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)

Canada's National Forest Inventory (NFI) sampling program is designed to support reporting on forests at the national scale. On the other hand, continuous maps of forest attributes are required to support strategic analyses of regional policy and management issues. We have therefore produced maps covering 4.03 × 106 km2 of inventoried forest area for the 2001 base year using standardised observations from the NFI photo plots (PP) as reference data. We used the k nearest neighbours (kNN) method with 26 geospatial data layers including MODIS spectral data and climatic and topographic variables to produce maps of 127 forest attributes at a 250 × 250 m resolution. The stand-level attributes include land cover, structure, and tree species relative abundance. In this article, we report only on total live aboveground tree biomass, with all other attributes covered in the supplementary data (http://nrcresearchpress.com/doi/suppl/10.1139/cjfr-2013-0401). In general, deviations in predicted pixel-level values from those in a PP validation set are greater in mountainous regions and in areas with either low biomass or sparse PP sampling. Predicted pixel-level values are overestimated at small observed values and underestimated at large ones. Accuracy measures are improved through the spatial aggregation of pixels to 1 km2 and beyond. Overall, these new products provide unique baseline information for strategic-level analyses of forests (https://nfi.nfis.org)Collection:- **[Canada's National Forest Inventory (NFI) 2006](https://open.canada.ca/data/en/dataset/e2fadaeb-3106-4111-9d1c-f9791d83fbf4)**

The raster maps depict a suite of forest attributes in 2001* and 2011 at 250 m by 250 m spatial resolution. The maps were produced using the k nearest neighbours method applied to MODIS imagery and trained from National Forest Inventory photo plot data. For detailed information about map production methods please refer to Beaudoin et al. (2018) "Tracking forest attributes across Canada between 2001 and 2011 using the k nearest neighbours mapping approach applied to MODIS imagery." Canadian Journal of Forest Research 48, 85-93. https://cfs.nrcan.gc.ca/publications?id=38979 The map datasets may be downloaded from https://nfi.nfis.org/downloads/nfi_knn2011.zip or https://open.canada.ca/data/en/dataset/ec9e2659-1c29-4ddb-87a2-6aced147a990 * Note: the forest composition (leading tree genus) map depicts forest attributes in 2001.How can this data be used?The resolution and accuracy of these map products are best suited for strategic-level forest reporting and informing policy and decision making at regional to national scales. As these maps also offer a coherent set of quantitative values for a large suite of forest attributes, they can be used as baseline information for modelling and in calculations such as merchantable forest volume or percentage of tree species. It is also possible to overlay these maps with other maps produced on the same pixel grid to make assessments of disturbance impacts, such as fire and harvests.

The spatial representation for a Tree Farm Licence Deletion, which is forest land within the Tree Farm Licence that is being removed from the Tree Farm Licence Schedule 'A' or 'B' For further information on Tree Farm Licenses please visit this website: https://www2.gov.bc.ca/gov/content?id=A93E6DFD8C164AD19CD17880450289A3

The spatial representation for a Tree Farm Licence Schedule A, which is private land or timber owned by the Tree Farm licence holder that is part of the Established Tree Farm Licence. These private lands can be inside or outside the main body of the Tree Farm Licence For further information on Tree Farm Licenses please visit this website: https://www2.gov.bc.ca/gov/content?id=A93E6DFD8C164AD19CD17880450289A3

Geospatial forest inventory dataset updated for depletions, such as harvesting, and projected annually for growth. Sample attributes in this dataset include: age, species, volume, height. The Vegetation Resources Inventory (VRI) spatial datasets describe both where a vegetation resource (ie timber volume, tree species) is located and how much of a given resource is within an inventory unit. Suggested citation: Forest Analysis and Inventory Branch (2024). VRI - 2024 - Forest Vegetation Composite Rank 1 Layer (R1). British Columbia Data Catalogue. https://catalogue.data.gov.bc.ca/dataset/2ebb35d8-c82f-4a17-9c96-612ac3532d55

In 2013, the Earth Observation Team of the Science and Technology Branch (STB) at Agriculture and Agri-Food Canada (AAFC) repeated the process of generating annual crop inventory digital maps using satellite imagery to for all of Canada, in support of a national crop inventory. A Decision Tree (DT) based methodology was applied using optical (Landsat-8) and radar (RADARSAT-2) based satellite images, and having a final spatial resolution of 30m. In conjunction with satellite acquisitions, ground-truth information was provided by provincial crop insurance companies and point observations from the BC Ministry of Agriculture and our regional AAFC colleagues.

The raster maps depict a suite of forest attributes in 2001* and 2011 at 250 m by 250 m spatial resolution. The maps were produced using the k nearest neighbours method applied to MODIS imagery and trained from National Forest Inventory photo plot data. For detailed information about map production methods please refer to Beaudoin et al. (2018) "Tracking forest attributes across Canada between 2001 and 2011 using the k nearest neighbours mapping approach applied to MODIS imagery." Canadian Journal of Forest Research 48, 85-93. https://cfs.nrcan.gc.ca/publications?id=38979 The map datasets may be downloaded from https://nfi.nfis.org/downloads/nfi_knn2011.zip or https://open.canada.ca/data/en/dataset/ec9e2659-1c29-4ddb-87a2-6aced147a990 * Note: the forest composition (leading tree genus) map depicts forest attributes in 2001.How can this data be used?The resolution and accuracy of these map products are best suited for strategic-level forest reporting and informing policy and decision making at regional to national scales. As these maps also offer a coherent set of quantitative values for a large suite of forest attributes, they can be used as baseline information for modelling and in calculations such as merchantable forest volume or percentage of tree species. It is also possible to overlay these maps with other maps produced on the same pixel grid to make assessments of disturbance impacts, such as fire and harvests.

The raster maps depict a suite of forest attributes in 2001* and 2011 at 250 m by 250 m spatial resolution. The maps were produced using the k nearest neighbours method applied to MODIS imagery and trained from National Forest Inventory photo plot data. For detailed information about map production methods please refer to Beaudoin et al. (2018) "Tracking forest attributes across Canada between 2001 and 2011 using the k nearest neighbours mapping approach applied to MODIS imagery." Canadian Journal of Forest Research 48, 85-93. https://cfs.nrcan.gc.ca/publications?id=38979 The map datasets may be downloaded from https://nfi.nfis.org/downloads/nfi_knn2011.zip or https://open.canada.ca/data/en/dataset/ec9e2659-1c29-4ddb-87a2-6aced147a990 * Note: the forest composition (leading tree genus) map depicts forest attributes in 2001.How can this data be used?The resolution and accuracy of these map products are best suited for strategic-level forest reporting and informing policy and decision making at regional to national scales. As these maps also offer a coherent set of quantitative values for a large suite of forest attributes, they can be used as baseline information for modelling and in calculations such as merchantable forest volume or percentage of tree species. It is also possible to overlay these maps with other maps produced on the same pixel grid to make assessments of disturbance impacts, such as fire and harvests.

The spatial representation for a Tree Farm Licence Addition, which is forest land designated by the Ministry to be added to an established Tree Farm Licence Schedule A or B For further information on Tree Farm Licenses please visit this website: https://www2.gov.bc.ca/gov/content?id=A93E6DFD8C164AD19CD17880450289A3