RAILLINE_OFFICIAL is one of the important layers for Saskatchewan Upgraded Road Network (SURN) and National Road Network (NRN). The RAILLINE_OFFICIAL provides the information of Railine to clients that require accurate, relatively up-to-date and detailed description of Saskatchewan Railline Network.RAILLINE_OFFICIAL data layer was developed by the Saskatchewan Ministry of Highways & infrastructure and contains the OFFICIAL version of the rail lines network in the province. RAILLINE_OFFICIAL layer has the linear geomtry of the CN, CP and provincial/shortline rail line in Saskatchewan. This version of the network is the one used for mapping, querying and plotting.

STE_SCANNED_MAP_BOUNDARY_SP includes an index of the mapsheet grid location of Soils, Terrain, Ecosystems and related scanned maps (including Agriculture Capability and Climate Capability maps). These maps are intended for on-screen viewing or printing. The majority of the maps have been geo-referenced. Mapping may not cover the whole map grid area. Some maps are interim or draft and may have been superseded. Some files are of related legends and map project text. Associated scanned map boundary attributes describe the project map (project level metadata) and provide a link for downloading the map, plus links to related reports, geo-referenced maps, and GIS digital data available from other sources. ATTENTION - The IMAGE_URL link is only useable by BC government staff. Public users can download the scanned maps by using the ECOCAT_URL link. There is no charge for the scanned map files. Please note that some maps and more recent mapping may also be available in digital GIS format. See - Ecosystem and Terrain Mapping Data Inventory.

This is a spatial layer showing Ministry of Forests Map Notation Lines. These are the spatial representation of the polygonal geometry for FSR Dedications and FSR Gravel Pits

This is a spatial layer showing Ministry of Forests Map Notation Lines. These are the spatial representation of the linear geometry for FSR Declarations and FSR Gazettes Unsurveyed.

GeoAI are buildings, hydrography, forests, and roads automatically extracted using Deep Learning models applied to a source dataset, typically aerial or satellite images. The primary aim of GeoAI is to increase Canada's availability of high-resolution foundational geospatial data for both spatial and temporal coverage.‌The infrastructure and expertise put in place by NRCan enables a rapid, efficient, and scalable data creation process through the use of leading-edge technology and Artificial Intelligence models. Published datasets for a given source can be revisited at a later date as more accurate models are developed and put into production. For now, only static files are available, but as the series develops, new products and services will be added.

The marks left in the seabed by the commercial anchoring process can be seen as linear features in high-resolution multibeam bathymetry data. These features have been digitized to polylines for individual marks and polygons for anchor scour zones for British Columbia's (BC) commercial anchorages. They are made available via the Federal Geospatial Platform (FGP) for use in a Geographical Information System (GIS). This feature dataset is complete for published BC commercial anchorages and the multibeam bathymetry data available in 2021. It does not represent features produced since the collection of each multibeam bathymetry survey nor any features infilled since. The data are intended to be used for scientific research to better understand the cumulative impacts to the seabed from commercial anchoring at a 1:5000 scale or greater.

One of the spatial views of the BC WATERSHED ATLAS 50K, which is the digital basemap representation of the aquatic Man-made waterbodies, Wetlands and Double-line Rivers based on the 1:50,000 scale Canadian National Topographic Series of Maps.

This layer represents Land use polygons as determined by a combination of analytic techniques, mostly using Landsat 5 image mosaics . BTM 1 was done on a federal satellite image base that was only accurate to about 250m. The images were geo-corrected, not ortho-corrected, so there is distortion in areas of high relief. This is not a multipart feature

The data layer (.shp) presented is the result of an unsupervised classification method for classifying seafloor habitat on German Bank (off South West Nova Scotia, Canada). This method involves separating environmental variables derived from multibeam bathymetry (Slope, Curvature) and backscatter (principal components: Q1, Q2, and Q3) into spatial units (i.e. pixels) and classifying the acoustically separated units into 5 habitat classes (Reef, Glacial Till, Silt, Silt with Bedforms, and Sand with Bedforms) using in situ data (imagery). Benthoscape classes (synonymous to landscape classifications in terrestrial ecology) describe the geomorphology and biology of the seafloor and are derived from elements of the seafloor that were acoustically distinguishable.Unsupervised classifications (acoustic classifications) optimized at 15 classes using Idrisi CLUSTER method (pixel based)Number representing the benthoscape classes (CLASS) derived from in situ imagery and video (See Brown et al., 2012, Figure 3, Table 1).Benthoscape classes (See Brown et al., 2012, Figure 3).Reference:Brown, C. J., Sameoto, J. A., & Smith, S. J. (2012). Multiple methods, maps, and management applications: Purpose made seafloor maps in support of ocean management. Journal of Sea Research, 72, 1–13. https://doi.org/10.1016/j.seares.2012.04.009Cite this data as: Brown, C. J., Sameoto, J. A., & Smith, S. J. Data of: Benthoscape Map of German Bank. Published: February 2021. Population Ecology Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/b7f81d4a-2cb6-4393-b35b-e536ec63e834

The Site / Structure Addresses layer represents the location of a site, or structure, or the location of access for the site, or structure, for the City of Whitehorse. Site / Structure addresses may also represent landmarks. Address points have the ability to locate sites that otherwise may not geocode correctly using the road centreline data, areas of unusual addressing, and other areas where the data is available.Data was modeled using the NENA NG9-1-1 GIS Data Template (NENA-REF-006. 2 -202 2 ).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)