4096 4096 application/vnd.ogc.wms_xml text/xml image/bmp image/jpeg image/tiff image/png image/png8 image/png24 image/png32 image/gif image/svg+xml application/vnd.esri.wms_raw_xml application/vnd.esri.wms_featureinfo_xml application/vnd.ogc.wms_xml application/geojson text/xml text/html text/plain application/vnd.ogc.sld+xml application/vnd.ogc.se_xml application/vnd.ogc.se_inimage application/vnd.ogc.se_blank text/xml XML CRS:84 EPSG:4326 EPSG:3857 EPSG:102100 EPSG:4258 -25.896182-0.68500046.74753957.443408 CRS:84 EPSG:4326 EPSG:3857 EPSG:102100 EPSG:4258 -25.896182-0.68500046.74753957.443408 1 http://www.isde.ie/#/fdb5bb9e-6bce-420c-a11f-1274ef815be5 life science, ecology The MSFD commission staff working paper (CSWP) defines predominant habitat types required for use in MSFD habitats initial reporting article 8 Analysis of essential features and characteristics (Art 8.1a Habitats). These predominant habitat typologies broadly correspond to EUNIS level 2 habitat typologies. This supported the process of mapping existing habitat types (evidence based and predicted) to the CSWP PHT classification by means of data re-engineering. The PHT layer has been derived from, Evidence based data source (EMODnet sediment and substrate) Predicted habitats data source (Predicted EUNIS habitats (2008 MESH model) In areas where neither evidence nor predicted data was available, a depth proxy was created using INFOMAR bathymetry. When viewing the PHT habitats layer, the Predominant Habitat Confidence should be also be used as reference as this provides the user with a means to establish the data source underpinning the derived PHT habitat type per polygon.]]> CRS:84 EPSG:4326 EPSG:3857 EPSG:102100 EPSG:4258 -25.896182-0.68500046.74753957.440539 2 http://www.isde.ie/#/987c8b25-6939-455a-a2bd-dc7af0559780 life science, ecology The MSFD commission staff working paper (CSWP) defines predominant habitat types required for use in MSFD habitats initial reporting article 8 - "Analysis of essential features and characteristics (Art 8.1a - Habitats)". These predominant habitat typologies broadly correspond to EUNIS level 2 habitat typologies. This supported the process of mapping existing habitat types (evidence based and predicted) to the CSWP PHT classification by means of data re-engineering. In areas where neither evidence nor predicted data was available, a depth proxy was created using INFOMAR bathymetry. When viewing the PHT habitats layer, the Predominant Habitat Confidence should be also be used as reference as this provides the user with a means to establish the data source underpinning the derived PHT habitat type per polygon.]]> CRS:84 EPSG:4326 EPSG:3857 EPSG:102100 EPSG:4258 -25.896182-0.68500046.74753957.440539 3 http://www.isde.ie/#/589786ac-5b34-43fb-a205-82e59528e9f1 life science, ecology Seabed Habitats was initiated in EMODnet Phase I (2009-2013) through the EUSeaMap project. During the current Phase II (2013-2016), Seabed Habitats will extend the work carried out during the preparatory Phase 1 to move from a prototype to an operational service delivering full coverage of a broad-scale map for all European sea-basins, along with the dissemination of maps from surveys. Habitat maps are important as they contain essential information about the seafloor which is required to sustainably manage and develop the economic potential of European sea-basins. European seabed habitat maps serve many purposes including the design of ecologically coherent Marine Protected Area (MPA) networks, species distribution modelling, establishing monitoring programmes for seabed habitats and informing maritime spatial planning (MSP). They are also indispensable for Member States to fulfill their legal obligations under the Marine Strategy Framework Directive (MSFD), where full coverage of seabed predominant habitats of all European seas is required. Unfortunately, habitat maps from surveys are very costly and time consuming to produce. A more time- and cost-efficient way to meet the need for a full coverage habitat map is to use low resolution maps and models to 'predict' seafloor habitat types. These maps of expected seabed-habitat types can be generated by combining a series of proxy measurements such as; water depth, sediment type and light levels amongst others, using statistical analysis and Geographical Information System (GIS) modelling. ]]> CRS:84 EPSG:4326 EPSG:3857 EPSG:102100 EPSG:4258 -24.848377-4.95483649.26683457.443408 4 http://www.isde.ie/#/782fcc22-0917-4184-8cc7-06241ceafd1c life science, ecology Collated EUNIS habitat classification.]]> CRS:84 EPSG:4326 EPSG:3857 EPSG:102100 EPSG:4258 -19.308402-5.27233349.26691856.712462