The Urban Atlas provides pan-European comparable land use and land cover data for Functional Urban Areas (FUA). The Street Tree Layer (STL) is a separate layer from the Urban Atlas 2012 LU/LC layer produced within the level 1 urban mask for each FUA. It includes contiguous rows or a patches of trees covering 500 m² or more and with a minimum width of 10 meter over "Artificial surfaces" (nomenclature class 1) inside FUA (i.e. rows of trees along the road network outside urban areas or forest adjacent to urban areas should not be included). Urban Atlas is a joint initiative of the European Commission Directorate-General for Regional and Urban Policy and the Directorate-General for Enterprise and Industry in the frame of the EU Copernicus programme, with the support of the European Space Agency and the European Environment Agency.

Akkeri og baujur og áætlaðar staðsetningar fyrir búnað í sjókvíaeldi.

DFO’s Oceans and Coastal Management Division (OCMD) in the Maritimes Region has updated its fisheries landings maps for 2010–2014. These maps will be used for decision making in coastal and oceans management, including mitigating human use conflicts, informing environmental emergency response operations and protocols, informing Marine Stewardship Council certification processes, planning marine protected area networks, assessing ecological risks, and monitoring compliance and threats in coral and sponge closures and Marine Protected Areas. Fisheries maps were created to identify important fishing areas using aggregate landed weight (kg) per 2 x 2-minute grid cell for selected species/gear types. This dataset has been filtered to comply with the Government of Canada's privacy policy. Privacy assessments were conducted to identify NAFO unit areas containing data with less than five vessel IDs, license IDs and fisher IDs. If this threshold was not met, catch weight locations were withheld from these unit areas to protect the identity or activity of individual vessels or companies. Maps were created for the following species/gear types: 1. Atlantic Halibut 2. Bluefin Tuna 3. Bottom Longline Groundfish 4. Bottom Trawl Groundfish 5. Cod 6. Cod, Haddock, Pollock 7. Cusk 8. Dogfish 9. Flatfish 10. Gillnet Groundfish 11. Greenland Halibut 12. Groundfish 13. Groundfish (quarterly composites Q1, Q2, Q3, Q4) 14. Hagfish 15. Herring 16. Large Pelagics 17. Mackerel 18. Monkfish 19. Offshore Clam 20. Offshore Lobster 21. Grey Zone Lobster 22. Other Crab 23. Other Tuna 24. Pollock 25. Porbeagle, Mako and Blue Shark 26. Red Hake 27. Redfish 28. Scallop 29. Scallop (quarterly composites Q1, Q2, Q3, Q4) 30. Sculpin 31. Sea Urchin 32. Shrimp 33. Silver Hake 34. Skate 35. Snow Crab 36. Squid 37. Swordfish 38. White Hake 39. Wolffish

Upplýsingar um eldissvæði í sjókvíaeldi sem eru í umsóknarferli hjá Matvælastofnun.

Herring Section shapefile - used for spatial analysis/presentation of data from Herring Stock Assessment Database.

This model is derived from geological, geophysical and other forms of geodata. Feature extraction used deep learning. Predictive modelling made use of the deep ensemble method. Displayed is a Pan-Canadian probability map of mineral potential of graphite. This map was generated using known graphite deposits and occurrences and their associated features. Higher probability values highlight areas with an increased probability of graphite mineral systems.