The 1 cm resolution vegetation digital height model was extracted using a bare earth model and digital surface model (DSM) derived from unmanned aerial vehicle (UAV) imagery acquired from a single day survey on July 28th 2016, in Cambridge Bay, Nunavut. The mapping product covers 525m2 and was produced by Canada Centre for Remote Sensing /Canada Centre for Mapping and Earth Observation. The UAV survey was completed in collaboration with the Canadian High Arctic Research Station (CHARS) for northern vegetation monitoring research. For more information, refer to our current Arctic vegetation research: Fraser et al; "UAV photogrammetry for mapping vegetation in the low-Arctic" Arctic Science, 2016, 2(3): 79-102. http://www.nrcresearchpress.com/doi/abs/10.1139/AS-2016-0008

This publication contains vector data (shapefile) of the post-harvest forest residues in Canada for the bioenergy/bioproducts sector in oven-dry tonnes per year (ODT/yr) over the next 20 years. The maps were produced using different remote sensing products. We used forest attribute data at 250 m MODIS for the years 2001 and 2011 (Beaudoin et al. 2014 and 2018) combined with forest cover changes for the years 1985 to 2015 contained in the CanLaD dataset at 30 m Landsat(Guindon et al. 2017 and 2018). Results of available biomass (in the form of harvest residues) were reported at the 10 km x 10 km scale, while the map of mature forests in Canada was prepared at the forest management unit (FMU) level. Briefly, our methodology consisted of three steps: 1- create a map of mature forests for the year 2011, based on 2001-2010 average cut volumes within FMUs; 2- develop an annual cut rate from the area harvested within FMUs from 1985 to 2015 and; 3- define the amount of biomass in the form of forest residues available for the bioenergy sector. The biomass of branches and leaves of forest attribute data was used as a proxy to define the biomass of forest residues available. Nationally, the average biomass of forest residues available after harvest is 26 ± 16 ODT/ha, while the total annual availability for all managed forests in Canada was 21 million ODT/yr. A scientific article gives additional details on the methodology: Barrette J, Paré D, Manka F, Guindon L, Bernier P, Titus B. 2018. Forecasting the spatial distribution of logging residues across the Canadian managed forest. Can. J. For. Res. 48: http://www.nrcresearchpress.com/doi/10.1139/cjfr-2018-0080 Reference for this dataset: Barrette J, Paré D, Manka F, Guindon L, Bernier P, Titus B. 2018. Maps forecasting the availability of logging residues in Canada. Natural Resources Canada, Canadian Forest Service, Laurentian Forestry Centre, Quebec, Canada. https://doi.org/10.23687/5072c495-240c-42a3-ad55-c942ab37c32a

IBL - Imagery, basemaps, and land cover (imageryBaseMapsEarthCover) Basemaps. For example, resources describing land cover, topographic maps, and classified and unclassified images

The Canadian long term satellite data record (LTDR) derived from 1-km resolution Advanced Very High Resolution Radiometer (AVHRR) data was produced by the Canada Center for Remote Sensing (CCRS). Processing included: geolocation, calibration, and compositing using Earth Observation Data Manager (Latifovic et al. 2005), cloud screening (Khlopenkov and Trishchenko, 2006), BRDF correction (Latifovic et. al., 2003), atmosphere and other corrections as described in Cihlar et. al. (2004). For temporal analysis of vegetation cross-sensor correction of Latifovic et al. (2012) is advised. Data collected by the AVHRR instrument on board the National Oceanic and Atmospheric Administration (NOAA) 9,11,14,16,17,18 and 19 satellites were used to generate Canada-wide 1-km 10-day AVHRR composites. Data are available starting in 1985. It is important to note that there are three types of AVHRR sensors: (i) AVHRR-1 flown onboard TIROS-N, NOAA-6, NOAA-8, and NOAA-10; (ii) AVHRR-2 flown onboard NOAA-7, NOAA-9, NOAA-11, NOAA-12, and NOAA-14; and (iii) AVHRR-3 currently operational onboard NOAA-15, NOAA-16, NOAA-17, NOAA-18 and NOAA-19. The AVHRR-1 has four channels, AVHRR-2 has five channels and the AVHRR-3 has six channels, although only five channels of AVHRR-3 can be operational at any one time. As such, channels 3A (1.6 m) and 3B (3.7 m) work interchangeably. The processing procedure was designed to minimize artefacts in AVHRR composite images. There are thirty six 10-day image composites per year. The following three processing levels are provided: P1) top of atmosphere reflectance and brightness temperature, P2) reflectance at surface and surface temperature and P3) reflectance at surface normalized to a common viewing geometry (BRDF normalization). The processing level P1 and P2 are provided for all 36 composites while level P3 is provided for 21 composites from April – October.

Leaf area index (LAI) quantified the density of vegetation irrespective of land cover. LAI quantifies the total foliage surface area per ground surface area. LAI has been identified by the Global Climate Observing System as an essential climate variable required for ecosystem, weather and climate modelling and monitoring. This product consists of a national scale coverage (Canada) of monthly maps of the maximum LAI during a growing season (May-June-july-August-September) at 20m. References: L. Brown, R. Fernandes, N. Djamai, C. Meier, N. Gobron, H. Morris, C. Canisius, G. Bai, C. Lerebourg, C. Lanconelli, M. Clerici, J. Dash. Validation of baseline and modified Sentinel-2 Level 2 Prototype Processor leaf area index retrievals over the United States IISPRS J. Photogramm. Remote Sens., 175 (2021), pp. 71-87, https://doi.org/10.1016/j.isprsjprs.2021.02.020. https://www.sciencedirect.com/science/article/pii/S0924271621000617 Richard Fernandes, Luke Brown, Francis Canisius, Jadu Dash, Liming He, Gang Hong, Lucy Huang, Nhu Quynh Le, Camryn MacDougall, Courtney Meier, Patrick Osei Darko, Hemit Shah, Lynsay Spafford, Lixin Sun, 2023. Validation of Simplified Level 2 Prototype Processor Sentinel-2 fraction of canopy cover, fraction of absorbed photosynthetically active radiation and leaf area index products over North American forests, Remote Sensing of Environment, Volume 293, https://doi.org/10.1016/j.rse.2023.113600. https://www.sciencedirect.com/science/article/pii/S0034425723001517

The Saskatchewan Digital Land Cover was created to be used in the interim. The National Land Cover Project plans to integrate land cover information compiled by Natural Resources Canada, Canadian Forest Service, and Agriculture and Agri-Food Canada. The Saskatchewan Digital Land Cover raster provides a seamless provincial coverage of the province and was created by combining the Saskatchewan Research Council's Northern Digital Land Cover (NDLC) with the Southern Digital Land Cover (SDLC).  With exception to the SDLC's value 2 (i.e. Hay Crops) and value 3 (i.e. Native Dominant Grass Lands), the NDLC takes precedence over the SDLC in areas that the two rasters overlap because the NDLC is more current than the dated SDLC. The SDLC's values 2 and 3 were preserved because these land covers are not specifically represented in the NDLC. For the purpose of this dataset, some of the SDLC and NDLC values were reclassified to new values to reconcile varying definitions.  It should also be noted that because the NDLC's 30 x 30 metre pixels do not align with the SDLC's 30 x 30 metre pixels, this raster was snapped to the NDLC. Last, as is with the SDLC and the NDLC, the extent of this raster does not extend all of the way to the Saskatchewan boundary, specifically, the Information Services Corporation's SaskGIS Provincial Boundary dataset, in numerous areas along the west, south and southeast borders: There are gaps of up to 500 m wide of "no data" between the provincial boundary and the raster along these areas of the Saskatchewan boundary. Classification Value AGRICULTURE 1 HAY CROPS 2 NATIVE DOMINANT GRASSLANDS 3 TALL SHRUBS 4 PASTURE 5 HARDWOODS (OPEN CANOPY) 6 HARDWOODS (CLOSED CANOPY) 7 JACKPINE (CLOSED CANOPY) 8 JACKPINE (OPEN CANOPY) 9 SPRUCE (CLOSED CANOPY) 10 SPRUCE (OPEN CANOPY) 11 MIXED WOODS 12 TREED ROCK 13 RECENT BURNS 14 REVEGETATING/REGENERATION BURN 15 CUTOVERS 16 WATER 17 MARSH 18 HERBACEOUS FEN 19 MUD/SAND/SALINE 20 SHRUB FEN (TREED SWAMP) 21 TREED BOG 22 OPEN BOG 23 FARMSTEAD 24 UNCLASSIFIED 25 BARREN LAND 26 MIXED SOFTWOODS (OPEN & CLOSED) 27 PASTURE UPLAND HERBACEOUS GRAMINOID 30 1. AGRICULTURE - Cropland, including all lands dedicated to the production of annual cereal, oil seed, and other specialty crops, and typically cultivated on an annual basis; and agricultural clearing areas.  2. HAY CROPS (Forage) - Alfalfa and alfalfa/tame grass mixtures.  3. NATIVE DOMINANT GRASSLANDS - Native dominant grasslands. (May contain tame grasses and herbs.)  4. TALL SHRUBS - Communities containing both low and tall shrub, snowberry, saskatoon, chokecherry, buffaloberry, and willow.  5. PASTURE (Seeded Grass Lands) - Grassland dominated by tame grass species.  6. HARDWOODS (I.E. OPEN CANOPY) - Greater than 75% hardwoods by area, including trembling aspen, white birch, balsam poplar; 10 - 55% crown closure.  7. HARDWOODS (I.E. CLOSED CANOPY) - Greater than 75% hardwoods by area, including trembling aspen, white birch, balsam poplar; Greater than 55% crown closure.  8. JACKPINE (I.E. CLOSED CANOPY) - Greater than 75% of Jack Pine by area; Greater than 55% crown closure.  9. JACKPINE (I.E. OPEN CANOPY) - Greater than 75% of Jack Pine by area; 10 - 55% crown closure.  10. SPRUCE (I.E. CLOSED CANOPY) - Greater than 75% or greater Black and White Spruce; Greater than 55% crown closure.  11. SPRUCE (I.E. OPEN CANOPY) - Greater than 75% Black and White Spruce; 10-55% crown closure.  12. MIXED WOODS - All softwood/hardwood mixtures; open and closed canopy (i.e. An area of hardwood and softwood combinations in which neither hardwood nor softwood account for greater than 75% of species by area, and where the crown closure is greater than 10%).  13. TREED ROCK - Areas of exposed bedrock with generally less then 10% tree cover.  14. RECENT BURNS - An area showing evidence of recent burning natural or prescribed and there is little to no regeneration or revegetation visible.  15. REVEGETATING/REGENERATION BURN - An area showing evidence of natural or prescribed burning and where regeneration or revegetation is visible.  16. CUTOVERS - An area of deforestation, vegetated and non-vegetated.  17. WATER - These areas include lakes, rivers, streams and reservoirs  18. MARSH - A periodically wet or continually flooded but non peat-forming area supporting grasses, sedges, and reeds.  19. HERBACEOUS FEN - A wetland area consisting of decomposing peat supporting vascular and nonvascular plants (i.e. grasses, sedges, reeds).  20. MUD/SAND/SALINE - Water saturated soil, sand containing no vegetation, and salt water.  21. SHRUB FEN (I.E. TREED SWAMP) - A wetland area consisting of decomposing peat supporting low shrubs, forbs, grass, moss, and a sparse tree cover.  22. TREED BOG - A wetland area consisting of decomposing peat moss, lichen, and shrubs, with 10% or more canopy by trees (i.e. primarily black spruce and tamarack).  23. OPEN BOG - A wetland area consisting of decomposing peat moss, lichen, and sparse tree cover.  24. FARMSTEAD - Farmsteads, towns, cities, exposed areas with little or no vegetation.  25. UNCLASSIFIED  26. BARREN LAND - Any area of exposed rock, soil, or non-vegetated land.  27. MIXED SOFTWOODS (OPEN & CLOSED) - Jack Pine/Spruce, Spruce/Jack Pine Open and Closed, an area of softwood combinations in which neither Jack Pine or Spruce account for greater than 75% of species by area, and where crown closure is greater than 10%.  30. PASTURE UPLAND HERBACEOUS GRAMINOID - Lands containing known pastures, tame or native grasses, and herbaceous vegetation. These lands may contain low-lying shrubs with less then 10% tree cover.

The 2010 AAFC Land Use is a culmination and curated metaanalysis of several high-quality spatial datasets produced between 1990 and 2021 using a variety of methods by teams of researchers as techniques and capabilities have evolved. The information from the input datasets was consolidated and embedded within each 30m x 30m pixel to create consolidated pixel histories, resulting in thousands of unique combinations of evidence ready for careful consideration. Informed by many sources of high-quality evidence and visual observation of imagery in Google Earth, we apply an incremental strategy to develop a coherent best current understanding of what has happened in each pixel through the time series.

Note: To visualize the data in the viewer, zoom into the area of interest. The National Air Photo Library (NAPL) of Natural Resources Canada archives over 6 million aerial photographs covering all of Canada, some of which date back to the 1920s. This collection includes Time Series of aerial orthophoto mosaics over a selection of major cities or targeted areas that allow the observation of various changes that occur over time in those selected regions. These mosaics are disseminated through the Data Cube Platform implemented by NRCan using geospatial big data management technologies. These technologies enable the rapid and efficient visualization of high-resolution geospatial data and allow for the rapid generation of dynamically derived products. The data is available as Cloud Optimized GeoTIFF (COG) for direct access and as Web Map Services (WMS) or Web Coverage Services (WCS) with a temporal dimension for consumption in Web or GIS applications. The NAPL mosaics are made from the best spatial resolution available for each time period, which means that the orthophotos composing a NAPL Time Series are not necessarily coregistrated. For this dataset, the spatial resolutions are: 100 cm for the year 1932 and 50 cm for the year 1950. The NAPL indexes and stores federal aerial photography for Canada, and maintains a comprehensive historical archive and public reference centre. The Earth Observation Data Management System (EODMS) online application allows clients to search and retrieve metadata for over 3 million out of 6 million air photos. The EODMS online application enables public and government users to search and order raw Government of Canada Earth Observation images and archived products managed by NRCan such as aerial photos and satellite imagery. To access air photos, you can visit the EODMS web site: https://eodms-sgdot.nrcan-rncan.gc.ca/index-en.html

Leaf area index (LAI) quantified the density of vegetation irrespective of land cover. LAI quantifies the total foliage surface area per groud surface area. LAI has been identified by the Global Climate Observing System as an essential climate variable required for ecosystem,weather and climate modelling and monitoring. This product consists of annual maps of the maximum LAI during a grownig season (June-July-August) at 100m resolution covering Canada's land mass.

This data publication contains two collections of raster maps of forest attributes across Canada, the first collection for year 2001, and the second for year 2011. The 2001 collection is actually an improved version of an earlier set of maps produced also for year 2001 (Beaudoin et al 2014, DOI: https://doi.org/10.1139/cjfr-2013-0401) that is itself available through the web site “http://nfi-nfis.org”. Each collection contains 93 maps of forest attributes: four land cover classes, 11 continuous stand-level structure variables such as age, volume, biomass and height, and 78 continuous values of percent composition for tree species or genus. The mapping was done at a spatial resolution of 250m along the MODIS grid. Briefly the method uses forest polygon information from the first version of photoplots database from Canada’s National Forest Inventory as reference data, and the non-parametric k-nearest neighbors procedure (kNN) to create the raster maps of forest attributes. The approach uses a set of 20 predictive variables that include MODIS spectral reflectance data, as well as topographic and climate data. Estimates are carried out on target pixels across all Canada treed landmass that are stratified as either forest or non-forest with 25% forest cover used as a threshold. Forest cover information was extracted from the global forest cover product of Hansen et al (2013) (DOI: https://doi.org/10.1126/science.1244693). The mapping methodology and resultant datasets were intended to address the discontinuities across provincial borders created by their large differences in forest inventory standards. Analysis of residuals has failed to reveal residual discontinuities across provincial boundaries in the current raster dataset, meaning that our goal of providing discontinuity-free maps has been reached. The dataset was developed specifically to address strategic issues related to phenomena that span multiple provinces such as fire risk, insect spread and drought. In addition, the use of the kNN approach results in the maintenance of a realistic covariance structure among the different variable maps, an important property when the data are extracted to be used in models of ecosystem processes. For example, within each pixel, the composition values of all tree species add to 100%. * Details on the product development and validation can be found in the following publication: Beaudoin, A., Bernier, P.Y., Villemaire, P., Guindon, L., Guo, X.-J. 2017. Tracking forest attributes across Canada between 2001 and 2011 using a kNN mapping approach applied to MODIS imagery, Canadian Journal of Forest Research 48: 85–93. DOI: https://doi.org/10.1139/cjfr-2017-0184 * Please cite this dataset as: Beaudoin A, Bernier PY, Villemaire P, Guindon L, Guo XJ. 2017. Species composition, forest properties and land cover types across Canada’s forests at 250m resolution for 2001 and 2011. Natural Resources Canada, Canadian Forest Service, Laurentian Forestry Centre, Quebec, Canada. https://doi.org/10.23687/ec9e2659-1c29-4ddb-87a2-6aced147a990 * This dataset contains these NFI forest attributes: ## LAND COVER : landbase vegetated, landbase non-vegetated, landcover treed, landcover non-treed ## TREE STRUCTURE : total above ground biomass, tree branches biomass, tree foliage biomass, stem bark biomass, stem wood biomass, total dead trees biomass, stand age, crown closure, tree stand heigth, merchantable volume, total volume ## TREE SPECIES : abies amabilis (amabilis fir), abies balsamea (balsam fir), abies lasiocarpa (subalpine fir), abies spp. (unidentified fir), acer macrophyllum (bigleaf maple), acer negundo (manitoba maple, box-elder), acer pensylvanicum (striped maple), acer rubrum (red maple), acer saccharinum (silver maple), acer saccharum (sugar maple), acer spicatum (mountain maple), acer spp. (unidentified maple), alnus rubra (red alder), alnus spp. (unidentified alder), arbutus menziesii (arbutus), betula alleghaniensis (yellow birch), betula papyrifera (white birch), betula populifolia (gray birch), betula spp. (unidentified birch), carpinus caroliniana (blue-beech), carya cordiformis (bitternut hickory), chamaecyparis nootkatensis (yellow-cedar), fagus grandifolia (american beech), fraxinus americana (white ash), fraxinus nigra (black ash), fraxinus pennsylvanica (red ash), juglans cinerea (butternut), juglans nigra (black walnut), juniperus virginiana (eastern redcedar), larix laricina (tamarack), larix lyallii (subalpine larch), larix occidentalis (western larch), larix spp. (unidentified larch), malus spp. (unidentified apple), ostrya virginiana (ironwood, hop-hornbeam), picea abies (norway spruce), picea engelmannii (engelmann spruce), picea glauca (white spruce), picea mariana (black spruce), picea rubens (red spruce), picea sitchensis (sitka spruce), picea spp. (unidentified spruce), pinus albicaulis (whitebark pine), pinus banksiana (jack pine), pinus contorta (lodgepole pine), pinus monticola (western white pine), pinus ponderosa (ponderosa pine), pinus resinosa (red pine), pinus spp. (unidentified pine), pinus strobus (eastern white pine), pinus sylvestris (scots pine), populus balsamifera (balsam poplar), populus grandidentata (largetooth aspen), populus spp. (unidentified poplar), populus tremuloides (trembling aspen), populus trichocarpa (black cottonwood), prunus pensylvanica (pin cherry), prunus serotina (black cherry), pseudotsuga menziesii (douglas-fir), quercus alba (white oak), quercus macrocarpa (bur oak), quercus rubra (red oak), quercus spp. (unidentified oak), salix spp. (unidentified willow), sorbus americana (american mountain-ash), thuja occidentalis (eastern white-cedar), thuja plicata (western redcedar), tilia americana (basswood), tsuga canadensis (eastern hemlock), tsuga heterophylla (western hemlock), tsuga mertensiana (mountain hemlock), tsuga spp. (unidentified hemlock), ulmus americana (white elm), unidentified needleaf, unidentified broadleaf, broadleaf species, needleaf species, unknown species