This service shows the average owner estimated value of dwelling for Canada by 2016 census subdivision. The data is from the Census Profile, Statistics Canada Catalogue no. 98-316-X2016001.Value (owner estimated) of private dwelling refers to the dollar amount expected by the owner if the asset were to be sold.In the context of dwelling, it refers to the value of the entire dwelling, including the value of the land it is on and of any other structure, such as a garage, which is on the property. If the dwelling is located in a building which contains several dwellings, or a combination of residential and business premises, all of which the household owns, the value is estimated as a portion of the market value that applies only to the dwelling in which the household resides. For additional information refer to 'Value (owner estimated)' in the 2016 Census Dictionary.For additional information refer to 'Value (owner estimated)' in the 2016 Census DictionaryTo have a cartographic representation of the ecumene with this socio-economic indicator, it is recommended to add as the first layer, the “NRCan - 2016 population ecumene by census subdivision” web service, accessible in the data resources section below.

This service shows the average owner estimated value of dwelling for Canada by 2016 census division. The data is from the Census Profile, Statistics Canada Catalogue no. 98-316-X2016001.Value (owner estimated) of private dwelling refers to the dollar amount expected by the owner if the asset were to be sold.In the context of dwelling, it refers to the value of the entire dwelling, including the value of the land it is on and of any other structure, such as a garage, which is on the property. If the dwelling is located in a building which contains several dwellings, or a combination of residential and business premises, all of which the household owns, the value is estimated as a portion of the market value that applies only to the dwelling in which the household resides. For additional information refer to 'Value (owner estimated)' in the 2016 Census Dictionary.For additional information refer to 'Value (owner estimated)' in the 2016 Census Dictionary.To have a cartographic representation of the ecumene with this socio-economic indicator, it is recommended to add as the first layer, the “NRCan - 2016 population ecumene by census division” web service, accessible in the data resources section below.

Predicted bulk density (g/cm3) at defined depth ranges (0–5 cm, 5–15 cm, 15–30 cm, 30–60 cm, 60–100 cm). The mass of dry soil per unit bulk volume.

Predicted silt percentage (%) at a defined depth range (0–5 cm, 5–15 cm, 15–30 cm, 30–60 cm, 60–100 cm).

Predicted cation exchange capacity (meq/100g) at a defined depth range (0–5 cm, 5–15 cm, 15–30 cm, 30–60 cm, 60–100 cm). The interchange of a cation in solution and another cation on the surface of any surface-active material such as clay colloid or organic colloid.

This service shows the median total income of households in 2015 for Canada by 2016 census division.The data is from the Census Profile, Statistics Canada Catalogue no. 98-316-X2016001.Total income refers to the sum of certain incomes (in cash and, in some circumstances, in kind) of the statistical unit during a specified reference period. The median income of a specified group is the amount that divides the income distribution of that group into two halves. For additional information refer to 'Total income' in the 2016 Census Dictionary.For additional information refer to 'Total income' in the 2016 Census Dictionary.To have a cartographic representation of the ecumene with this socio-economic indicator, it is recommended to add as the first layer, the “NRCan - 2016 population ecumene by census division” web service, accessible in the data resources section below.

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)

Forest Gross Stem Volume 2015Gross stem volume. It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). Individual tree gross volumes are calculated using species-specific allometric equations. In the measured ground plots, gross total volume per hectare is calculated by summing the gross total volume of all trees and dividing by the area of the plot (units = m3/ha). 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 represents abundance data of commercial size Sea Scallop (Placopecten magellanicus; ≥ 80 mm shell height) from 2011-2023 from the Bay of Fundy Inshore Scallop Survey. Data is binned into 5-mm shell height bins, is prorated to an 800 m tow length and 17.5 feet (5.334 m) drag width (i.e., representing an area swept of 4267 m2), and was collected using unlined dredge gear. Each row represents a tow and contains information such as tow date, cruise name, gear type, geographical coordinates (decimal degrees, WGS 84) and the Scallop Production Area in which the tow took place. Survey protocols are documented in Glass (2017). This dataset contains tow data from a comparative survey conducted in 2012 (Smith et al., 2013). Further, these data correspond to the publication of Hebert et al. (2025).ReferencesGlass, A. 2017. Maritimes Region Inshore Scallop Assessment Survey: Detailed Technical Description. Can. Tech. Rep. Fish. Aquat. Sci. 3231: v + 32 p.Hebert, N, Sameoto, J.A., Keith, D.M., Murphy, O.A., Brown, C.J., Flemming, J. 2025. Interannual variability in the length–weight relationship can disrupt the abundance–biomass correlation of sea scallop (Placopecten magellanicus). ICES. J. Mar. Sci. Smith, S.J., Glass, A., Sameoto. J., Hubley, B., Reeves, A., and Nasmith, L. 2013. Comparative survey between Digby and Miracle drag gear for scallop surveys in the Bay of Fundy. DFO Can. Sci. Advis. Sec. Res. Doc. 2012/161. iv + 20 p.Cite this data as: Sameoto, J.A. Data of: Bay of Fundy Sea Scallop Commercial Size Abundance Data. Published: December 2025. Population Ecology Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/ecc09d98-56ed-4a27-ad62-5c3714a1d9b4

This data set represents the digital Mineral Resource potential of the Province of Saskatchewan.This dataset represents the mineral resource potential of Saskatchewan. Methodologies used to determine a ranking system of low to high mineral potential areas. 6 being high mineral potential while 1 being low. The data was created as a file geodatabase feature class and output for public distribution. **Please Note – All published Saskatchewan Geological Survey datasets, including those available through the Saskatchewan Mining and Petroleum GeoAtlas, are sourced from the Enterprise GIS Data Warehouse.  They are therefore identical and share the same refresh schedule.