Map of Canada showing locations of facilities selling nautical charts in both paper and digital formats.

Transportation networks (transportation)The means and aids for conveying people and goods. For example, resources describing roads, airports and airstrips, shipping routes, tunnels, nautical charts, vehicle or vessel location, aeronautical charts, and railways.

This service provides a compilation of Electronic Navigational Charts (ENC) produced by the Canadian Hydrographic Service. All information provided by this service conforms to the International Hydrographic Organization (IHO) Publication S-57. An ENC contains all the chart information useful for navigation, and may contain supplementary information in addition to that contained in the paper chart. This service is not for navigation.

The Canadian Hydrographic Service (CHS) Low Water Mark Lines provide alongshore and across-shore geomorphological and biological attributes of the low water mark shoreline. The lines are used in the CHS nautical charts to represent the level reached by sea water at low tide.

The Canadian Hydrographic Service (CHS) High Water Mark Lines provide alongshore and across-shore geomorphological and biological attributes of the high water mark shoreline. The lines are used in the CHS nautical charts to represent the level reached by sea water at high tide.

INW - Inland water resources (inlandWaters)Inland water features, drainage systems, and their characteristics. For example, resources describing rivers and glaciers, salt lakes, water use plans, dams, currents, floods, water quality, and hydrographic charts

Canadian Hydrographic Service (CHS) has made available all the publishable limits of modern day surveys whose data has been collected since 1989.

This record contains two-weekly minimum sea ice concentration images of the Canadian Beaufort Sea at 1.1 km resolution. The dataset originated from the Canadian Ice Service (CIS) Digital Archive weekly regional charts for the western Arctic (See “additional credit” for a link to these data), created by synthesis of remotely-sensed, ship and airborne observations (Fequet, 2005). These vector ice charts were gridded at 1.1 km resolution and aggregated into two-week composites by calculating the minimum sea-ice concentration at each grid cell over each two-week interval in each year. Week numbers were defined using the ISO 8601 convention, and sea-ice concentration isrepresented in tenths (with 0/10 corresponding to an ice-free pixel, ranging to 10/10 corresponding to 100% pixel coverage with sea-ice). The result is 12 composite images per year in 1998 through 2020 (23 years), corresponding to https://open.canada.ca/data/en/dataset/ee27e86f-7b18-4e3f-8444-0c5efb6110a4. For further details, see Galley et al., 2022.

This dataset is a contribution to the development of a kelp distribution vector dataset.Bull kelp (Nereocystis leutkeana) and giant kelp (Macrocystis pyrifera) are important canopy-forming kelp species found in marine nearshore habitats on the West coast of Canada. Often referred to as a foundation species, beds of kelp form structural underwater forests that offer habitat for fishes and invertebrates. Despite its far-ranging importance, kelp has experienced a decline in the west coast of North America. The losses have been in response to direct harvest, increase in herbivores through the removal of predators by fisheries or diseases, increase in water turbidity from shoreline development as well as sea temperature change, ocean acidification, and increased storm activates. Understanding these impacts and the level of resilience of different kelp populations requires spatiotemporal baselines of kelp distribution. The area covered by this dataset includes the BC coast and extends to portions of the Washington and Alaska coasts. This dataset was created using 137 British Admiralty (BA) charts, including insets, with scales ranging from 1:6,080 to 1:500,000, created between 1858 and 1956. All surveys were based on triangulation, in which a sextant or theodolite was used to determine latitude and angles, while a chronometer was used to help determine longitude.First, each BA chart was scanned by the Canadian Hydrographic Service (CHS) using the CHS Colortrac large format scanner, and saved as a Tagged Image Format at 200 DPI, which was deemed sufficient resolution to properly visualize all the features of interest. Subsequently, the scanned charts were imported into ESRI ArcMap and georeferenced directly to WGS84 using CHS georeferencing standards and principles (charts.gc.ca). In order to minimize error, a hierarchy of control points was used, ranging from high survey order control points to comparing conspicuous stable rock features apparent in satellite imagery. The georeferencing result was further validated against satellite imagery, CHS charts and fieldsheets, the CHS-Pacific High Water Line (charts.gc.ca), and adjacent and overlapping BA charts. Finally, the kelp features were digitized, and corresponding chart information (scale, chart number, title, survey start year, survey end year, and comments) was added as attributes to each feature. Given the observed differences in kelp feature representation at different scales, when digitizing kelp features, polygons were used to represent the discrete observations, and as such, they represent presence of kelp and not kelp area. Polygons were created by tracing around the kelp feature, aiming to keep the outline close to the stipe and blades.The accuracy of the location of the digitized kelp features was defined using a reliability criterion, which considers the location of the digitized kelp feature (polygon) in relation to the local depth in which the feature occurs. For this, we defined a depth threshold of 40 m to represent a low likelihood of kelp habitat in areas deeper than the threshold.An accuracy assessment of the digitized kelp features concluded that 99% of the kelp features occurred in expected areas within a depth of less than 40 m, and only about 1% of the features occurred completely outside of this depth.

The amount of groundwater exploited is estimated in m³/year. Groundwater usages are classified in four categories: agricultural, industrial, domestic and energy. Typically, groundwater usage should be represented as a series of sub-polygons or points fitting inside the boundary of the hydrogeological unit. The scope and method used to estimate the amount of water are described in the metadata associated with the dataset. The dataset identifies the main usages for the hydrogeological unit. It features numbers and percentages describing groundwater usages for a predetermined scope. The groundwater usage is frequently compiled by municipalities or counties. It could then be possible to display the usage by superimposing a series of pie charts depicting the groundwater usages over multiples administrative areas.