The Open Database of Healthcare Facilities (ODHF) is a collection of open data containing the names, types, and locations of health facilities across Canada. It is released under the Open Government License - Canada.The ODHF compiles open, publicly available, and directly-provided data on health facilities across Canada. Data sources include regional health authorities, provincial, territorial and municipal governments, and public health and professional healthcare bodies. This database aims to provide enhanced access to a harmonized listing of health facilities across Canada by making them available as open data. This database is a component of the Linkable Open Data Environment (LODE).

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 dataset includes all MPMO projects at various stages in the review process, including those that are currently undergoing review and those that have completed a review.

The Treaty Boundary dataset is comprised of all the polygons that represent the historical treaty lands of Canada negotiated by First Nations over the years through treaty-making between 1867 - 1999. The approximate boundaries illustrate the traditional territories described in First Nations Statements of Intent to negotiate treaties which have been submitted to, and accepted.

A Linear Safety Feature is one of a number of various appliances/appurtenances that have been installed or constructed either alongside or as an integral part of the road infrastructure to reduce the severity or potential of accidents. It is a Linear feature

A trapline area is a polygon feature that identifies a ministry-regulated boundary used to administer traplines and fur management programs.

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 Canadian Index of Multiple Deprivation (CIMD) is an area-based index which used 2021 Census of Population microdata to measure four key dimensions of deprivation at the dissemination area (DA)-level: residential instability, economic dependency, situational vulnerability and ethno-cultural composition.Using factor analysis, DA-level factor scores were calculated for each dimension. Within a dimension, ordered scores were assigned a quintile value, 1 through 5, where 1 represents the least deprived and 5 represents the most deprived.The CIMD allows for an understanding of inequalities in various measures of health and social well-being. While it is a geographically-based index of deprivation and marginalization, it can also be used as a proxy for an individual. The CIMD has the potential to be widely used by researchers on a variety of topics related to socio-economic research. Other uses for the index may include: policy planning and evaluation, or resource allocation.*** Correction October 22, 2024 ***A correction has been made to the variables in the following downloadable 2021 CIMD index datasets : Canada, Atlantic, Quebec, Ontario, Prairies, and British-Columbia. This correction impacts all the data in these datasets.

The data layer (.shp) presented is the result of an unsupervised classification method for classifying seafloor habitat in the Bay of Fundy (Northwest Atlantic, Canada). This method involves separating environmental variables derived from multibeam bathymetry (slope, bathymetric position index), backscatter, and oceanographic information (wave-shear current velocity) into spatial units (i.e. image objects) and classifying the acoustically and oceanographically separated units into 7 habitat classes (Bedrock and Boulders, Mixed Sediments, Gravelly Sand, Sand, Silty Gravel with Anemones, Silt, and Tidal Scoured Mixed Sediments) using in-situ data (imagery). Benthoscape classes (synonymous to landscape classifications in terrestrial ecology) describe the geomorphology and biology of the seafloor and are derived from elements of the seafloor that were acoustically and oceanographically distinguishable. Reference:Wilson, B.R., Brown, C.J., Sameoto, J.A., Lacharite, M., Redden, A. (2021). Mapping seafloor habitats in the Bay of Fundy to assess macrofaunal assemblages associated with Modiolus modiolus beds. Estuarine, Coastal and Shelf Science, 252. https://doi.org/10.1016/j.ecss.2021.107294Cite this data as: Wilson, B.R., Brown, C.J., Sameoto, J.A., Lacharite, M., Redden, A. Bay of Fundy Benthoscape. Published May 2023. Population Ecology Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/dbabd17a-a2c7-4b3f-9bd8-a77a9c7f9c1c

The purpose of this dataset is to give a an accurate representation of the game hunting boundaries in Manitoba.Please refer to the Manitoba Game Hunting Areas dataset . Game Hunting Areas (GHAs) are defined under the Hunting Areas and Zones Regulation (220/86) of The Wildlife Act (CCSM c. W130). Game Hunting Areas are used to support boundaries for species specific hunting seasons, harvest allocations, bag limits and associated regulations. Refer to the Hunting Areas and Zones Regulation for GHA boundary descriptions.Fields Included (Alias (Field Name): Field description) OBJECTID (OBJECTID): s equential unique whole numbers that are automatically generated GHA (GHA): the n umber assigned to each Game Hunting Area Shape_Length (Shape_Length): the l ength of the feature in internal units Shape_Area (Shape_Area): a rea of the feature in internal units squared