This dataset provides information related to the top-spending off-mine-site exploration and deposit appraisal projects in Canada for the given reference year. The dataset is maintained by the Lands and Minerals Sector, Natural Resources Canada, and forms the basis for the annual Map of Top 100 Exploration and Deposit Appraisal Projects in Canada.Related product:- **[Principal Mineral Areas, Producing Mines, and Oil and Gas Fields (900A)](https://open.canada.ca/data/en/dataset/000183ed-8864-42f0-ae43-c4313a860720)**

This dataset is produced and published annually by Natural Resources Canada. It contains a variety of statistics on Canada’s mineral production, and provides the geographic locations of significant metallic, nonmetallic and coal mines, oil sands mines, selected metallurgical works and gas fields for the provinces and territories of Canada.Related product:- **[Top 100 Exploration Projects](https://open.canada.ca/data/en/dataset/b64179f3-ea0f-4abb-9cc5-85432fc958a0)**

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.

Prospectivity model highlights areas of Canada with the greatest potential for magmatic nickel deposits. The preferred prospectivity model is based on public geological, geochemical, and geophysical datasets that were spatially indexed using the H3 discrete global grid system. Each H3 cell is associated with a prospectivity value, or class probability, calculated from the best-performing gradient boosting machines model. Model results are filtered to include the top 20% of prospectivity values for visualization purposes.

Prospectivity model highlights areas of Canada with the greatest potential for clastic-dominated zinc deposits. The preferred prospectivity model is based on public geological, geochemical, and geophysical datasets that were spatially indexed using the H3 discrete global grid system. Each H3 cell is associated with a prospectivity value, or class probability, calculated from the best-performing gradient boosting machines model. Model results are filtered to include the top 20% of prospectivity values for visualization purposes.

Prospectivity model highlights areas of Canada with the greatest potential for Mississippi Valley-type zinc deposits. The preferred prospectivity model is based on public geological, geochemical, and geophysical datasets that were spatially indexed using the H3 discrete global grid system. Each H3 cell is associated with a prospectivity value, or class probability, calculated from the best-performing gradient boosting machines model. Model results are filtered to include the top 20% of prospectivity values for visualization purposes.

These structure, isopach and zero edge files are part of a series of stratigraphic framework maps for the Saskatchewan Phanerozoic Fluids and Petroleum Systems (SPFPS) project.The series of stratigraphic framework maps for the Saskatchewan Phanerozoic Fluids and Petroleum Systems (SPFPS) project have been produced using 2 km equi-spaced modified grids generated from Golden Software’s Surfer 9 kriging algorithm. The dataset used to produce each of the maps in this series was created using data from several projects completed by the Ministry (Christopher, 2003; Saskatchewan Industry and Resources et al., 2004; Kreis et al., 2004; Marsh and Heinemann, 2006; Saskatchewan Ministry of Energy and Resources et al., 2007; Heinemann and Marsh, 2009); these data were validated and edited as required to facilitate correlations between the various regional projects. In addition, to minimize edge effects during contouring, the senior author also generated stratigraphic data from wells in adjacent jurisdictions.

Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM+) sensors were used to generate the circa 2010 Mosaic of Canada at 30 m spatial resolution. All scenes were processed to Standard Terrain Correction Level 1T by the United States Geological Survey (USGS). Further processing performed by the Canada Centre for Remote Sensing included conversion of sensor measurements to top of atmosphere reflectance, cloud and cloud shadow detection, re-projection, selection of best measurements, mosaic generation ,noise removal and quality control. To provide a clear sky measurement for each location in Canada, data from the years 2009, 2010, and 2011 were used, but 2010 was preferentially selected. Bands 3 (0.63-0.69 µm), 4 (0.76-0.90 µm), 5 (1.55-1.75 µm), and 7 (2.08-2.35 µm) are provided in this version as significant atmosphere effects strongly limit the quality of the blue (0.45-0.52 µm) and green (0.52-0.60 µm) bands. Multi-criteria compositing was used for the selection of the most representative pixel. For ETM+ onboard Landsat 7 a scan line malfunction caused missing lines of data in all scenes collected after May 2003. Atmosphere and target variability between scenes cause these lines to have significant radiometric differences in some cases. A Fourier transformation approach was applied to correct this occurrence. This mosaic was developed for land cover and biophysical mapping applications across Canada. Other applications of these data are also possible, but should consider the temporal and spectral limitations of the product. Research to enhance the spatial, spectral and temporal aspects are in development for future versions of moderate resolution products from historical Landsat sensors, Landsat 8, and Sentinel 2 data.

The mapping depicts a first-order estimate of the combined volumetric percentage of excess ice in the top 5 m of permafrost from segregated, wedge, and relict ice. The estimates for the three ice types are based on modelling by O'Neill et al. (2019) (https://doi.org/10.5194/tc-13-753-2019), and informed by available published values of ground ice content and expert knowledge. The mapping offers an improved depiction of ground ice in Canada at a broad scale, incorporating current knowledge on the associations between geological and environmental conditions and ground ice type and abundance. It provides a foundation for hypothesis testing related to broad-scale controls on ground ice formation, preservation, and melt.

This dataset represents meat weight and shell height data of commercial size Sea Scallop (Placopecten magellanicus; ≥ 80 mm shell height) from 2011-2023 from the Bay of Fundy Inshore Scallop Survey collected from June to mid-August. Wet meat weights were recorded to a tenth of a gram and shell heights are measured in millimeters. Meat weights and shell heights are sampled from a subset of scallops caught on survey and this detailed sampling is conducted from approximately half of the tows conducted. Each row in the dataset represents an individual scallop and contains information such as tow number, tow date, cruise name, 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 Meat Weight and Shell Height Data 2011 to 2023. Published: December 2025. Population Ecology Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/65d32794-2d81-4682-b0ea-8d8bbe907a58