Appropriately responding to a marine pollution event, especially hydrocarbon spills, often requires detailed knowledge of local habitat and environmental features. Access to high resolution habitat profiles can support effective spill response plans, informing discussions on protection priorities or expediated remediation. However, marine habitat composition data for a given area is often lacking due to the high cost and effort of conducting such surveys across the vast shorelines of Canada. The purpose of this study was to develop methodologies for conducting rapid and affordable habitat compositions in the marine environment via drone aerial photography; an emerging technology for conducting high resolution surveys. We used the Musquash Marine Protected Area (MPA; Musquash, NB, Canada) as a model system as it contains a diverse range of habitat types, is a region of conservation concern in Atlantic Canada, and is in close proximity to oil and gas handling facilities and vessel traffic. The MPA consists of a tidal river that outflows into the Bay of Fundy. Using Geographic Information System (GIS) software, we subdivided the MPA into several transects (N =61) that were used to generate flight plans for a Remotely Piloted Aircraft System (RPAS; DJI Mavic 3 Enterprise, DJI ). The RPAS was flown (6 m s-1) at an altitude of 100m (Above ground level) taking images with side (70%) and front (80%) overlap. Resulting images were then compiled as an orthomosaic map using Pix4Dmatic software. These data will be used to inform marine spill response planning in the region, to support marine planning and conservation, and Marine Protected Area (MPA) monitoring efforts as well as develop further methodological approaches for conducting RPAS-based habitat surveys in other coastal systems within Atlantic Canada. Cite this data as: Lawrence MJ, Coates PJ, Matheson K, Hamer A. Characterisation of intertidal habitat types in the Musquash Marine Protected Area using aerial drone photography. Published November 2025. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, St. Andrews, N.B.

In July and August of 2019, a remotely piloted aircraft system (RPAS) project was undertaken in Canada’s western Arctic along the Inuvik to Tuktoyaktuk (ITH) and Dempster highways. The objective of this project was to test long-range RPAS missions for photogrammetric data acquisition and processing of these two Arctic highway corridors with embankments, bridges and culverts at risk of changing environmental and climatic regimes. The imagery was used to derive an orthomosaic and digital elevation model that could be used to measure road infrastructure and landscape change over time (e.g., fish habitat). The RPAS missions were conducted with a Griffon SeaHunter and full-frame DSLR sensor and scoped to obtain <10 cm spatial resolution imagery along a combined 396 linear km. The final deliverables covered over 22,000 ha and 29,000 ha for the ITH and Dempster Highways, respectively, and represent one of the first non-military beyond-visual-line-of-sight RPAS data products of its kind and scale in Canada, and likely elsewhere. At the time of collection the data constituted the most current and detailed photo surveys of two of Canada’s most northern highways constructed over ice-rich permafrost terrain, and will provide a valuable baseline to study past and future landscape change.

The DND Air Weapons Range dataset is comprised of all the polygons that represent the Air Weapons Range established by the Department of National Defence, Government of Canada, within the Province of Alberta. Air Weapons Range is the area used as a practice and firing range with restricted access provisions and which is owned and operated by the Department of National Defence, Government of Canada.

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.

In 2010 the Earth Observation Team of the Science and Technology Branch (STB) at Agriculture and Agri-Food Canada (AAFC) continued the process of generating annual crop inventory digital maps using satellite imagery. Focusing on the Prairie Provinces, a Decision Tree (DT) based methodology was applied using both optical (AWiFS, Landsat-5, DMC) and radar (RADARSAT-2) based satellite imagery, and having a final spatial resolution of 56m. Methods were also developed to enhance the optical classification with RADARSAT-2 imagery, addressing issues associated with cloud cover. In conjunction with satellite acquisitions, ground-truth information was provided by provincial crop insurance companies and point observations from our regional AAFC colleagues. The overall process for Crop Inventory Map includes: satellite data acquisition; field data acquisition for classification training and accuracy assessment; and, operational implementation of the classification methodology.

In 2009 the Earth Observation Team of the Science and Technology Branch (STB) at Agriculture and Agri-Food Canada (AAFC) began the process of generating annual crop inventory digital maps using satellite imagery. Focusing on the Prairie Provinces, a Decision Tree (DT) based methodology was applied using both optical (AWiFS, Landsat-5) and radar (RADARSAT-2) based satellite imagery, and having a final spatial resolution of 56m. Methods were also developed to enhance the optical classification with RADARSAT-2 imagery, addressing issues associated with cloud cover. In conjunction with satellite acquisitions, ground-truth information was provided by provincial crop insurance companies and point observations from our regional AAFC colleagues. The overall process for Crop Inventory Map includes: satellite data acquisition; field data acquisition for classification training and accuracy assessment; and, operational implementation of the classification methodology.The initial methodology was developed in partnership with AAFC Research Branch, and supported in part by the Canadian Space Agency. The long-term objective of this endeavour is to expand from the Prairies and produce an annual crop inventory of the entire agricultural extent of Canada.

In 2018, the Earth Observation Team of the Science and Technology Branch (STB) at Agriculture and Agri-Food Canada (AAFC) repeated the process of generating annual crop inventory digital maps using satellite imagery to for all of Canada, in support of a national crop inventory. A Decision Tree (DT) based methodology was applied using optical (Landsat-8, Sentinel-2) and radar (RADARSAT-2) based satellite images, and having a final spatial resolution of 30m. In conjunction with satellite acquisitions, ground-truth information was provided by: provincial crop insurance companies in Alberta, Saskatchewan, Manitoba, & Quebec; point observations from the BC Ministry of Agriculture, & the Ontario Ministry of Agriculture, Food and Rural Affairs; and data collection supported by our regional AAFC Research and Development Centres in St. John’s, Kentville, Charlottetown, Fredericton, Guelph, and Summerland

These products are derived from RGB (red/green/blue) images, a satellite processing technique that uses a combination of satellite sensor bands (also called channels) and applies a red/green/blue (RGB) filter to each of them. The result is a false-color image, i.e. an image that does not correspond to what the human eye would see, but offers high contrast between different cloud types and surface features. The on-board sensor of a weather satellite obtains two basic types of information: visible light data (reflected light) reflecting off clouds and different surface types, also known as "reflectance", and infrared data (emitted radiation) which are short-wave and long-wave radiation emitted by clouds and surface features. RGBs are specially designed to combine this type of satellite data, resulting in an information-rich final product.Other products are based on the enhancement of channel data for a single wavelength, also aimed at highlighting meteorological features of the observed surface or clouds, but in a simpler way since only a single wavelength is involved. This older approach is still useful today, as its simplicity makes image interpretation easier in some cases.

This dataset provides polygon extents of the runway surfaces at airports, aerodromes and airstrips across the territory.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)

In 2012, the Earth Observation Team of the Science and Technology Branch (STB) at Agriculture and Agri-Food Canada (AAFC) repeated the process of generating annual crop inventory digital maps using satellite imagery to for all of Canada (except Newfoundland), in support of a national crop inventory. A Decision Tree (DT) based methodology was applied using optical (DMC, SPOT) and radar (RADARSAT-2) based satellite images, and having a final spatial resolution of 30m. In conjunction with satellite acquisitions, ground-truth information was provided by provincial crop insurance companies and point observations from our regional AAFC colleagues.