The spatial representation for the areas that have been eliminated from a timber licence

Spatial representation of a reserve of retention area associated with a silvicultural system. Reserves are forest patches or individual trees retained during harvesting, or other forestry operations to provide habitat, scenic, biodiversity, and other values. The reserve types included are Riparian, Wildlife Tree Patches, and Other. This is part of the Silviculture and Land status Tracking dataset, which includes all business processes required to receive and process records from forest licensees to record report on Silviculture and Land Status Management activities.

A spatial representation of the Map Blocks for Timber Licences

This dataset provides wall-to-wall maps of forest structure across Canada's 650 million hectare forested ecosystems for the year 2022, generated at a spatial resolution of 30 m. Structure estimates include key attributes such as canopy height, canopy cover, and aboveground biomass, derived using a combination of airborne lidar and Landsat-based spectral composites. Structure models were trained using the - lidar-plot framework - (Wulder et al. 2012), which integrates co-located airborne lidar data and ground plot measurements with Landsat time-series composites (Hermosilla et al. 2016). A Nearest Neighbour imputation approach was applied to estimate structural attributes across the full extent of Canada's forested area. These nationally consistent products are intended to support strategic-level forest monitoring and assessment and are not designed for operational forest management.For further details on the methods, accuracy assessment, and source data, see Matasci et al. (2018).Matasci, G., Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., Hobart, G.W., Bolton, D.K., Tompalski, P., Bater, C.W., 2018. 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. https://doi.org/10.1016/j.rse.2018.07.024 (Matasci et al. 2018)

This is a spatial layer showing Ministry of Forests Real Property Projects. These are spatial representations of land that is under intensive management/administration by the Ministry of Forests for various purposes consistent with the Forest Act.

Land Features entities are: Island, Shoreline, Wooded Area, Saturated soil, Landform Feature (esker, sand\...), and Cut Line. CanVec is a digital cartographic reference product of Natural Resources Canada (NRCan). It originates from the best available data sources covering Canadian territory, offers quality topographical information in vector format, and complies with international geomatics standards. CanVec is a multi-source product coming mainly from the National Topographic Data Base (NTDB), the Mapping the North process conducted by the Canada Center for Mapping and Earth Observation (CCMEO), the Atlas of Canada data, the GeoBase initiative, and the data update using satellite imagery coverage (e.g. Landsat 7, Spot, Radarsat, etc.).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)

Geospatial forest inventory dataset updated for depletions, such as harvesting, and projected annually for growth. Sample attributes in this dataset include: age, species, volume, height. The Vegetation Resources Inventory (VRI) spatial datasets describe both where a vegetation resource (ie timber volume, tree species) is located and how much of a given resource is within an inventory unit. Suggested citation: Forest Analysis and Inventory Branch (2024). VRI - 2024 - Forest Vegetation Composite Rank 1 Layer (R1). British Columbia Data Catalogue. https://catalogue.data.gov.bc.ca/dataset/2ebb35d8-c82f-4a17-9c96-612ac3532d55

This feature class represents Manitoba's Forest Management Licence (FML) boundaries.The Forest Act provides for the establishment of Forest Management Licences to provide a continuous supply of timber to the forest industry. A Forest Management Licence, granted for a period of not more than twenty years, may be renewed for further periods. The Forest Management Licence describes the land upon which trees may be cut, the volume of wood that may be harvested, and other terms and conditions. There are currently two Forest Management Licences in Manitoba, FML-2 and FML-3 . Timber management and forest renewal are the responsibilities of Manitoba Sustainable Government on Crown Forest Land outside of Forest Management Licence areas, and within Forest Management Licence areas where the wood is used by a facility other than that operated by the Forest Management Licensee. Version 3 of Manitoba's Forest Management Licence (FML) boundaries includes FML-2 and FML-3. Previous boundaries associated with FML-1 and IWSA's have been removed. To update and improve the positional accuracy of Manitoba's Forest Management Licence (FML) boundaries, written descriptions of FML areas were referenced along with linework from Forest Land Inventories (FLI), Forest Resource Inventories (FRI) and Manitoba's township fabric to improve Provincial FML boundaries. Boundary linework the following related geospatial datasets were topologically checked for coincident linework: Manitoba Provincial Boundary; Manitoba Forest Management Units ; Manitoba Forest Management Licence Agreement Areas; Manitoba Forest Sections; Manitoba Provincial Forests . Fields Included: FML_NAME : Forest Management Licence area name.

This feature class represents Manitoba's Forest Management Unit (FMU) boundaries.Forest Management Units (FMU's) define a forested area with common forest conditions that are managed in a similar manner. Forest Sections are comprised of FMU's. Forest inventories within Forest Management Units are analysed to determine allowable harvest limits of softwood and hardwood tree species within each Forest Management Unit. Version 3: The southern portion of FMU 67 within the Highrock Forest Section has been adjusted to align with base features captured in 2009. Additionally, an 11 hectare portion of the Saskatchewan River Forest Section (FMU 59) has been added to the Highrock Forest Section. Version 4: The northern portion of FMU 68 along the Rail Haul within the Highrock Forest Section has been adjust so that the boundary falls within water only. Additionally, version 4 splits the 'White Zone' forest section (FMU 76) by ecozones, creating FMU 76 (Taiga Shield), FMU 77 (Southern Arctic), FMU 78 (Hudson Plain) and FMU 79 (Boreal Shield). Version 4 is dated February 8, 2013. Fields Included: OBJECTID: Sequential unique whole numbers that are automatically generated . MANAGEMENT_UNIT_NUMBER : Management Unit (MU) number . S ECTION : Forest section number . SECTION_NAME : Forest section name .

High-resolution annual forest land cover maps for Canada's forested ecosystems (1984-2022). The annual time series of forest land cover maps are national in scope (entire 650 million hectare forested ecosystem) and represent a wall-to-wall land cover characterization yearly from 1984 to 2022. These time-series land cover maps were produced from annual time-series of Landsat image composites, forest change information, and ancillary topographic and hydrologic data following the framework described in Hermosilla et al. (2022), which builds upon the approach introduced in Hermosilla et al. (2018). The methodological innovations included (i) a refined training pool derived from existing land cover products using airborne and spaceborne measures of forest structure; (ii) selection of training samples proportionally to the land cover distribution using a distance-weighted approach; and (iii) generation of regional classification models using a 150x150 km tiling system. Maps are post-processed using disturbance information to ensure logical class transitions over time using a Hidden Markov Model. Hidden Markov Models assess individual year class likelihoods to reduce variability and possible noise in year-on-year class assignments (for instances when class likelihoods are similar).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. Vol. 268, No. 112780. https://doi.org/10.1016/j.rse.2021.112780. ( Hermosilla et al. 2022)Hermosilla, T., M.A. Wulder, J.C. White, N.C. Coops, G. W. Hobart, (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.DOI: 10.1080/07038992.2018.1437719 ( Hermosilla et al. 2018).