This GIS dataset represents a reclassification of existing surficial map information for the purpose of portraying the distribution of sand and gravel deposits in Alberta. The surficial geology of Alberta ungeneralised digital mosaic (Alberta Geological Survey DIG2013-0001) represents the primary source of information used in this reclassification. This dataset was updated with more recently published 1:100,000 scale surficial geology maps, and where appropriate new polygon features that were digitized from line features in the Glacial Landforms of Alberta (Alberta Geological Survey Map 604 and DIG2014-0022). The updated surficial geology mosaic was then reclassified using a thematically-based attribute table which categorizes the original surficial geology features based on their sand and gravel component. Attributes within this table comprise: (1) an approximation of the material type (MATERIAL). (2) the aerial proportion that this material represents of the polygon, as a percentage (PROPORTION). (3) an indication of whether the sand and gravel unit is mapped at the land surface or is buried (SRF_BURIED). (4) the depositional environment relating to the sand and gravel unit (GENESIS). (5) the reference source to the original data (SOURCE_MAP). (6) the GIS dataset from which the features were derived (DATASET). and (7) the mapping scale (SCALE). The MATERIAL honours the original surficial geology polygons when sufficiently precise texture/material information was provided. Otherwise MATERIAL is based on the typical range of materials that are associated with each surficial geology unit on a litho-genetic basis, using the standard Alberta Geological Survey surficial geology legend. When multiple surficial geological units that contain sand and gravel are present within a single polygon (i.e. 60% eolian deposits and 40% fluvial deposits), MATERIAL reflects the unit with the greatest proportion. For geological units whose material properties are of marginal significance as a sand and gravel deposit, particularly those that contain a mixture of silt and sand, a hierarchy was used to determine whether they are included as sand and gravel deposits. Fluvial deposits, littoral and nearshore deposits, and eolian deposits with a silt textural modifier in the original mapping data were included as potential sand and/or gravel deposits because these units are often interspersed with sand and/or gravel materials. Glaciolacustrine deposits with a silt textural modifier were not included because this environment generally does not result in the deposition of extensive sand and gravel sediments. After all of the attributes had been updated, all polygons that may contain some component of sand or gravel were extracted from this dataset to create the sand and gravel potential for Alberta digital mosaic. With this dataset, users can view the extent of surficial sand and gravel deposits in the province in a single GIS layer without the need to interpret this information from a variety of legends in the original surficial geology datasets. Users can further highlight polygons that may represent more suitable targets for sand and gravel based on the estimated material type (i.e. by eliminating polygons that typically contain large amounts of silt and fine sand), the estimated proportion of sand and gravel within the polygon, and depositional environment. This dataset best portrays sand and gravel potential that occurs at the land surface or in the very near surface, and does not attempt evaluate the sub-surface distribution of sand and gravel units. This dataset also does not provide any direct assessment of aggregate quality or thickness, and the material information is mostly inferred from the general association between certain surficial material types and their geological, depositional environment. Furthermore, the sand and gravel potential dataset is based on surficial geology maps produced at different scales and using different legends, therefore the detail and amount of information provided by these polygons will exhibit regional variations. The mapping scale for each polygon is provided in the SCALE attribute.

Areas of non-productive forest land in the Cariboo Region. Includes icefields, alpine areas, rock, gravel pits, sand, clay, non-productive brush, etc. From FC1 circa 2002

This GIS dataset is a result of the compilation of all existing Alberta Geological Survey sand and gravel geology and resource data into digital format. Data sources include Alberta Geological Survey maps and reports produced between 1976 and 2006. References are provided as an attribute so the user can refer back to the original maps and reports. Attributes include study level, material description, references, area, sand and gravel thickness, and gravel and sand volumes. In 2009, data from newly mapped area NTS 83N/NE were added.

This dataset results from mapping the surficial geology, and sand and gravel deposits with aggregate potential in the McLennan area (NTS 83N). This shapefile shows where materials and geology were observed at natural outcrops, sand and gravel pits, hand auger holes, and excavations dug by a backhoe. The type, thickness and order of the observed materials are described in the attribute table. Map 536 is a PDF version generated from the shapefiles.

Bay Scale Assessment of Nearshore Habitat - Bras d'Or Lake - Eskasoni 2007 data is part of the publication Bay Scale Assessment of Nearshore Habitat Bras d'Or Lakes. A history of nearshore benthic surveys of Bras d’Or Lake from 2005 – 2011 is presented. Early work utilized drop camera and fixed mount sidescan. The next phase was one of towfish development, where camera and sidescan were placed on one platform with transponder-based positioning. From 2009 to 2011 the new towfish was used to ground truth an echosounder. The surveys were performed primarily in the northern half of the lake; from 10 m depth right into the shallows at less than 1 m. Different shorelines could be distinguished from others based upon the relative proportions of substrate types and macrophyte canopy. The vast majority of macrophytes occurred within the first 3 m of depth. This zone was dominated by a thin but consistent cover of eelgrass (Zostera marina L.) on almost all shores with a current or wave regime conducive to the growth of this plant. However, the eelgrass beds were frequently in poor shape and the negative impacts of commonly occurring water column turbidity, siltation, or possible localized eutrophication, are suspected. All survey data were placed into a Geographic Information System, and this document is a guide to that package. The Geographic Information System could be used to answer management questions such as the placement and character of habitat compensation projects, the selection of nearshore protected areas or as a baseline to determine long term changes.Vandermeulen, H. 2016. Video-sidescan and echosounder surveys of nearshore Bras d’Or Lake. Can. Tech. Rep. Fish. Aquat. Sci. 3183: viii + 39 p.Cite this data as: Vandermeulen H. Bay Scale Assessment of Nearshore Habitat Bras d'Or Lake - Eskasoni 2007. Published May 2022. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S.

Sand and gravel include information related to aggregate deposits.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Grain size is the most fundamental physical property of sediment, and these data are widely used in a variety of applications in science. Marine expeditions of the Geological Survey of Canada have been collecting grain size information on seabed and sub-seabed samples for over 50 years. Results have been recorded at 5th phi midpoints since the early 1990's in contrast to the earlier full, half or quarter phi interval end point values. Users of high resolution data must note that the sum of %Silt and %Clay equals the total %Mud makeup and that %Gravel, %Sand, %Silt and %Clay sum to 100%. Summary statistics include percentages of gravel, sand, silt, clay and mud as well as mean, kurtosis, skewness and standard deviation. The quality of these data varies. Results should be used with some caution as they may not be fully representative of seabed grainsize, particularly in areas of sandy and coarser sediment (e.g., sand and mud can leak out of the sampler during recovery). Canada makes no representation or warranty of any kind with respect to the accuracy, usefulness, novelty, validity, scope, completeness or currency of the data and expressly disclaims any implied warranty of merchantability or fitness for a particular purpose of the data. For the purpose of the web mapping service, grain size data are sorted by the expedition id. Coarse and detailed grain size distribution plots are shown when a point is chosen. If the sample contains more that one sub-sample ( e.g., as with a piston core sequence), the grain size plots are stacked in the display window from the top of the core downwards.

This deep water substrate bottom type model was created to aid in habitat modeling, and to complement the nearshore bottom patches. It was created from a combination of bathymetrically-derived layers in addition to bottom type observations. Using random forest classification, the relationship between observed substrates and bathymetric derivatives was estimated across the entire area of interest. The raster is categorized into: 1) Rock, 2) Mixed, 3) Sand, 4) Mud

The data in this layer represents habitat suitability of soft-shelled clams (Mya arenaria) in the DFO Maritimes region, and was developed using an interdepartmental approach. Substrate classification data as well as bathymetric data for the Region were used to identify potential habitat for soft-shelled clams. Substrates identified as suitable included: sand, mud, sand and mud (Greenlaw, 2022). Contours (0m and 70m) from GEBCO bathymetric data were used to isolate depths between which soft-shelled clams are present. At this stage, a polygon reflecting soft substrates from 0-70m was created as "Suitable". A "Not Suitable" layer was similarly created using the substrates: boulders, continuous bedrock, discontinuous bedrock, gravel, mixed sediment, sand and gravel.To digitally validate the model, the Regional shoreline was divided into subsectors (developed by Environment and Climate Change Canada for the Canadian Shellfish Sanitation Program). Data from DFO (clam harvesting intensity) as well as Conservation and Protection (clam harvesting infraction locations) were used to established species presence within each sub-sector. If there had been any harvesting activity, legal or illegal, in an individual subsector, it was considered "Suitable and Validated". Merged into one final product, the model includes areas that are "Not Suitable", "Suitable", as well as "Suitable and Validated" for soft-shelled clam habitat.Cite this data as: Harvey, C., Vincent, M., Greyson, P., Hamer, A. (2024) Data of: A Soft-Shelled Clam (Mya arenaria) Habitat Suitability Model For The DFO Maritimes Region.Published: January 2024. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, St. Andrews, N.B. https://open.canada.ca/data/en/dataset/c76f7813-d802-4b31-8ebe-476f8a7cacf2

The National Ecological Framework for Canada's "Soil Texture by Ecodistrict” dataset contains tables that provide soil texture information within the ecodistrict framework polygon. It provides soil texture codes and their English and French language descriptions as well as the percentage of the polygon that the component occupies.Soil texture indicates the relative proportions of the various soil separates (sand, silt, clay) as described by classes of texture. Soil separates are mineral particles, 2.0 mm in diameter and include: gravel 0.2 -7.5 cm and cobbles 7.5-25.0 cm. There are 12 texture group classes definitions and one class definition for Not Applicable (which indicates, for example, water, ice or urban areas).