight ascending node at 1:30 pm, formation flying in the A-train with other Earth Observation Satellites (EOS), to study the global dynamics of the Earth atmosphere, land and oceans. MODIS captures data in 36 spectral bands at a variety of spatial resolutions. Two SST products can be present in these files. The first is a skin SST produced for both day and night (NSST) observations, derived from the long wave IR 11 and 12 micron wavelength channels, using a modified nonlinear SST algorithm intended to provide continuity of SST derived from heritage and current NASA sensors. At night, a second SST product is generated using the mid-infrared 3.95 and 4.05 micron wavelength channels which are unique to MODIS; the SST derived from these measurements is identified as SST4. The SST4 product has lower uncertainty, but due to sun glint can only be used at night. MODIS L2P SST data have a 1 km spatial resolution at nadir and are stored in 288 five minute granules per day. Full global coverage is obtained every two days, with coverage poleward of 32.3 degree being complete each day. The production of MODIS L2P SST files is part of the Group for High Resolution Sea Surface Temperature (GHRSST) project and is a joint collaboration between the NASA Jet Propulsion Laboratory (JPL), the NASA Ocean Biology Processing Group (OBPG), and the Rosenstiel School of Marine and Atmospheric Science (RSMAS). Researchers at RSMAS are responsible for SST algorithm development, error statistics and quality flagging, while the OBPG, as the NASA ground data system, is responsible for the production of daily MODIS ocean products. JPL acquires MODIS ocean granules from the OBPG and reformats them to the GHRSST L2P netCDF specification with complete metadata and ancillary variables, and distributes the data as the official Physical Oceanography Data Archive (PO.DAAC) for SST. The R2019.0 supersedes the previous R2014.0 datasets which can be found athttps://doi.org/10.5067/GHMDA-2PJ02
Information retrieved upon specific request to the data source
There is detailed information provided to understand data policy
Format not proprietary and content clearly specified (e.g. autodescriptive like ODV, NetCDF CF) or at least with appropriate document describing the content
Online discovery + downloading + viewing services (Advanced services)
The datasets are referenced in a public national catalogue, in an international catalogue service
/Ocean Temperature/Sea Surface Temperature
Visualization products for Beach Litter data
EU Threshold Value for Macro Litter on Coastlines
IFREMER / IDM / SISMER - Scientific Information Systems for the SEA
Ifremer / VIGIES (Information Valuation Service for Integrated Management and Monitoring)
National Institute of Oceanography and Applied Geophysics - OGS, Division of Oceanography
Ifremer, VIGIES (Information Valuation Service for Integrated Management and Monitoring)
IFREMER, SISMER, Scientific Information Systems for the SEA
Aarhus University,Danish Centre for Environment and Energy
Aarhus University, Department of Bioscience
ARPA Emilia-Romagna, Struttura Oceanografica Daphne
CENTRE FOR DOCUMENTATION, RESEARCH AND EXPERIMENTATION ON ACCIDENTAL WATER POLLUTION
Chief Inspectorate for Environmental Protection
Department of Fisheries and Marine Research, Division of Marine Biology and Ecology
Foundation for Environmental Education, Latvia
Hellenic Centre for Marine Research, Institute of Oceanography
Institute for Water of the Republic of Slovenia
Marine Research Institute of Klaipeda University
Mediterranean Information Office for Environment, Culture and Sustainable Development
MTE-DGSCM, Directorate for Coast and Sea Sustainability. Ministry for Ecological Transition
National Agricultural Research Foundation, Fisheries Research Institute
National Institute for Marine Research and Development "Grigore Antipa"
Nature and Biodiversity Conservation Union Germany
Nature and Biodiversity Conservation Union, Marine Conservation Office
Non-governmental environmental organization "Mare Nostrum"
Office of Schleswig-Holstein Wadden Sea National Park
Royal Belgian Institute of Natural Sciences
Southeast Rügen Biosphere Reserve Office
State Agency for Environment, Nature and Geology, Mecklenburg-Vorpommern
State Office for Agriculture, Environment and Rural Areas of Schleswig Holstein
The Danish Environmental Protection Agency
University of Patras, Department of Geology, Laboratory of Marine Geology and Physical Oceanography
Ifremer/CERSAT > Satellite Data Processing and Distribution Center of the French Research Institute for Exploitation of the Sea
NASA/JPL/PODAAC > Physical Oceanography Distributed Active Archive Center, Jet Propulsion Laboratory, NASA
GHRSST Level 2P Global 1m Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-19 satellite produced by NAVO
A global Group for High Resolution Sea Surface Temperature (GHRSST) Level 2P dataset based on multi-channel sea surface temperature (SST) retrievals generated in real-time from the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-19 platform (launched 6 Feb 2009) produced and used operationally in oceanographic analyses and forecasts by the US Naval Oceanographic Office (NAVO). The AVHRR is a space-borne scanning sensor on the National Oceanic and Atmospheric Administration (NOAA) family of Polar Orbiting Environmental Satellites (POES) having a operational legacy that traces back to the Television Infrared Observation Satellite-N (TIROS-N) launched in 1978. AVHRR instruments measure the radiance of the Earth in 5 (or 6) relatively wide spectral bands. The first two are centered around the red (0.6 micrometer) and near-infrared (0.9 micrometer) regions, the third one is located around 3.5 micrometer, and the last two sample the emitted thermal radiation, around 11 and 12 micrometers, respectively. The legacy 5 band instrument is known as AVHRR/2 while the more recent version, the AVHRR/3 (first carried on the NOAA-15 platform), acquires data in a 6th channel located at 1.6 micrometer. Typically the 11 and 12 micron channels are used to derive SST sometimes in combination with the 3.5 micron channel. The NOAA platforms are sun synchronous generally viewing the same earth location twice a day (latitude dependent) due to the relatively large AVHRR swath of approximately 2400 km. The highest ground resolution that can be obtained from the current AVHRR instruments is 1.1 km at nadir. AVHRR data are acquired in three formats: High Resolution Picture Transmission (HRPT), Local Area Coverage (LAC), and Global Area Coverage (GAC). HRPT data are full resolution image data transmitted to a ground stations as they are collected. LAC are also full resolution data, but the acquisition is prescheduled and recorded with an on-board tape recorder for subsequent transmission during a station overpass. This particular dataset is produced from GAC data that are derived from an on-board sample averaging of the full resolution global AVHRR data. Four out of every five samples along the scan line are used to compute on average value and the data from only every third scan line are processed, yielding an effective 4 km resolution at nadir. Further binning and averaging of these pixels results in a final dataset resolution of 8.8 km.
Micro litter - Density per net normalized in grams per km² - Research and monitoring protocols 2011/2020 v2023
This visualization product displays the density of floating micro-litter per net normalized in grams per km² per year from research and monitoring protocols. EMODnet Chemistry included the collection of marine litter in its 3rd phase. Before 2021, there was no coordinated effort at the regional or European scale for micro-litter. Given this situation, EMODnet Chemistry proposed to adopt the data gathering and data management approach as generally applied for marine data, i.e., populating metadata and data in the CDI Data Discovery and Access service using dedicated SeaDataNet data transport formats. EMODnet Chemistry is currently the official EU collector of micro-litter data from Marine Strategy Framework Directive (MSFD) National Monitoring activities (descriptor 10). A series of specific standard vocabularies or standard terms related to micro-litter have been added to SeaDataNet NVS (NERC Vocabulary Server) Common Vocabularies to describe the micro-litter. European micro-litter data are collected by the National Oceanographic Data Centres (NODCs). Micro-litter map products are generated from NODCs data after a test of the aggregated collection including data and data format checks and data harmonization. A filter is applied to represent only micro-litter sampled according to research and monitoring protocols as MSFD monitoring. Densities were calculated for each net using the following calculation: Density (weight of particles per km²) = Micro-litter weight / (Sampling effort (km) * Net opening (cm) * 0.00001) When the weight of microlitters or the net opening was not filled, the density could not be calculated. Percentiles 50, 75, 95 & 99 have been calculated taking into account data for all years. Warning: the absence of data on the map doesn't necessarily mean that they don't exist, but that no information has been entered in the National Oceanographic Data Centre (NODC) for this area.
Guidelines and formats for gathering micro-litter data
ARPA Friuli-Venezia Giulia, Alto Adriatico Observatory
ARPA Toscana, Area Tutela Ambiente Marino
ARPA Veneto, Osservatorio Regionale Acque
Department of Marine Systems at Tallinn University of Technology
Helmholtz Centre for Ocean Research Kiel (Westshore campus)
Ifremer, Environment Resources Laboratory Provence Azur Corsica (La Seyne-sur-Mer)
Ifremer, Fisheries Science and Technology (Plouzane)
Institute of Marine Sciences, Middle East Technical University
Istanbul University, Institute of Marine Science and Management