14 Class - Canadian Ecological Domain Classification from Satellite Data. Satellite derived data including 1) topography, 2) landscape productivity based on photosynthetic activity, and 3) land cover were used as inputs to create an environmental regionalization of the over 10 million km2 of Canada’s terrestrial land base. The outcomes of this clustering consists of three main outputs. An initial clustering of 100 classes was generated using a two-stage multivariate classification process. Next, an agglomerative hierarchy using a log-likelihood distance measure was applied to create a 40 and then a 14 class regionalization, aimed to meaningfully group ecologically similar components of Canada's terrestrial landscape. For more information (including a graphical illustration of the cluster hierarchy) and to cite this data please use: Coops, N.C., Wulder, M.A., Iwanicka, D. 2009. An environmental domain classification of Canada using earth observation data for biodiversity assessment. Ecological Informatics, Vol. 4, No. 1, Pp. 8-22, DOI: https://doi.org/10.1016/j.ecoinf.2008.09.005. ( Coops et al. 2009).

100 Class - Canadian Ecological Domain Classification from Satellite Data. Satellite derived data including 1) topography, 2) landscape productivity based on photosynthetic activity, and 3) land cover were used as inputs to create an environmental regionalization of the over 10 million km2 of Canada’s terrestrial land base. The outcomes of this clustering consists of three main outputs. An initial clustering of 100 classes was generated using a two-stage multivariate classification process. Next, an agglomerative hierarchy using a log-likelihood distance measure was applied to create a 40 and then a 14 class regionalization, aimed to meaningfully group ecologically similar components of Canada's terrestrial landscape. For more information (including a graphical illustration of the cluster hierarchy) and to cite this data please use: Coops, N.C., Wulder, M.A., Iwanicka, D. 2009. An environmental domain classification of Canada using earth observation data for biodiversity assessment. Ecological Informatics, Vol. 4, No. 1, Pp. 8-22, DOI: https://doi.org/10.1016/j.ecoinf.2008.09.005. ( Coops et al. 2009).

40 Class - Canadian Ecological Domain Classification from Satellite Data. Satellite derived data including 1) topography, 2) landscape productivity based on photosynthetic activity, and 3) land cover were used as inputs to create an environmental regionalization of the over 10 million km2 of Canada’s terrestrial land base. The outcomes of this clustering consists of three main outputs. An initial clustering of 100 classes was generated using a two-stage multivariate classification process. Next, an agglomerative hierarchy using a log-likelihood distance measure was applied to create a 40 and then a 14 class regionalization, aimed to meaningfully group ecologically similar components of Canada's terrestrial landscape. For more information (including a graphical illustration of the cluster hierarchy) and to cite this data please use: Coops, N.C., Wulder, M.A., Iwanicka, D. 2009. An environmental domain classification of Canada using earth observation data for biodiversity assessment. Ecological Informatics, Vol. 4, No. 1, Pp. 8-22, DOI: https://doi.org/10.1016/j.ecoinf.2008.09.005. ( Coops et al. 2009).

The land classification shown is derived from in-field investigation and is only undertaken for project investigation purposes. These polygons represent the most accurate and up-to-date information regarding agriculture land conditions at those specific locations.Distributed from [[GeoYukon](.underline)](https://yukon.ca/geoyukon) by the [[Government of Yukon](.underline)](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](.underline)](mailto:geomatics.help@yukon.ca)

Wall-to-wall map of water bodies across Canada's forested ecosystems for the year 2022, derived from the "water" class of the annual Virtual Land Cover of Engine (VLCE) product. It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). The VLCE maps are based on Landsat image time-series composites and represent annual land cover classifications from 1984 to 2022 at a spatial resolution of 30 m. The classification process integrates forest change information and ancillary topographic and hydrologic variables, applying a regional modeling framework based on a 150x150 km tiling system ( Hermosilla et al., 2022). Training data are drawn from multiple land cover sources and selected proportionally to land cover distributions using a distance-weighted approach. Classifications are refined over time using a Hidden Markov Model to ensure consistency and reduce classification noise between years.Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C. 2022. Land cover classification in an era of big and open data: Optimizing localized implementation and training data selection to improve mapping outcomes. Remote Sensing of Environment. 268, 112780. https://doi.org/10.1016/j.rse.2021.112780. ( Hermosilla et al., 2022)Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., Hobart, G.W. 2018. Disturbance-Informed Annual Land Cover Classification Maps of Canada's Forested Ecosystems for a 29-Year Landsat Time Series. Canadian Journal of Remote Sensing. 44(1) 67-87. https://doi.org/10.1080/07038992.2018.1437719.( Hermosilla et al., 2018)

This dataset is produced for the Government of Alberta and is available to the general public. Please consult the Distribution Information of this metadata for the appropriate contact to acquire this dataset. Physical Land Classification (PLC) is a mapping system that was designed to describe the landscape in terms of landform, soils, drainage and slope. It is a hierarchical system that captures physiographic information at the following levels: Region - 1:3 000 000 or smaller Section - 1:1 000 000 to 1:3 000 000 District - 1:500 000 to 1:1 000 000 Geomorphic System - 1:100 000 (can range from 1:50 000 to 1:250 000) Geomorphic Unit - 1:10 000 to 1:50 000 There are some variations in this hierarchy for individual study areas. The Land Classification Group (Resource Inventory Section), Alberta Energy and Natural Resources, adopted the initial Physical Land Classification methodology in 1977 to meet the needs of resource planning and management agencies. Many aspects of the methodology were developed from landform mapping schemes used by the System of Soil Classification for Canada (1976). The PLC system is essentially a geomorphic interpretation and classification system based on the principles of the inherent properties of the land and its forms. Physical Land Classification (PLC) maps have been created largely during the 1980s and 1990s as part of a program to acquire background information for Integrated Resource Plans along the eastern slopes and across northern Alberta. The data were generally mapped at the geomorphic unit level using the 1:50 000 scale National Topographic System maps as a base. The PLC hardcopy maps were scanned, georeferenced, rectified, cleaned, vectorized, merged and attributed to form GIS polygons. The polygons are attributed for parent geologic material, landform / surface expression, modifying process, slope, texture, soil taxonomy and soil drainage. This classification system was designed to enhance and replace the Canada Land Inventory (CLI) and Alberta Landform Inventory (ALI) Landform classification systems. There is more attribution associated with PLC mapping than with ALI / CLI Landform mapping. There is some overlap with the ALI / CLI Landform maps but much of the PLC mapping was conducted in areas not covered by ALI / CLI Landform maps. PLC mapping is considered to be more reliable than ALI / CLI Landform mapping as field checking was more extensive.

The Ecological Land Mass (ELM) classification was established through the 2020 National Interest Land Mass (NILM) Update. ELM lands describe ecological corridors that have inherent natural values and that protect Species at Risk (SAR) and their habitats. The classification identifies lands to protect in perpetuity through planning and partnership efforts. ELM was derived from two separate analyses - the Ontario side from the AECOM natural linkages analysis (2012) and the Quebec side from Del Degan, Masse (DDM) ecological corridors analysis (2012). Adjustments were made as appropriate.

This polygon dataset shows First Nation land acquisitions designated as Other Land as outlined by the Treaty Land Entitlement (TLE) Agreements in Manitoba, pursuant to the Crown Lands Act 5(1)(d).The purpose of this dataset is to show geographic boundaries for land acquisitions designated as Other Land, as outlined by the Treaty Land Entitlement (TLE) Agreements in Manitoba, pursuant to the Crown Lands Act 5(1)(d). This is a dynamic dataset - data can change daily.Other Land includes land that has been purchased by the First Nations from private landowners or Surplus Provincial or Surplus Federal land that has been purchased from the Manitoba or Canada governments. The title to the land is privately held by a First Nation corporation until it gets transferred to the Government of Canada, however the mines and minerals and other residual interests may be owned by the Crown (Government of Manitoba) and they are required to be transferred to the Government of Canada (subject to third party interest resolution, if applicable).The sites are generally identified by title with reference to a plan of survey, metes and bounds description. Locations are mapped using existing cadastral or parcel mapping data, or reasonably illustrate the site within the dataset. A record may contain multiple polygons that have been combined to form one record.All boundaries are to be considered approximate and for illustrative purposes only.For more information on Treaty Land Entitlement (TLE) Agreements please visit the Manitoba government website: https://www.gov.mb.ca/inr/treaty-land-entitlement/index.htmlFields included [Alias (Field Name): Field description]OBJECTID (OBJECTID): Sequential unique whole numbers that are automatically generatedSite ID (SITE_ID): Site ID number of the selected siteArea in Square Metres (AREA): Area in square metresArea in Acres (ACREAGE): Area in acresBand Council Resolution Number (BCR_NO): Band Council Resolution numberName of the First Nation Making the Land Selection (BAND_NAME): Name of the First Nation making the land selectionSite Number (SITE_NO): Site number of the selected siteSelection Name (SELECTION): Name of the selected site

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

Health Service Delivery Area (HSDA) boundaries; 2022 boundary configuration. The HSDAs are a mutually exclusive and exhaustive classification of the land area in BC. HSDAs are contiguous (land area is geographically adjacent) and fit within a geographical hierarchy structure, e.g., cannot violate higher-level geography boundaries Health Authorities (HA).