Programs that perform a laboratory analysis of body fluids and tissue to determine the presence of irregularities or to identify unknown substances submitted for analysis. Definition is protected by Copyright by Information and Referral Federal of Los Angeles County, Inc (https://211taxonomy.org/subscriptions/#agreement)

Satellite-based forest area consistent with FAO definitions for Canada. It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). The forest area is based on the Food and Agricultural Organization of the United Nations (FAO) definition. The FAO definition incorporates land use, whereby trees removed by fire and harvesting for instance, remain forest as the trees will return. The included map displays the current forest cover for year as noted (i.e. 2022), plus the satellite-based temporally informed forest area where tree cover has been temporarily lost due to stand replacing disturbances (i.e., fire, harvest). For an overview of the methods, data, image processing, as well as information on accuracy assessment see Wulder et al. (2020).Open Access: Wulder, M.A., T. Hermosilla, G. Stinson, F.A. Gougeon, J.C. White, D.A. Hill, B.P. Smiley. (2020). Satellite-based time series land cover and change information to map forest area consistent with national and international reporting requirements. Forestry: An International Journal of Forest Research 93(3), 331-34, https://doi.org/10.1093/forestry/cpaa0063 . ( Wulder et al. 2020)

This table is a list of polygon attributes to be used in map production for the vegetation Inventory map series. It contains attribute information for polygons in the inventory that are not labeled with the Inventory Annotation. Attribute information is pulled from this table to use as additional labels on the map layout for the Forest Inventory map series.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)

A polygon coverage showing the location of coalfields with coalbed methane (cbm) potential in BC

Food Banks is a point dataset identifying food banks in British Columbia.

This data is used for referencing spatial and tabular Forest Resource Processing Facility information. Each facility has one or more processing sites, each dedicated to processing resources for a specific purpose. For example, a pulp, paper and paperboard facility has one processing site to produce pulp, and another one dedicated to producing paper. All facilities that use 1,000 cubic metres or more of forest resources in one year must have a facility licence. This data class has been remodeled in 2014 to make it more flexible as a stand-alone product.

This spatial layer displays stream inventory sample sites that have had full or partial surveys, and contains measurements or indicator information of the data collected at each survey site on each date.

Coal Agreement feature class contains provincial extent polygon features representing Coal applications, agreements, leases, and licences, with varying term dates and conditions. These applications and subsequent agreements give the holder the right to explore Coal.

Local Government Offices is a point dataset identifying local government offices in British Columbia.

**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-9ab479b73cbfThis 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)