Metallic and Industrial Minerals Agreement feature class contains provincial extent polygon features representing Metallic and Industrial Minerals applications, agreements, leases, and licences, with varying term dates and conditions. These applications and subsequent agreements give the holder the right to explore Metallic and Industrial Minerals.

“Automatically Extracted Buildings” is a raw digital product in vector format created by NRCan. The feature classes of this product delineate polygonal building footprints automatically extracted from airborne Lidar data, high-resolution optical imagery or other sources.The first feature class, Automatically Extracted Buildings by acquisition source, contains building footprints delivered according to the spatial extent of each source dataset used for extraction. When the spatial extents of acquisition sources overlap, footprints for the same building may therefore be duplicated in this class.The second feature class, Optimized Buildings Layer, is an assembled and harmonized layer derived from the buildings by acquisition source. Its objective is to provide a unique representation of each building footprint by removing duplicates and resolving overlaps between sources.

Predicted Soil Great Group class as defined by the The Canadian System of Soil Classification (third edition).

The Yukon government amended the Quartz Mining Act and the Placer Mining Actin December 2013, to establish the authority to designate areas where government notification of Class 1 exploration activities is required. Before these amendments to the mining acts and regulation came into effect, prospectors undertaking Class 1 activities were not required to inform government of their work. Class 1 exploration activities generally have low potential to cause adverse environmental effects. A Notification is required if an exploration program is categorized as class 1 (OIC 2003/59 and OIC 2003/64) and located either on settlement land (category A or B) or within a class 1 notification area (OIC 2013/221). This layer show current class 1 exploration program that are allowed to proceed.Distributed from [GeoYukon](https://yukon.ca/geoyukon) by the [Government of Yukon](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](mailto:geomatics.help@yukon.ca)

The Yukon government amended the Quartz Mining Act and the Placer Mining Actin December 2013, to establish the authority to designate areas where government notification of Class 1 exploration activities is required. Before these amendments to the mining acts and regulation came into effect, prospectors undertaking Class 1 activities were not required to inform government of their work. Class 1 exploration activities generally have low potential to cause adverse environmental effects. A Notification is required if an exploration program is categorized as class 1 (OIC 2003/59 and OIC 2003/64) and located either on settlement land (category A or B) or within a class 1 notification area (OIC 2013/221). This layer show current class 1 exploration program that are allowed to proceed.Distributed from [GeoYukon](https://yukon.ca/geoyukon) by the [Government of Yukon](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](mailto:geomatics.help@yukon.ca)

High-resolution binary wetland map for Canada (2001-2016). Wetland map for the forested ecosystems of Canada focused on current conditions. It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). The binary wetland data included in this product is national in scope (entirety of forested ecosystem) and represents the wall to wall characterization for 2001-2016 (see Wulder et al. 2018). This product was generated using both annual gap free composite reflectance images and annual forest change maps following the Virtual Land Cover Engine (VLCE) process (see Hermosilla et al. 2018), over the 650 million ha forested ecosystems of Canada. Elements of the VLCE classification approach are inclusion of disturbance information in the processes as well as ensuring class transitions over time are logical. Further, a Hidden Markov Model is implemented to assess individual year class likelihoods to reduce variability and possible noise in year-on-year class assignments (for instances when class likelihoods are similar). For this product, to be considered as currently a wetland a pixel must have been classified as wetland at least 80% or 13 of the 16 years between 2001 and 2016, inclusively. For an overview on the data, image processing, and time series change detection methods applied, see Wulder et al. (2018). Wulder, M.A., Z. Li, E. Campbell, J.C. White, G. Hobart, T. Hermosilla, and N.C. Coops (2018). A National Assessment of Wetland Status and Trends for Canada’s Forested Ecosystems Using 33 Years of Earth Observation Satellite Data. Remote Sensing. For a detailed description of the VLCE process and the subsequently generated land cover product, including an accuracy assessment, please see Hermosilla et al. (2018).

The wetland year count data included in this product is national in scope (entire forested ecosystem) and represents a wall to wall wetland characterization for 1984-2016 (Wulder et al. 2018). It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). This product was generated using both annual gap free composite reflectance images and annual forest change maps following the Virtual Land Cover Engine (VLCE) process (see Hermosilla et al. 2018), over the 650 million ha forested ecosystems of Canada. Elements of the VLCE classification approach are inclusion of disturbance information in the processes as well as ensuring class transitions over time are logical. Further, a Hidden Markov Model is implemented to assess individual year class likelihoods to reduce variability and possible noise in year-on-year class assignments (for instances when class likelihoods are similar). The values can range from 0 to 33 denoting the number of years between 1984 and 2016 that a pixel was classified as wetland or wetland-treed in the VLCE data cube.For an overview on the data, image processing, and time series change detection methods applied, as well as information on independent accuracy assessment of the data, see Hermosilla et al. (2016; http://www.tandfonline.com/doi/full/10.1080/17538947.2016.1187673). A detailed description of the VLCE process and the subsequently generated land cover product, including an accuracy assessment, please see Hermosilla et al. (2018). The focused wetland analyses can be found described in Wulder et al (2018).Geographic extent: Canada's forested ecosystems (~ 650 Mha)Time period: 1985–2011

This table contains data on whole and partial condemnation and slaughtering from 2015 to 2022.This table contains data on whole and partial condemnation and slaughtering from 2015 to 2022. The data is also classified by its Slaughter Class: Cattle, Swine, Chiken,  Spent layer hens, Ducks, Geese, Rabbits, Spent Breeder hens, 5 kg and under, Bison, Elk, Goats, Horses, Lambs, Llama/Alpaca, Mature turkey, over 11 kg, over 5 but no more than 7 kg, over 7 but no more than 9 kg, over 9 but no more than 11 kg, Sheep, and Wild boars.Field Names (Field Alias): Field description.SlaughterFigureID (SlaughterFigureID): unique indexed number assigned to each record in the database. BodyPart (BodyPart): code for the different body parts affected in partial condemnations. CondemnationReasonCode (CondemnationReasonCode): code for all the different reasons for condemnation. CondemnationType (CondemnationType): This identifies whether the condemnations are either Whole or Partial. SlaughterYear (SlaughterYear): Year when the slaughter occurred. NumberSlaughtered (NumberSlaughtered): Total number of animals slaughtered during the indicated period of time. NumberCondemned (NumberCondemned): Total number of animals condemned (whole) or total  number of parts of animals condemned (partial) during the indicated period of time. SlaughterClass (SlaughterClass): Species or class of the animal or part of the animal condemned. Quarter (Quarter): Number of the quarter.                   - January to March – 1                     - April to June – 2                     - July to September – 3                     - October to December - 4 QuarterYear (Quarter/Year): Corresponding quarter and year.

The Plains, Northern, Foothills Boundary feature class contains polygon features representing Department of Energy Regional Boundaries for the Province of Alberta.

Coal Agreement feature class contains provincial extent polygon features representing Coal applications, agreements, leases, and licences, with varying term dates and conditions. These applications and subsequent agreements give the holder the right to explore Coal.