Facilities used by the Ministry of Natural Resources' Aviation Forest Fire and Emergency Services (AFFES) branch. This dataset is used to support aviation forest fire and AFFES business operations.

Weather Elements on Grid (WEonG) based on the High Resolution Deterministic Prediction System (HRDPS) is a post-processing system designed to compute the weather elements required by different forecast programs (public, marine, aviation, air quality, etc.). This system amalgamates numerical and post-processed data using various diagnostic approaches. Hourly concepts are produced from different algorithms using outputs from the pan-Canadian High Resolution Deterministic Prediction System (HRDPS-NAT).

Canadian airports served by NAV CANADA control towers or flight service station.

The purpose of this dataset is to provide maintained runway locations as points. These points are the centroids of the Runway_Poly_25k dataset. Runways include airports, aerodromes, and airstrips managed by Transportation Aviation Yukon. The latitude and longitude locations in the table are based on the centroid of the runway.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)

This layer is derived from data provided by Nav Canada. This layer should not be used for navigation purposes. Official GEO title: Airport Other

VIDEO FLIGHT POINTS are a specific GPS spatial point recorded during the video taping of the shoreline. They are represented by a specific latitude and longitude taken at a specific date and time. They are associated with a specific VIDEO SEGMENT and link to online Youtube video of the recorded flight.

Offshore wind represents a potentially significant source of low-carbon energy for Canada, and ensuring that relevant, high-quality data and scientifically sound analyses are brought forward into decision-making processes will increase the chances of success for any future deployment of offshore wind in Canada. To support this objective, CanmetENERGY-Ottawa (CE-O), a federal laboratory within Natural Resources Canada (NRCan), completed a preliminary analysis of relevant considerations for offshore wind, with an initial focus on Atlantic Canada. To conduct the analysis, CE-O used geographic information system (GIS) software and methods and engaged with multiple federal government departments to acquire relevant data and obtain insights from subject matter experts on the appropriate use of these data in the context of the analysis. The purpose of this work is to support the identification of candidate regions within Atlantic Canada that could become designated offshore wind energy areas in the future.The study area for the analysis included the Gulf of St. Lawrence, the western and southern coasts of the island of Newfoundland, and the coastal waters south of Nova Scotia. Twelve input data layers representing various geophysical, ecological, and ocean use considerations were incorporated as part of a multi-criteria analysis (MCA) approach to evaluate the effects of multiple inputs within a consistent framework. Six scenarios were developed which allow for visualization of a range of outcomes according to the influence weighting applied to the different input layers and the suitability scoring applied within each layer.This preliminary assessment resulted in the identification of several areas which could be candidates for future designated offshore wind areas, including the areas of the Gulf of St. Lawrence north of Prince Edward Island and west of the island of Newfoundland, and areas surrounding Sable Island. This study is subject to several limitations, namely missing and incomplete data, lack of emphasis on temporal and cumulative effects, and the inherent subjectivity of the scoring scheme applied. Further work is necessary to address data gaps and take ecosystem wide impacts into account before deployment of offshore wind projects in Canada’s coastal waters. Despite these limitations, this study and the data compiled in its preparation can aid in identifying promising locations for further review.A description of the methodology used to undertake this study is contained in the accompanying report, available at the following link: https://doi.org/10.4095/331855. This report provides in depth detail into how these data layers were compiled and details any analysis that was done on the data to produce the final data layers in this package.

BC Airports identifies locations where aircraft may take-off and land. No guarantee is given that an identified point will be maintained to sufficient standards for landing and take-off of any/all aircraft. It includes airports, aerodromes, water aerodromes, heliports, and airstrips.

Geometric and conventional representation of airport facilities for planning purposes. The geospatial “aerodrome” data is structured according to the following layers of information:- CARTO-VOI-AERODROME-TRACK: A defined surface on earth intended to be used, in whole or in part, for the arrival, departure and maneuvers of aircraft.- CARTO-VOI-AERODROME-PARKING: A furnished area, off the airfield runway, intended for the parking of a certain number of aircraft.These elements form part of the layers in the digital cartographic compilation.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

The Automatic Identification System (AIS) is a global, satellite-based and terrestrial-based ship tracking system that uses shipborne equipment to remotely track vessel identification and positional information and is typically required on vessels of 300 gross tonnage or more on an international voyage, of 500 gross tonnage or more not on an international voyage, and passenger ships of all sizes. AIS tracking technologies are primarily used in support of real-time maritime domain awareness and for maritime security and safety of life at sea. This report describes a geographic information system (GIS) analysis of 2019 AIS data to produce yearly and monthly vessel density maps of all vessel classes combined and yearly density maps of each vessel class. The year 2019 was selected to portray shipping densities in a pre-COVID 19 pandemic depiction of the maritime transport sector in the Northwest Atlantic. Vessel density map applications include use in spatial analysis and decision support for marine spatial planning. In 2023 the process was applied to the years 2013 through to 2022 and were made available using the same processes that were applied to the original 2019 datasets.