Patterns of wet deposition of the nitrate (NO3), non-sea-salt sulfate (xSO4) and ammonium (NH4) ions across areas of Canada and the United States are based on measurements of precipitation depth and ion concentrations in precipitation samples. xSO4 refers to the wet deposition of sulfate with the sea-salt sulfate contribution removed at coastal sites. These measurements were collected and quality controlled by their respective networks: in Canada, the federal Canadian Air and Precipitation Monitoring Network (CAPMoN) and provincial or territorial networks in Alberta, New Brunswick, the Northwest Territories, Nova Scotia, Ontario and Quebec. In the United States, wet deposition measurements were made by two coordinated networks: the National Atmospheric Deposition Program (NADP) / National Trends Network (NTN) and the NADP/Atmospheric Integrated Research Monitoring Network (AIRMoN). Only data from sites that were designated as regionally representative were used in the mapping. Wet deposition amounts were interpolated by ordinary kriging using ArcMap Geostatistical Analyst. The map is limited to the contiguous U.S. and southeastern or southern Canada because outside that region, the interpolation error exceeds 30% due to the larger distances between stations. Links to annual and five-year average maps are available in the associated resources.

MetNotes are a geo- and time-referenced, free form polygon product issued by MSC that complement today's location-based dissemination systems. The concise text of a MetNote (similar to a Tweet) is consistent with communication today where people are seeking information at a glance. Meteorologists will issue a MetNote to add contextual and/or impact information to complement the public forecast that is valid over a specific area, for a specific time range.

This dataset provides the results obtained by Health Canada’s Canadian Radiological Monitoring Network (CRMN) for the gross alpha and beta activity concentrations in drinking water, given in units of becquerels per liter (Bq/L). More information about the CRMN network can be found on the Health Canada website (see link below). Although water quality is a matter of provincial jurisdiction, the CRMN, in collaboration with the city of Ottawa, has been conducting a targeted program to monitor the radiological content of drinking water from two water treatment plants in Ottawa, ON. The Guidelines for Canadian Drinking Water Quality recommend screening levels of 0.5 Bq/L and 1.0 Bq/L for gross alpha and gross beta activity, respectively. The screening levels are set to reflect the most restrictive Maximum Acceptable Concentrations (MACs) for specific radionuclides in drinking water. If the screening levels are not exceeded, compliance with the guidelines can be inferred. The screening levels set out in the Guidelines for Canadian Drinking Water Quality are calculated based on annual averages of radionuclides in drinking water. Short-term exposure to levels above those recommended by these guidelines does not indicate a health risk. The measured gross alpha and gross beta activity concentrations presented here are well below the screening levels set by the Guidelines for Canadian Drinking Water Quality, with only one exception to date. This occurred February 28, 2011, and was attributable to the flushing of lead pipes at the water treatment plant. It resulted in a spike of naturally occurring lead radionuclides that was dealt with immediately by the City of Ottawa. The map shows the approximate sampling location for each monitoring station. Stations are found within the associated location range.

Crown Game Preserves were established to prohibit or regulate the hunting and trapping of wildlife in specific areas to restore local populations.

Forest Lorey's Height 2015Lorey's mean height. It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). Average height of trees weighted by their basal area (m). Products relating the structure of Canada's forested ecosystems have been generated and made openly accessible. The shared products are based upon peer-reviewed science and relate aspects of forest structure including: (i) metrics calculated directly from the lidar point cloud with heights normalized to heights above the ground surface (e.g., canopy cover, height), and (ii) modelled inventory attributes, derived using an area-based approach generated by using co-located ground plot and ALS data (e.g., volume, biomass). Forest structure estimates were generated by combining information from lidar plots (Wulder et al. 2012) with Landsat pixel-based composites (White et al. 2014; Hermosilla et al. 2016) using a nearest neighbour imputation approach with a Random Forests-based distance metric. These products were generated for strategic-level forest monitoring information needs and are not intended to support operational-level forest management. All products have a spatial resolution of 30 m. For a detailed description of the data, methods applied, and accuracy assessment results see Matasci et al. (2018). When using this data, please cite as follows: Matasci, G., Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., Hobart, G.W., Bolton, D.K., Tompalski, P., Bater, C.W., 2018b. Three decades of forest structural dynamics over Canada's forested ecosystems using Landsat time-series and lidar plots. Remote Sensing of Environment 216, 697-714. Matasci et al. 2018)Geographic extent: Canada's forested ecosystems (~ 650 Mha)Time period: 1985–2011

The Common Attribute Schema for Forest Resource Inventories (CASFRI) is a Canadian forest resource inventory data repository. Forest resource inventory datasets in CASFRI are harmonized to a common data model so that data collected by different agencies following different standards can be used together. Participating provincial, territorial and federal government departments and agencies share current and historical map-based forest resource inventory datasets through CASFRI so that their data are available to users who’s areas of interest span multiple jurisdictions. CASFRI was originally developed by academic researchers (Cumming et al., https://doi.org/10.1139/cjfr-2014-0102). This flavour of CASFRI (CASFRIv5) was developed anew in collaboration with academic researchers at the University of Laval to provide a government version of CASFRI that is findable, accessible, interoperable, and reusable. It uses the most up-to-date forest inventory data provided by participating provincial, territorial, and federal government departments and agencies. CASFRIv5 is hosted on the Canadian Council of Forest Ministers’ data portal, the National Forest Information System (http://nfis.org).

Forest Elevation(Ht) Mean 2015Mean height of lidar first returns (m). Represents the mean canopy height. It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). Products relating the structure of Canada's forested ecosystems have been generated and made openly accessible. The shared products are based upon peer-reviewed science and relate aspects of forest structure including: (i) metrics calculated directly from the lidar point cloud with heights normalized to heights above the ground surface (e.g., canopy cover, height), and (ii) modelled inventory attributes, derived using an area-based approach generated by using co-located ground plot and ALS data (e.g., volume, biomass). Forest structure estimates were generated by combining information from lidar plots (Wulder et al. 2012) with Landsat pixel-based composites (White et al. 2014; Hermosilla et al. 2016) using a nearest neighbour imputation approach with a Random Forests-based distance metric. These products were generated for strategic-level forest monitoring information needs and are not intended to support operational-level forest management. All products have a spatial resolution of 30 m. For a detailed description of the data, methods applied, and accuracy assessment results see Matasci et al. (2018). When using this data, please cite as follows: Matasci, G., Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., Hobart, G.W., Bolton, D.K., Tompalski, P., Bater, C.W., 2018b. Three decades of forest structural dynamics over Canada's forested ecosystems using Landsat time-series and lidar plots. Remote Sensing of Environment 216, 697-714. Matasci et al. 2018) Wulder et al. 2018)Geographic extent: Canada's forested ecosystems (~ 650 Mha)Time period: 1985–2011

A Sign is a lettered board, message or other display which includes all regulatory, warning, guide, informational, advisory, construction and maintenance and route markers, but excluding electronically controlled messages/displays. It is a Point feature

The Common Attribute Schema for Forest Resource Inventories (CASFRI) is a Canadian forest resource inventory data repository. Forest resource inventory datasets in CASFRI are harmonized to a common data model so that data collected by different agencies following different standards can be used together. Participating provincial, territorial and federal government departments and agencies share current and historical map-based forest resource inventory datasets through CASFRI so that their data are available to users who’s areas of interest span multiple jurisdictions. CASFRI was originally developed by academic researchers (Cumming et al., https://doi.org/10.1139/cjfr-2014-0102). This flavour of CASFRI (CASFRIv5) was developed anew in collaboration with academic researchers at the University of Laval to provide a government version of CASFRI that is findable, accessible, interoperable, and reusable. It uses the most up-to-date forest inventory data provided by participating provincial, territorial, and federal government departments and agencies. CASFRIv5 is hosted on the Canadian Council of Forest Ministers’ data portal, the National Forest Information System (http://nfis.org).

**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.# 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)