RESULTS opening's forest cover polygons with inventory component provided. Current forest cover submissions into RESULTS must contain attribute and map information. However, there are historical forest cover polygon information where maps are not available. Forest Cover is provided at three critical milestones of at harvesting, at achieved regeneration and at free growing. This is part of the Silviculture and Land status Tracking dataset, which includes tracking achievement of silviculture obligations on Crown Land

RESULTS opening's forest cover poylgons with silviculture component provided. Current forest cover subimssion into RESULTS must contain attribute and map information. However, there are historical forest cover polygon infomration where maps are not available. Forest Cover is provided at three critical milestones of at harvesting, at regeneration, and at free growing. This is a part o fthe Silviculture and Land Status Tracking dataset, which includes tracking achievement of silviculture obligations on Crown Land

Planting activities reported on openings into RESULTS. More than one planting activitiy may occur within an opening. Planting activiites may also overlap. Planting attribute reporting is mandatory requirement while planting maps are optional. Planting reports includes species and seedlot information. This is a part of Silviculture and Land Status dataset, which includes tracking achievement of silviculture obligations on Crown land

__The link: *Access the data directory* is available in the section*Dataset Description Sheets; Additional Information*__.**The results of compilations by forel** are one of the deliverables of the ecoforest inventory in southern Quebec. These results are used to produce forest compilations by stand associated with the original ecoforest map. The forel corresponds to a forest pixel with a resolution of 20 meters by 20 meters. These results are presented in the form of matrix mapping (image in raster format) to assess the variability of the various dendrometric characteristics within the same forest stand.Here is the list of variables presented in this map: gross market volume per hectare, basal area per hectare and number of stems per hectare.These results are intended to provide small-scale information that can, among other things, support the planning of forest operations. They cover ecoforest stands 7 m or more in height. For commercial stems, a separate matrix file is produced for each of the three variables and each of the species, attribution groups, species types and for the total all species. For saplings (stems of 9 cm or less in diameter), only results for basal area and the number of stems per hectare for species types and for the total of all species are produced. The information contained in this map is an image of the forest in the year the aerial photograph was taken.The results of this forest compilation method will eventually cover most of the territory south of the 52nd parallel. When achieved, the results are disseminated by planning unit (AU) for the territories produced under the fourth inventory and by ecological planning unit (UPE) for the territories produced as part of the fifth inventory.__ ⚠️ Notes: __Consult the [original ecoforest map and current inventory results]] (https://www.donneesquebec.ca/recherche/dataset/resultats-d-inventaire-et-carte-ecoforestiere) for the results of forest compilations by population, also available on Data Quebec.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Dominant Species Map 2015The data represent dominant tree species for British Columbia forests in 2015, are based upon Landsat data and modeling, with results mapped at 30 m spatial resolution. It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). The map was generated with the Random Forests classifier that used predictor variables derived from Landsat time series including surface reflectance, land cover, forest disturbance, and forest structure, and ancillary variables describing the topography and position. Training and validation samples were derived from the Vegetation Resources Inventory (VRI), from a pool of polygons with homogeneous internal conditions and with low discrepancies with the remotely sensed predictions. Local models were applied over 100x100 km tiles that considered training samples from the 5x5 neighbouring tiles to avoid edge effects. An overall accuracy of 72% was found for the species which occupy 80% of the forested areas. Satellite data and modeling have demonstrated the capacity for up-to-date, wall-to-wall, forest attribute maps at sub-stand level for British Columbia, Canada.BC Species Likelihood 2015The tree species class membership likelihood distribution data included in this product focused on the province of British Columbia, based upon Landsat data and modeling, with results mapped at 30 m spatial resolution. The data represent tree species class membership likelihood in 2015. The map was generated with the Random Forests classifier that used predictor variables derived from Landsat time series including surface reflectance, land cover, forest disturbance, and forest structure, and ancillary variables describing the topography and position. Training and validation samples were derived from the Vegetation Resources Inventory (VRI) selecting from a stratified pool of polygons with homogeneous internal conditions and with low discrepancies when related to remotely sensed information. Local models were applied over 100x100 km tiles that, to avoid edge effects, considered training samples from the 5x5 neighbouring tiles. An overall accuracy of 72% was found for the species which occupy 80% of the forested areas. As an element of the mapping process, we also obtain the votes received for each class by the Random Forest models. The votes can be understood as analogous to class membership likelihoods, providing enriched information on land cover class uncertainty for use in modeling. Tree species class membership likelihoods lower than 5% have been masked and converted to zero.When using this data, please cite as: Shang, C., Coops, N.C., Wulder, M.A., White, J.C., Hermosilla, T., 2020. Update and spatial extension of strategic forest inventories using time series remote sensing and modeling. International Journal of Applied Earth Observation and Geoinformation 84, 101956. DOI: 10.1016/j.jag.2019.101956 ( Shang et al. 2020).

Forest 95th Percentile Elevation(Ht) 201595th percentile of first returns height (m). Products relating the structure of Canada's forested ecosystems have been generated and made openly accessible. It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). The shared products are based upon peer-reviewed science and relate aspects of forest structure including: (i) metrics calculated directly from the lidar point cloud with heights normalized to heights above the ground surface (e.g., canopy cover, height), and (ii) modelled inventory attributes, derived using an area-based approach generated by using co-located ground plot and ALS data (e.g., volume, biomass). Forest structure estimates were generated by combining information from lidar plots (Wulder et al. 2012) with Landsat pixel-based composites (White et al. 2014; Hermosilla et al. 2016) using a nearest neighbour imputation approach with a Random Forests-based distance metric. These products were generated for strategic-level forest monitoring information needs and are not intended to support operational-level forest management. All products have a spatial resolution of 30 m. For a detailed description of the data, methods applied, and accuracy assessment results see Matasci et al. (2018). When using this data, please cite as follows: Matasci, G., Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., Hobart, G.W., Bolton, D.K., Tompalski, P., Bater, C.W., 2018b. 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. Matasci et al. 2018)Geographic extent: Canada's forested ecosystems (~ 650 Mha)Time period: 1985–2011

Forest Elevation(Ht) Mean 2015Mean height of lidar first returns (m). Represents the mean canopy height. It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). Products relating the structure of Canada's forested ecosystems have been generated and made openly accessible. The shared products are based upon peer-reviewed science and relate aspects of forest structure including: (i) metrics calculated directly from the lidar point cloud with heights normalized to heights above the ground surface (e.g., canopy cover, height), and (ii) modelled inventory attributes, derived using an area-based approach generated by using co-located ground plot and ALS data (e.g., volume, biomass). Forest structure estimates were generated by combining information from lidar plots (Wulder et al. 2012) with Landsat pixel-based composites (White et al. 2014; Hermosilla et al. 2016) using a nearest neighbour imputation approach with a Random Forests-based distance metric. These products were generated for strategic-level forest monitoring information needs and are not intended to support operational-level forest management. All products have a spatial resolution of 30 m. For a detailed description of the data, methods applied, and accuracy assessment results see Matasci et al. (2018). When using this data, please cite as follows: Matasci, G., Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., Hobart, G.W., Bolton, D.K., Tompalski, P., Bater, C.W., 2018b. 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. Matasci et al. 2018) Wulder et al. 2018)Geographic extent: Canada's forested ecosystems (~ 650 Mha)Time period: 1985–2011

Forest Percentage Above 2m 2015Percentage of first returns above 2 m (%). Represents canopy cover. It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). Products relating the structure of Canada's forested ecosystems have been generated and made openly accessible. The shared products are based upon peer-reviewed science and relate aspects of forest structure including: (i) metrics calculated directly from the lidar point cloud with heights normalized to heights above the ground surface (e.g., canopy cover, height), and (ii) modelled inventory attributes, derived using an area-based approach generated by using co-located ground plot and ALS data (e.g., volume, biomass). Forest structure estimates were generated by combining information from lidar plots (Wulder et al. 2012) with Landsat pixel-based composites (White et al. 2014; Hermosilla et al. 2016) using a nearest neighbour imputation approach with a Random Forests-based distance metric. These products were generated for strategic-level forest monitoring information needs and are not intended to support operational-level forest management. All products have a spatial resolution of 30 m. For a detailed description of the data, methods applied, and accuracy assessment results see Matasci et al. (2018). When using this data, please cite as follows: Matasci, G., Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., Hobart, G.W., Bolton, D.K., Tompalski, P., Bater, C.W., 2018b. 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. Matasci et al. 2018)Geographic extent: Canada's forested ecosystems (~ 650 Mha)Time period: 1985–2011

Forest Elevation(Ht) Stddev 2015Standard deviation of height of lidar first returns (m). Represents the variability in canopy heights. It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). Products relating the structure of Canada's forested ecosystems have been generated and made openly accessible. The shared products are based upon peer-reviewed science and relate aspects of forest structure including: (i) metrics calculated directly from the lidar point cloud with heights normalized to heights above the ground surface (e.g., canopy cover, height), and (ii) modelled inventory attributes, derived using an area-based approach generated by using co-located ground plot and ALS data (e.g., volume, biomass). Forest structure estimates were generated by combining information from lidar plots (Wulder et al. 2012) with Landsat pixel-based composites (White et al. 2014; Hermosilla et al. 2016) using a nearest neighbour imputation approach with a Random Forests-based distance metric. These products were generated for strategic-level forest monitoring information needs and are not intended to support operational-level forest management. All products have a spatial resolution of 30 m. For a detailed description of the data, methods applied, and accuracy assessment results see Matasci et al. (2018). When using this data, please cite as follows: Matasci, G., Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., Hobart, G.W., Bolton, D.K., Tompalski, P., Bater, C.W., 2018b. 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. Matasci et al. 2018)Geographic extent: Canada's forested ecosystems (~ 650 Mha)Time period: 1985–2011

Forest Percent Above Mean 2015Percentage of first returns above the mean height (%). It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). Represents the canopy cover above mean canopy height. Products relating the structure of Canada's forested ecosystems have been generated and made openly accessible. The shared products are based upon peer-reviewed science and relate aspects of forest structure including: (i) metrics calculated directly from the lidar point cloud with heights normalized to heights above the ground surface (e.g., canopy cover, height), and (ii) modelled inventory attributes, derived using an area-based approach generated by using co-located ground plot and ALS data (e.g., volume, biomass). Forest structure estimates were generated by combining information from lidar plots (Wulder et al. 2012) with Landsat pixel-based composites (White et al. 2014; Hermosilla et al. 2016) using a nearest neighbour imputation approach with a Random Forests-based distance metric. These products were generated for strategic-level forest monitoring information needs and are not intended to support operational-level forest management. All products have a spatial resolution of 30 m. For a detailed description of the data, methods applied, and accuracy assessment results see Matasci et al. (2018). When using this data, please cite as follows: Matasci, G., Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., Hobart, G.W., Bolton, D.K., Tompalski, P., Bater, C.W., 2018b. 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. Matasci et al. 2018)Geographic extent: Canada's forested ecosystems (~ 650 Mha)Time period: 1985–2011