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

This dataset identifies the geographic locations of marine ports, terminals, shipyards, and harbours on the west coast of British Columbia. The points were reviewed and cross referenced with government and industry data sources for geographic and attribute data accuracy.

'Province' and 'territory' refer to the major political units of Canada. From a statistical point of view, province and territory are basic areas for which data are tabulated. Canada is divided into 10 provinces and 3 territories. Statistics Canada uses standard codes and abbreviations to represent provinces and territories. The two-digit code that uniquely identifies each province/territory is based on the Standard Geographical Classification (SGC). The code is assigned from east to west. The first digit represents the geographical region of Canada in which the province/territory is located and the second digit denotes one of the 10 provinces and 3 territories.

This database aggregates basic information on orphaned and abandoned mine sites from participating Canadian jurisdictions, including their name, location, jurisdiciton, and the commodity that was mined. It was originally created in 2012 through the National Orphaned/Abandoned Mines Initiative and has undergone several updates since that time. Data on sites in each jurisdiction is owned and maintained by that jurisdiction. The database includes links to the corresponding records in that jursidiction. While the database includes common informaiton about all sites, there may be discrepancies in the types of data provided about sites in different jurisdictions and data from some jurisdictions may be updated more frequently than others.

FERRYSEG_OFFICIAL provides the information about the Ferry Connection Segments. Ferry Connection Segment is the specific representation of a portion of a ferry connection with uniform characteristics. FERRYSEG_OFFICIAL is one of the base layer used to create "Ferryseg" layer for Saskatchewan Upgraded Road Network (SURN) and National Road Network (NRN). This data layer has been created for mainly MHI data users, that require relatively up-to-date and accurate description of all ferry routes in the Province of Saskatchewan.FERRYSEG_OFFICIAL consists of the data for the average route a ferryboat takes when transporting vehicles between two fixed locations on the Road Network. "NID" National Identifier is used to manage the updates between data producer and data users. FERRYSEG_OFFICIAL data layer serves as a foundation for SURN, NRN, SASK911 and other applications.

The transport features of the CanVec series are derived from the National Road Network (NRN) and the National Railway Network (NRWN). The dataset describes roads, trails, bridges, railroads and their related information. The transport features include nautical facilities, track segments, track junctions, railway stations, track crossings, track marker posts, track structures, rail ferry segments, road segments, road ferry segments, road junctions, blocked passages, toll points, aerial cableway features, footbridges, trails, navigational aids, marinas and runways.The CanVec multiscale series is available as prepackaged downloadable files and by user-defined extent via a Geospatial data extraction tool.Related Products (Open Maps Links):[Topographic Data of Canada - CanVec Series](https://open.canada.ca/data/en/dataset/8ba2aa2a-7bb9-4448-b4d7-f164409fe056)

The resource management features of the CanVec series include power lines, communication lines, pipelines, valves, petroleum wells, wind-operated devices, transformer stations, ore extraction sites, aggregate extraction sites, peat extraction sites and oil and gas sites.The CanVec multiscale series is available as prepackaged downloadable files and by user-defined extent via a Geospatial data extraction tool.Related Products (Open Maps Links):[Topographic Data of Canada - CanVec Series](https://open.canada.ca/data/en/dataset/8ba2aa2a-7bb9-4448-b4d7-f164409fe056)

This data is intended to identify Canadian Alternate Exchange Areas described in https://tc.canada.ca/en/marine-transportation/marine-safety/list-canada-s-designated-alternate-ballast-water-exchange-area-fresh-waters-tp-13617e-2021. The data is not intended for navigation purposes.According to Canada’s Ballast Water Regulations, if your vessel enters waters under Canadian jurisdiction from somewhere other than the U.S. waters within the Great Lakes Basin, and it cannot conduct a ballast water exchange in the areas set out in paragraphs 14(1)(a) and (b) of the regulations, then it will have to conduct a ballast water exchange in one of the areas listed below:-Gulf of St. Lawrence-Atlantic Canada-Western Canada-Canadian Eastern Arctic-Canadian Western Arctic: If you bring your vessel to a Canadian port, offshore terminal or anchorage area in the Western Arctic ballast water must be exchanged in an area as far away from shore as possible, where the water is more than 100 meters deep.Legal Constraints: Users should be aware that the polygons depicting ballast water exchange areas are intended for illustration only and should not be used for navigational or legal purposes.

Geospatial data for public transit agencies in Canada, with information on stop locations, route locations, route types, level of service, wheel chair access, bike access, and more.

Description:Data on recreational boating are needed for marine spatial planning initiatives in British Columbia (BC). Vessel traffic data are typically obtained by analyzing automatic identification system (AIS) vessel tracking data, but recreational vessels are often omitted or underrepresented in AIS data because they are not required to carry AIS tracking devices. Transport Canada’s National Aerial Surveillance Program (NASP) conducted aerial surveys to collect information on recreational vessels along several sections of the BC coast between 2018 and 2022. Recreational vessel sightings were modeled against predictor variables (e.g., distance to shore, water depth, distance to, and density of marinas) to predict the number of recreational vessels along coastal waters of BC.The files included here are:--A Geodatabase (‘Recreational_Boating_Data_Model’), which includes: (1) recreational vessel sightings data collected by NASP in BC and used in the recreational vessel traffic model (‘Recreational_Vessels_PointData_BC’); (2) aerial survey effort (or number of aerial surveys) raster dataset (‘surveyeffort’); and (3) a vector grid dataset (2.5 km resolution) containing the predicted number of recreational vessels per cell and predictor variables (‘Recreational_Boating_Model_Results_BC).--Scripts folder which includes R Markdown file with R code to run the modelling analysis (‘Recreational_Boating_Model_R_Script’) and data used to run the code.Methods:Data on recreational vessels were collected by NASP during planned aerial surveys along pre-determined routes along the BC coast from 2018 to 2022. Data on non-AIS recreational vessels were collected using video cameras onboard the aircraft, and data on AIS recreational vessels using an AIS receiver also onboard the aircraft. Recreational boating predictors explored were: water depth, distance to shore, distance to marinas, density of marinas, latitude, and longitude. Recreational vessel traffic models were fitted using Generalized Linear Models (GLM) R packages and libraries used here include: AED (Roman Lustrik, 2021) and MASS (Venables, W. N., Ripley, 2002), pscl package (Zeileis, Kleiber, and Jackman, 2008) for zeroinfl() and hurdle() function. Final model was selected based on the Akaike’s information criterion (AIC) and the Bayes’ information criterion (BIC). An R Markdown file with code use to run this analysis is included in the data package in a folder called Script. Spatial Predictive Model: The selected model, ZINB, consist of two parts: one with a binomial process that predicts the probability of encountering a recreational vessel, and a second part that predicts the number of recreational vessels via a count model. The closer to shore and to marinas, and the higher the density of marinas, the higher the predicted number of recreational vessels. The probability of encountering recreational vessels is driven by water depth and distance to shore. For more information on methodology, consult metadata pdf available with the Open Data record.References:Serra-Sogas, N. et al. 2021. Using aerial surveys to fill gaps in AIS vessel traffic data to inform threat assessments, vessel management and planning. Marine Policy 133: 104765. https://doi.org/10.1016/j.marpol.2021.104765Data Sources:Recreational vessel sightings and survey effort: Data collected by NASP and analyzed by Norma Serra to extract vessel information and survey effort (more information on how this data was analyzed see SerraSogas et al, 2021). Bathymetry data for the whole BC coast and only waters within the Canadian EEZ was provided by DFO – Science (Selina Agbayani). The data layer was presented as a raster file of 100 meters resolution. Coastline dataset used to estimate distance to shore and to clip grid was provided by DFO – Science (Selina Agbayani), created by David Williams and Yuriko Hashimoto (DFO – Oceans). Marinas dataset was provided by DFO – Science (Selina Agbayani), created by Josie Iacarella (DFO – Science). This dataset includes large and medium size marinas and fishing lodges. The data can be downloaded from here: Floating Structures in the Pacific Northwest - Open Government Portal (https://open.canada.ca/data/en/dataset/049770ef-6cb3-44ee-afc8-5d77d6200a12)Uncertainties:Model results are based on recreational vessels sighted by NASP and their related predictor variables and not always might reflect real-world vessel distributions. Any biases caused by the opportunistic nature of the NASP surveys were minimized by using survey effort as an offset variable.