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.

Natural gas onshore facilities used to receive, unload, load, store, gasify, liquefy, process and transport by ship, natural gas that is imported from a foreign country, exported to a foreign country, or interior commerce.Mapping Resources implemented as part of the North American Cooperation on Energy Information (NACEI) between the Department of Energy of the United States of America, the Department of Natural Resources of Canada, and the Ministry of Energy of the United Mexican States.The participating Agencies and Institutions shall not be held liable for improper or incorrect use of the data described and/or contained herein. These data and related graphics, if available, are not legal documents and are not intended to be used as such. The information contained in these data is dynamic and may change over time and may differ from other official information. The Agencies and Institutions participants give no warranty, expressed or implied, as to the accuracy, reliability, or completeness of these data.

Routes that cruise ships travel off the coast of BC

Ferry Terminals is a point dataset identifying vehicle and passenger ferry terminals in British Columbia.

Itinerary of the various bus routes managed by the City of Rouyn-Noranda**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Sub-surface facilities used for storing natural gas. The facilities are usually hollowed-out salt domes, geological reservoirs (depleted oil or gas field) or water bearing sands (called aquifers) topped by an impermeable cap rock.Mapping Resources implemented as part of the North American Cooperation on Energy Information (NACEI) between the Department of Energy of the United States of America, the Department of Natural Resources of Canada, and the Ministry of Energy of the United Mexican States.The participating Agencies and Institutions shall not be held liable for improper or incorrect use of the data described and/or contained herein. These data and related graphics, if available, are not legal documents and are not intended to be used as such. The information contained in these data is dynamic and may change over time and may differ from other official information. The Agencies and Institutions participants give no warranty, expressed or implied, as to the accuracy, reliability, or completeness of these data.

All stops in the public transport network managed by the City of Rouyn-Noranda**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

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.

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

This is a point layer of the names and locations of the actively used commercial shipping anchorages in British Columbia. These point locations were manually compiled from available port guides and documents. The objective of this dataset is to provide a consolidated file containing all active commercial shipping anchorage locations as there has been a lack of consistency between different sources due to variations in names and locations in different datasets and historical changes to anchorage locations.