Background:More than 80% of the heat produced in the Earth's crust comes from granitoid rocks. When granitoid rocks form they naturally concentrate radioactive elements such as U, Th, and K, and the radiogenic decay of these elements is an exothermic reaction. The radioactive decay of these elements within a granitoid body may generate local heat anomalies and elevated geothermal gradient at relatively shallow crustal levels. In combination with other local rock properties (e.g, porosity, permeability, thermal conductivity), radiogenic heat has the potential to generate a geothermal resource. The decay of radioactive elements converts mass into radiation energy, which in turn gets converted to heat. While all naturally radioactive isotopes generate some heat, significant heat generation only occurs from the decay of 238 U ,235 U ,232 Th and 40 K. Therefore, potential heat production is governed by the concentrations of U ,Th and K in the rock. In igneous rocks, radiogenic heat production is dependent on the bulk chemistry of the rock and decreases from acidic (e.g. granite) through basic to ultra basic rock types. Therefore, granites with anomalously high concentrations of U ,Th and K are targets for calculating potential radiogenic heat production. Potential radiogenic heat production (A)from plutonic rocks can be calculated using this equation:A (\\u03BCW/m 3 )=10 -5 \\u1D29 (9.52c u +2.56c K +3.48c Th )where "c" is the concentration of radioactive elements "U" and "Th" in ppm, and "K" in %; and "\\u1D29" is the rock density. Heat production constants of the natural radio-elements U, Th, K are 9.525x10 -5 , 2.561x10 -5 and 3.477x10 -9 W/kg, respectively.Data and Methods:Geochemical data from \~1760 samples of plutonic rocks from Yukon are used to calculate potential heat production. The calculated values for radiogenic heat production (A) are plotted over the mapped distribution of Paleozoic and younger plutonic rocks and major crustal faults are also shown for reference.

The Bedrock Index provides a spatial record of the location of all Bedrock maps published by the Geological Survey of Canada and hosted on Geoscan. The index has three "series" of maps; CGM, A series, and preliminary maps. In cases where there have been multiple editions of a map, the most recent record is reported in the Bedrock Index attribute table. Maps published in Open File documents are not recorded in the bedrock index. The "A" series maps were produced from 1909 to 2010 and have been replaced by the CGM (Canadian Geoscience Maps) series. CGM maps began production in 2010 and are still being published. Preliminary maps were published from 1941 to 2021.

Sub-surface facilities used for storing natural gas. The facilities are usually hollowed-out salt domes, geological reservoirs (depleted oil or gas field) or water bearing sands (called aquifers) topped by an impermeable cap rock.Mapping Resources implemented as part of the North American Cooperation on Energy Information (NACEI) between the Department of Energy of the United States of America, the Department of Natural Resources of Canada, and the Ministry of Energy of the United Mexican States.The participating Agencies and Institutions shall not be held liable for improper or incorrect use of the data described and/or contained herein. These data and related graphics, if available, are not legal documents and are not intended to be used as such. The information contained in these data is dynamic and may change over time and may differ from other official information. The Agencies and Institutions participants give no warranty, expressed or implied, as to the accuracy, reliability, or completeness of these data.

The National Ecological Framework for Canada's "Surface Material by Ecozone” dataset provides surface material information within the ecozone framework polygon. It provides surface material codes and their English and French language descriptions as well as information about the percentage of the polygon that the component occupies. Surface material includes the abiotic material at the earth's surface. The materials can be: ICE and SNOW - Glacial ice and permanent snow ORGANIC SOIL - Contains more than 30% organic matter as measured by weight ROCK - Rock undifferentiated MINERAL SOIL - Predominantly mineral particles: contains less than 30% organic matter as measured by weight URBAN - Urban areas. Note that only a few major urban area polygons are included on SLC source maps, therefore, do not use for tabulating total urban coverage

The National Ecological Framework for Canada's "Surface Material by Ecoregion” dataset provides surface material information within the ecoregion framework polygon. It provides surface material codes and their English and French language descriptions as well as information about the percentage of the polygon that the component occupies. Surface material includes the abiotic material at the earth's surface. The materials can be: ICE and SNOW - Glacial ice and permanent snow ORGANIC SOIL - Contains more than 30% organic matter as measured by weight ROCK - Rock undifferentiated MINERAL SOIL - Predominantly mineral particles: contains less than 30% organic matter as measured by weight URBAN - Urban areas. Note that only a few major urban area polygons are included on SLC source maps, therefore, do not use for tabulating total urban coverage

The National Ecological Framework for Canada's "Surface Material by Ecoprovince” dataset provides surface material information within the ecoprovince framework polygon. It provides surface material codes and their English and French language descriptions as well as information about the percentage of the polygon that the component occupies. Surface material includes the abiotic material at the earth's surface. The materials can be: ICE and SNOW - Glacial ice and permanent snow ORGANIC SOIL - Contains more than 30% organic matter as measured by weight ROCK - Rock undifferentiated MINERAL SOIL - Predominantly mineral particles: contains less than 30% organic matter as measured by weight URBAN - Urban areas. Note that only a few major urban area polygons are included on SLC source maps, therefore, do not use for tabulating total urban coverage

The extent of Sedimentary Rock as defined by Yukon Geological Survey, data is based on "GSC Open File 4673" .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)

The National Ecological Framework for Canada's "Surface Material by Ecodistrict” dataset provides surface material information within the ecodistrict framework polygon. It provides surface material codes and their English and French language descriptions as well as information about the percentage of the polygon that the component occupies. Surface material includes the abiotic material at the earth's surface. The materials can be: ICE and SNOW - Glacial ice and permanent snow ORGANIC SOIL - Contains more than 30% organic matter as measured by weight ROCK - Rock undifferentiated MINERAL SOIL - Predominantly mineral particles: contains less than 30% organic matter as measured by weight URBAN - Urban areas. Note that only a few major urban area polygons are included on SLC source maps, therefore, do not use for tabulating total urban coverage.

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.# Limitations1- 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.Updates of this dataset will eventually be available on this metadata page.# 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• Aboveground 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: o Balsam fir tree cover in percentage (Abies balsamea) o Black spruce tree cover in percentage (Picea mariana) o Douglas fir tree cover in percentage (Pseudotsuga menziesii) o Jack pine tree cover in percentage (Pinus banksiana) o Lodgepole pine tree cover in percentage (Pinus contorta) o Ponderosa pine tree cover in percentage (Pinus ponderosa) o Tamarack tree cover in percentage (Larix laricina) o White and red pine tree cover in percentage (Pinus strobus and Pinus resinosa) o Broadleaf tree cover in percentage (PrcB) o Other coniferous tree cover in percentage (PrcC)

As part of the International Polar Year (IPY) 2007'08 and 2008'09 activities, and related objectives of the Commission for the Geological Map of the World (CGMW), nations of the circumpolar Arctic have co-operated to produce a new bedrock geology map and related digital map database at a scale of 1:5 000 000. The map, released in north polar stereographic projection using the World Geodetic System (WGS) 84 datum, includes complete geological and physiographic coverage of all onshore and offshore bedrock areas north of latitude 60° north.