The “Terrestrial Ecozones of Canada” dataset provides representations of ecozones. An ecozone is the top level of the four levels of ecosystems that the National Ecological Framework for Canada defines. The framework divides Canada into 15 terrestrial ecozones that define its ecological mosaic on a sub-continental scale. Ecozones represent an area of the earth’s surface as large and very generalized ecological units. These units are characterized by interactive and adjusting abiotic and biotic factors.

Sensitive Ecosystems Inventory (SEI) Detailed Polygons (STE_SEI_ATTRIBUTE_POLYS_SVW) contains SEI inventory polygons with key and amalgamated (concatenated) attributes derived from the Resource Inventory Standards Committee (RISC) standard attributes. This layer is derived from the [STE_TEI_ATTRIBUTE_POLYS_SP](https://catalogue.data.gov.bc.ca/dataset/f2cd2cc3-5f58-481c-bf3c-64934acb6fad) layer by filtering on the PROJECT_TYPE attribute. Project types include: SEI, TEMSEI, TEMSET, SEIWHR and NEMSEI. SEI identifies and maps rare and fragile terrestrial ecosystems. Ecosystems mapped may include (but are not limited to) older forests, woodlands, coastal bluffs, herbaceous and sparsely vegetated ecosystems, grasslands, riparian ecosystems and wetlands. SEI methods include manual air photo interpretation or theming of other Ecosystem Mapping, each supported by selective field checking. SEI Detailed Polygons should be used in conjunction with [SEI Project Boundaries](https://catalogue.data.gov.bc.ca/dataset/5a5680fa-29e0-4ad2-b2ce-ff0dabc1f666) which contain boundaries (study areas) and attributes describing each project (project level metadata), plus links to the locations of other data associated with the project (e.g., reports, polygon datasets, plotfiles, legends). SEI inventory polygons with full RISC attributes can be accessed through the [Terrestrial Ecosystem Information (TEI) Data Distribution Packages](https://catalogue.data.gov.bc.ca/dataset/8fd15e4e-e7b1-4566-81d1-1ff8947bfd46). **Current version**: v12 (2026-06-22)

Sensitive Ecosystems Inventory (SEI) Project Boundaries (STE_SEI_PROJECT_BOUNDARIES_SVW) contain boundaries (study areas) and attributes describing each SEI project (project level metadata), and includes links to the locations of other data associated with the project (e.g. reports, polygon datasets, plot files). This layer is derived from the [STE_TEI_PROJECT_BOUNDARIES_SP](https://catalogue.data.gov.bc.ca/dataset/1313fac7-2ea1-4c6b-995b-bd421b7ec3c6) layer by filtering on the PROJECT_TYPE attribute. Project types include: SEI, TEMSEI, TEMSET, SEIWHR and NEMSEI. SEI project boundaries should be used in conjunction with SEI detailed inventory polygons which identify and map rare and fragile terrestrial ecosystems in a given area for the purpose of encouraging land-use decisions that will ensure the continued integrity of these ecosystems. SEI inventory polygons with full Resources Information Standards Committee (RISC) attributes can be accessed through the [Terrestrial Ecosystem Information (TEI) Data Distribution Packages](https://catalogue.data.gov.bc.ca/dataset/8fd15e4e-e7b1-4566-81d1-1ff8947bfd46). SEI inventory polygons with simplified and amalgamated (concatenated) RISC attributes can be accessed through the [Sensitive Ecosystems Inventory (SEI) Detailed Polygons with Short Attribute Table Spatial View](https://catalogue.data.gov.bc.ca/dataset/b00fd09f-ebe1-4b52-9717-6ef9c243d52e). **Current version**: v12 (2026-06-22)

STE_TEI_ATTRIBUTE_POLYS_SP contains Terrestrial Ecosystem Information (TEI) polygons with key and amalgamated (concatenated) attributes derived from the RISC (Resource Inventory Standards Committee) standard attributes. These describe the physical and biological characteristics of ecosystems at a landscape level. TEI currently includes Terrestrial Ecosystem Mapping (TEM), Predictive Ecosystem Mapping (PEM), Sensitive Ecosystems Inventory (SEI), Terrain Mapping (TER), Wetland Mapping (WET) and Soil Mapping (SOIL). Mapping methods include manual air photo interpretation and modeling supported by limited field checking. **Current version**: v12 (2026-06-22)

Terrestrial Ecosystem Mapping (TEM) Detailed Polygons (STE_TEM_ATTRIBUTE_POLYS_SVW) contains TEM inventory polygons with key and amalgamated (concatenated) attributes derived from the Resource Inventory Standards Committee (RISC) standard attributes. This layer is derived from the [STE_TEI_ATTRIBUTE_POLYS_SP](https://catalogue.data.gov.bc.ca/dataset/f2cd2cc3-5f58-481c-bf3c-64934acb6fad) layer by filtering on the PROJECT_TYPE attribute. Project types include: TEM, NEM, TEMNSS, NEMNSS, TEMPRE, NEMPRE, TEMSEI, TEMSET, TEMTSM, TEMWHR, TEMSDM, TEMPRW, NEMPRW, NEMSEI and NEMWHR. TEM divides the landscape into units according to a variety of ecological features including climate, physiography, surficial material, bedrock geology, soils and vegetation. TEM methods include manual air photo interpretation supported by selective field checking. TEM Detailed Polygons should be used in conjunction with [TEM Project Boundaries](https://catalogue.data.gov.bc.ca/dataset/b6b86630-26c0-4b6d-a4b0-6633d7f00c7a) which contain boundaries (study areas) and attributes describing each project (project level metadata), plus links to the locations of other data associated with the project (e.g., reports, polygon datasets, plotfiles, legends). TEM inventory polygons with full RISC attributes can be accessed through the [Terrestrial Ecosystem Information (TEI) Data Distribution Packages](https://catalogue.data.gov.bc.ca/dataset/8fd15e4e-e7b1-4566-81d1-1ff8947bfd46). **Current version**: v12 (2026-06-22)

High-resolution map of leading tree species distribution for Canada’s forested ecosystems (2019). Leading tree species map produced from a 2019 Landsat image composite, geographic and climate data, elevation derivatives, and remote sensing derived phenology following the framework described in Hermosilla et al. (2022). Regional classification models were generated based on Canada’s National Forest Inventory using a 150x150 km tiling system. The leading tree species are defined by representing the most voted tree species from the Random Forests classification models (i.e. the class with the highest class membership probability).The data represents leading tree species of Canada's forested ecosystems in 2019. An image compositing window of August 1 ± 30 days was used to generate the best-available-pixel (BAP) image composites utilized as source data for the classification.The science and methods developed to generate the information outcomes shown here, that track and characterize the history of Canada’s forests, were led by Canadian Forest Service of Natural Resources Canada, developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS), partnered with the University of British Columbia, augmented by processing capacity from Digital Research Alliance of Canada.For an overview on the data, image processing, and methods applied, as well as information on independent accuracy assessment of the data, see Hermosilla et al. (2022) https://doi.org/10.1016/j.rse.2022.113276When using this data, please cite as: Hermosilla, T., Bastyr, A., Coops, N.C., White, J.C., Wulder, M.A., 2022. Mapping the presence and distribution of tree species in Canada’s forested ecosystems. Remote Sensing of Environment 282, 113276.

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. It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). 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. It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). 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.It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). 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)

A compendium of reports that provide information about aquatic and terrestrial animals and plants, soils, surface water, groundwater and their accompanying data files and maps