Location of flight lines of Yukon aerial photographs. Data was produced from heads up digitization of paper flight line index maps . Distributed from [GeoYukon](https://yukon.ca/geoyukon) by the [Government of Yukon](https://yukon.ca/maps) . Discover more digital map data and interactive maps from Yukon's digital map data collection. For more information: [geomatics.help@yukon.ca](mailto:geomatics.help@yukon.ca)

This report describes an analysis of Maritimes Region inshore lobster logbook data reported at a grid level, including Bay of Fundy Disputed Zone data reported at the coordinate level. Annual and composite (2015–2019) grid maps were produced for landings, number of trap hauls, and the same series standardized by grid area, as well as maps of catch weight per number of trap hauls as an index of catch per unit effort (CPUE). Spatial differences in fishing pressure, landings, and CPUE are indicated, and potential mapping applications are outlined. Mapping the distribution and intensity of inshore lobster fishing activity has management applications for spatial planning and related decision support. The lack of region-wide latitude and longitude coordinates for inshore lobster effort and landings limits the utility of commercial logbook data for marine spatial planning purposes.

The spatial representation for current Timber Supply Areas (TSA). A Timber Supply Area is a designated area established by the Ministry in order to practice sound, integrated, resource management principles to improve the allowable annual cuts. TSAs were originally defined by an established pattern of wood flow from management units to the primary timber-using industries. They are the primary unit for allowable annual cut (AAC) determination.

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

The Labour Force Distribution (LFD) maps are derived from the CanEcumene 2.0 Geodatabase using custom tabulations of census-based labour force data. These LFD maps were calculated for each of the five major natural resource sectors in Canada: Forestry, Fisheries, Agriculture, Minerals, and Petroleum and Coal. The measure used is the labour force of each sector as a proportion of the goods-producing sectors in the economy. Labour force proportions were first calculated at the individual community level, and then interpolated on a regional level using GIS (see Eddy et. al. 2020 for more detail). In effect, these maps show the strong importance of Canada’s natural resource sectors in various regions of the country. The darker the tone in each map indicates a region’s higher degree of dependency on a given sector for their economic livelihood.

**Attention: there is a new version of this product (SCANFI v2)** SCANFI v2 can be found here: https://doi.org/10.23687/07653869-f303-46c2-a04e-9ab479b73cbf This data publication contains a set of 30m resolution raster files representing 2020 Canadian wall-to-wall maps of broad land cover type, forest canopy height, degree of crown closure and aboveground tree biomass, along with species composition of several major tree species. The Spatialized CAnadian National Forest Inventory data product (SCANFI) was developed using the newly updated National Forest Inventory photo-plot dataset, which consists of a regular sample grid of photo-interpreted high-resolution imagery covering all of Canada’s non-arctic landmass. SCANFI was produced using temporally harmonized summer and winter Landsat spectral imagery along with hundreds of tile-level regional models based on a novel k-nearest neighbours and random forest imputation method. A full description of all methods and validation analyses can be found in Guindon et al. (2024). As the Arctic ecozones are outside NFI’s covered areas, the vegetation attributes in these regions were predicted using a single random forest model. The vegetation attributes in these arctic areas could not be rigorously validated. The raster file « SCANFI_aux_arcticExtrapolationArea.tif » identifies these zones. SCANFI is not meant to replace nor ignore provincial inventories which could include better and more regularly updated inputs, training data and local knowledge. Instead, SCANFI was developed to provide a current, spatially-explicit estimate of forest attributes, using a consistent data source and methodology across all provincial boundaries and territories. SCANFI is the first coherent 30m Canadian wall-to-wall map of tree structure and species composition and opens novel opportunities for a plethora of studies in a number of areas, such as forest economics, fire science and ecology. **Limitations** 1- The spectral disturbances of some areas disturbed by pests are not comprehensively represented in the training set, thus making it impossible to predict all defoliation cases. One such area, severely impacted by the recent eastern spruce budworm outbreak, is located on the North Shore of the St-Lawrence River. These forests are misrepresented in our training data, there is therefore an imprecision in our estimates. 2- Attributes of open stand classes, namely shrub, herbs, rock and bryoid, are more difficult to estimate through the photointerpretation of aerial images. Therefore, these estimates could be less reliable than the forest attribute estimates. 3- As reported in the manuscript, the uncertainty of tree species cover predictions is relatively high. This is particularly true for less abundant tree species, such as ponderosa pine and tamarack. The tree species layers are therefore suitable for regional and coarser scale studies. Also, the broadleaf proportion are slightly underestimated in this product version. 4- Our validation indicates that the areas in Yukon exhibit a notably lower R2 value. Consequently, estimates within these regions are less dependable. 5- Urban areas and roads are classified as rock, according to the 2020 Agriculture and Agri-Food Canada land-use classification map. Even though those areas contain mostly buildings and infrastructure, they may also contain trees. Forested urban parks are usually classified as forested areas. Vegetation attributes are also predicted for forested areas in agricultural regions. **Details on the product development and validation can be found in the following publication:** - Guindon, L., Manka, F., Correia, D.L.P., Villemaire, P., Smiley, B., Bernier, P., Gauthier, S., Beaudoin, A., Boucher, J., and Boulanger, Y. 2024. A new approach for Spatializing the Canadian National Forest Inventory (SCANFI) using Landsat dense time series. Can. J. For. Res. https://doi.org/10.1139/cjfr-2023-0118 **Please cite this dataset as:** - Guindon L., Villemaire P., Correia D.L.P., Manka F., Lacarte S., Smiley B. 2023. SCANFI: Spatialized CAnadian National Forest Inventory data product. Natural Resources Canada, Canadian Forest Service, Laurentian Forestry Centre, Quebec, Canada. https://doi.org/10.23687/18e6a919-53fd-41ce-b4e2-44a9707c52dc **The following raster layers are available:** - NFI land cover class values: Land cover classes include Water, Rock, Bryoid, Herbs, Shrub, Treed broadleaf, Treed mixed and Treed conifer - Live aboveground dry tree biomass (tonnes/ha): biomass was derived from total merchantable volume estimates produced by provincial agencies - Height (meters): vegetation height - Crown closure (%): percentage of pixel covered by the tree canopy - Tree species cover (%): estimated as the proportion of the canopy covered by each tree species: - Balsam fir tree cover in percentage (Abies balsamea) - Black spruce tree cover in percentage (Picea mariana) - Douglas fir tree cover in percentage (Pseudotsuga menziesii) - Jack pine tree cover in percentage (Pinus banksiana) - Lodgepole pine tree cover in percentage (Pinus contorta) - Ponderosa pine tree cover in percentage (Pinus ponderosa) - Tamarack tree cover in percentage (Larix laricina) - White and red pine tree cover in percentage (Pinus strobus and Pinus resinosa) - Broadleaf tree cover in percentage (PrcB) - Other coniferous tree cover in percentage (PrcC)

A Surveyed Sub-Surface Area Object that represents the spatial extent of a mineral claim to which sub-surface rights can be registered. In the Yukon, mineral claims can be classified as Quartz or Placer Claims, where as in other regions they are generically called mineral claims Distributed from [GeoYukon](https://yukon.ca/geoyukon) by the [Government of Yukon](https://yukon.ca/maps) . Discover more digital map data and interactive maps from Yukon's digital map data collection. For more information: [geomatics.help@yukon.ca](mailto:geomatics.help@yukon.ca)

Canadian airports served by NAV CANADA control towers or flight service station.