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)

Forest Elevation(Ht) Mean 2015 Mean height of lidar first returns (m). Represents the 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) Wulder et al. 2018) Geographic extent: Canada's forested ecosystems (~ 650 Mha) Time period: 1985–2011

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).

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)

The British Columbia Detailed Soil Survey dataset series at a scale of 1:100 000 consists of geo-referenced soil polygons with linkages to attribute data found in the associated Component File (CMP), Soil Names File (SNF) and Soil Layer File (SLF). Together, these datasets describe the spatial distribution of soils and associated landscapes for nearly all agricultural areas for the Lower Fraser Valley, British Columbia.

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).

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). 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

Forest Lorey's Height 2015 Lorey's mean height. Average height of trees weighted by their basal area (m). 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

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)