The dataset includes subsurface stratigraphic picks for the top of the Foremost Formation (Belly River Group) in the Alberta Plains (Townships 1 to 52, Ranges 1W4 to 5W5) made from downhole wireline geophysical well logs. The top of the Foremost was picked at the base of a continuous sandstone or siltstone bed (low-gamma-ray) of variable thickness overlying the Taber coal zone. Well data were screened to detect errors resulting from deviated wells, as well as incorrect ground and kelly bushing elevation data. We used statistical methods to identify local and regional statistical outliers, which were examined individually.

BiologicEcologic ISO Feature Dataset symbolization and publication. September 5, 2017.

Toponymic Features entity is Named Feature (geographical name or toponym). CanVec is a digital cartographic reference product of Natural Resources Canada (NRCan). It originates from the best available data sources covering Canadian territory, offers quality topographical information in vector format, and complies with international geomatics standards. CanVec is a multi-source product coming mainly from the National Topographic Data Base (NTDB), the Mapping the North process conducted by the Canada Center for Mapping and Earth Observation (CCMEO), the Atlas of Canada data, the GeoBase initiative, and the data update using satellite imagery coverage (e.g. Landsat 7, Spot, Radarsat, etc.).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@gov.yk. ca](mailto:geomatics.help@yukon.ca)

Predicted Soil Great Group class as defined by the The Canadian System of Soil Classification (third edition).

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

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)**

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)**

The toponymic features of the CanVec series include proper nouns designating places and representations of the territory. This data come from provincial, territorial and Canadian toponymic databases. They are used in the CanVec Series for cartographic reference purposes and vary according to the scale of display. The toponymic features of the CanVec series can differ from the Canada's official geographical names.The CanVec multiscale series is available as prepackaged downloadable files and by user-defined extent via a Geospatial data extraction tool. Related Products (Open Maps Links):[Topographic Data of Canada - CanVec Series](https://open.canada.ca/data/en/dataset/8ba2aa2a-7bb9-4448-b4d7-f164409fe056)Users can obtain information about Canada's official toponyms at: **[Geographical names in Canada](https://www.nrcan.gc.ca/maps-tools-publications/maps/geographical-names-canada/10786)**

The selection of an Area of Interest (AOI) marks the beginning of the Oceans Act Marine Protected Area (MPA) establishment process led by Fisheries and Oceans Canada. The process includes completing detailed ecological and socioeconomic assessments, setting conservation objectives, determining boundaries and management measures, and eventually developing the regulations under section 35 of the Oceans Act. Collaboration, consultation, and engagement occurs with stakeholders and partners throughout each step of this process.

The Eastern Arctic dataset comes from the Petroleum and Environmental Management Tool (PEMT). The online tool was decommissioned in 2019 and the data was transferred to Open Data in order to preserve it.The PEMT was originally developed in 2009 to help guide development in the Canadian Arctic by Indian and Northern Affairs Canada (INAC). The online tool mapped the sensitivities of a variety of Arctic features, ranging from whales to traditional harvesting, across the Arctic. The tool was intended to aid government, oil and gas companies, Aboriginal groups, resource managers and public stakeholders in better understanding the geographic distribution of areas which are sensitive for environmental and socio-economic reasons. The study area is located east of Baffin Island, Nunavut and encompasses marine habitat in Baffin Bay and Davis Strait. The boundaries of the study area are based on NOGB leasing grids applied in the Eastern Arctic, under which exploration and production licenses may be issued. Although portions of the study area hold high oil and gas potential and several small oil fields and substantial reserves of gas have been found since the 1960s in the north Baffin region, exploration for oil and gas has been limited to seismic operations and geological field work.DISCLAIMER: Please refer to the PEMT Disclaimer document or the Resource Constraints - Use Limitation in the Additional Information section below.Note: This is one of the 3 (three) datasets included in the PEMT application which includes the Beaufort Sea and Mackenzie Delta and High Arctic datasets.