Summer/Fall and Winter/Forest-Dwelling 2017 habitat model for caribou in the Itcha Ilgachuz area. [Season] field should be used to split the data out into separate summer/fall and winter/forest-dwelling habitat models. Model development is detailed in _Apps, C., and N. Dodd. 2016.. Caribou habitat modeling and evaluation of forest disturbance influences across landscape scales in west-central British Columbia – March, 2016. Prepared for Ministry of Forests, Lands and Natural Resource Operations, Williams Lake, British Columbia_. See also: https://catalogue.data.gov.bc.ca/dataset/7ea6556b-c113-4194-92f2-7ddb55a340b6 __Note: The 2001 habitat model covers a similar area, but is not replaced by the 2017 habitat model.__

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)**

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.

Canadas Managed Forests 2020 Vector Tile Layer

This polygon layer displays sub-basin-level average precipitation derived from the ECMWF (European Centre for Medium-Range Weather Forecasts) model. This layer helps hydrologists, forecasters, and planners see how much rainfall/snowfall is predicted or has occurred in each sub-basin, supporting medium-range water resource and flood management. We are intersested in the forecast period of 7 days.This layer aggregates ECMWF forecast precipitation over polygonal sub-basins. Each feature includes attributes for average accumulated precipitation, forecast run/valid times, and sub-basin identifiers. ECMWF is a leading global model offering medium-range (up to 10 days) forecasts at a high skill level. By focusing on sub-basins, this layer aids in local-scale decision-making—enabling more precise flood risk assessments, reservoir inflow estimates, and water resource planning across the region of interest.

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 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 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 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)

Manitoba's Provincial Forest Boundaries (version 6): There are currently 15 provincial forests totalling almost 22,000 km2. Attributes include the name of the provincial forest, the year it was established and its area. Detailed descriptions of Manitoba’s provincial forests are provided in the Provincial Forest Act Regulations.Manitoba's Provincial Forest B oundaries ( V ersion 6 ). Manitoba's provincial forests reserve certain areas in the province for perpetual growth of timber, preserve the forest cover thereon and provide for a reasonable use of all the resources that the forest lands contain. All Crown lands within a provincial forest are withdrawn from disposition, sale, settlement or occupancy, except under authority of the Forest Act . Before the Province of Manitoba was established, European settlers were promised 160 acres of free land if they lived on it and cleared it for agriculture. As a result, farms began replacing our southern forests. The federal government decided they must retain some forests for building material. In 1885 , they established Turtle Mountain, Spruce Woods and Riding Mountain (now a national park) as timber reserves. Duck Mountain and Porcupine Mountain followed in 1906. What started out as federal timber reserves 100 years ago have become our provincial forests of today. Manitoba has 15 provincial forests , totalling almost 22,000 sq. km . These forests are among the highest quality timber stands in the province. Today, our provincial forests are much more than reserves for timber. They are also places for wildlife, recreation and research. Control of Manitoba's forests was transferred from the federal to the provincial governments in 1930. Provincial forests are Crown lands owned by the people of Manitoba. The feature class name (BDY_MB_PROV_FOREST_PY) components include: 1. ISO 19115 Topic Category Name (BDY for boundary); 2. Location code (MB for Manitoba); 3. Intuitive or descriptive name (PROV_FOREST); 4. Data/geometry type (PY for polygon); 5. Version number (v 6 ).Manitoba's provincial forests include Agassiz Provincial Forest, Belair Provincial Forest, Brightstone Sand Hills Provincial Forest, Cat Hills Provincial Forest, Cormorant Provincial Forest, Duck Mountain, Moose Creek Provincial Forest, Northwest Angle Provincial Forest, Porcupine Provincial Forest, Sandilands Provincial Forest, Spruce Woods Provincial Forest, Swan-Pelican Provincial Forest, Turtle Mountain Provincial Forest, Wampum Provincial Forest, and Whiteshell Provincial Forest.Detailed descriptions of Manitoba’s Provincial Forests are provided in the Provincial Forest Act Regulations. The dataset includes the following fields : Name / Nom Alias Description PROV_FOREST_ID Provincial Forest ID / No de la forêt provinciale Provincial Forest identifier Identificateur de la forêt provinciale PROV_FOREST_NAME Provincial Forest Name Provincial Forest name -- NOM_FORET_PROV Nom de la forêt provinciale -- Nom de la forêt provinciale ESTABLISHED Year Established / Année d’établissement The year that the provincial forest was established L’année où la forêt provinciale a été établie AREA_HA Area / Surface (Hectares) Area in hectares La surface en hectares