Aurora Geosciences Ltd was contracted to perform a review of publicly available digital magnetic geophysical data submitted with assessment reports to develop standardized products and compilations. Data submitted prior to March 2015 were considered.Individual assessment report data were levelled and integrated with 1:250 000 compilations.Four gridded PDFs have been produced (residual total magnetic field, reduced to pole, vertical derivative and tilt derivative). Original 250k geophysical data can be found in YGS Open File 2017-46.

Aurora Geosciences Ltd was contracted to perform a review of publicly available digital magnetic geophysical data submitted with assessment reports to develop standardized products and compilations. Data submitted prior to March 2015 were considered.Individual assessment report data were levelled and integrated with 1:250 000 compilations.Four gridded PDFs have been produced (residual total magnetic field, reduced to pole, vertical derivative and tilt derivative). Original 250k geophysical data can be found in YGS Open File 2017-13.

Aurora Geosciences Ltd was contracted to perform a review of publicly available digital magnetic geophysical data submitted with assessment reports to develop standardized products and compilations. Data submitted prior to March 2015 were considered.Individual assessment report data were levelled and integrated with 1:250 000 compilations.Four gridded PDFs have been produced (residual total magnetic field, reduced to pole, vertical derivative and tilt derivative). Original 250k geophysical data can be found in YGS Open File 2017-25.

GEO - Geological and geophysical (geoscientificInformation)The earth sciences. For example, resources describing geophysical features and processes; minerals; the composition, structure, and origin of the earths rocks; earthquakes; volcanic activity; landslides; gravity information; soils; permafrost; hydrogeology; and erosion

The dataset identifies the location and types of Areas of Natural and Scientific Interest (ANSIs) that are commonly used in maps for resource management purposes. Official GEO title: ANSI

This is the spatial view used by Mineral Titles Online (MTO) on the mineral, placer and coal viewers. The spatial view combines the polygon information with attribute information for each title. Contains sub-surface title data in British Columbia for: - mineral claims, mining leases, mineral claim applications - placer claims, placer leases, placer claim applications - coal license applications, coal licenses, coal leases

Geochronology is a discipline of geoscience which measures the age of earth materials and provides the temporal framework in which other geoscience data can be interpreted in the context of Earth history. This knowledge helps to answer questions such as when did a volcano last erupt, what is the rate of crustal uplift in a specific area, are rocks at one gold prospect the same age as those at another.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)

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)