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.

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.

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.

The basking shark (Cetorhinus maximus), is a species found in Atlantic Canadian waters which is mostly encountered “basking” on the surface waters and sometimes caught accidentally in commercial fisheries. One Pop-up Satellite Archival Tag (PSAT Mk10) from Wildlife Computers was applied to a single female basking shark in September 2008 on a commercial vessel to collect data on depth (pressure), temperature and ambient light level (for position estimation). The basking shark was 610 cm Total Length (curved). The tag released on the pre-programmed date 125 days after deployment. Raw data transmitted from the PSAT’s after release was processed through Wildlife Computers software (GPE3) to get summary files, assuming a maximum swimming speed of 2m/s, NOAA OI SST V2 High Resolution data set for SST reference and ETOPO1-Bedrock dataset for bathymetry reference. The maximum likelihood position estimates are available in .csv and .kmz format and depth and temperature profiles are also in .csv format. Other tag outputs as well as metadata from the deployment can be obtained upon request from: warren.joyce@dfo-mpo.gc.ca or heather.bowlby@dfo-mpo.gc.ca.

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.

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 2013, 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) 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 the BC Ministry of Agriculture and our regional AAFC colleagues.

PURPOSE:Provide early detection of newly arrived Aquatic Invasive Species (AIS) and determine the spread, establishment and spatial distribution of existing AIS within marine waters of the southern Gulf of St. Lawrence (sGSL), DFO Gulf Region boundaries (northern and eastern coastal shores of NB, Gulf shore of NS, and PEI shoreline).DESCRIPTION:DFO Science monitors for AIS in the Gulf Region. The data collected from DFO's biofouling monitoring program provides an overview of the distribution and abundance of Aquatic Invasive Species (AIS) in the Gulf Region. This information can be used by the general public, scientists and DFO managers.Monitoring program targeting aquatic invasive species (AIS). Native biofouling species are not included in this dataset. Botrylloides violaceus: Violet tunicateBotryllus schlosseri: Golden star tunicateCiona intestinalis: Vase tunicateStyela clava: Clubbed tunicateCaprella mutica*: Japanese skeleton shrimpMembranipora membranacea: Coffin box bryozoanCarcinus maenas*: European green crabCodium fragile*: Oyster thief algaJuxtacribrilina mutabilis**: Ribbed bryozoan (JCM)*indicates species that are not included as percent cover as they are not accurately captured by the sampling method, but are included as detections.**indicates species was only integrated fully into the monitoring protocol starting in 2025.Included here is a dataset of detection and percent cover data of AIS, as well as a monitoring station dataset. Environmental data collected, including from temperature loggers, are stored but not included here. PARAMETERS COLLECTED:Air and water temperature, salinity, depth, dissolved oxygen, weather conditions, list of biofouling AIS, percent cover of AIS on PVC plates, and incidental detection of other species and AIS in surrounding area. Only species data is pushed to the Open Data platform.NOTES ON QUALITY CONTROL:Each sample and species is processed and identified in a standardized fashion using standardized DFO Science AIS protocols and taxonomic references. Data is manually entered into DFO Gulf Region's AIS Science biofouling database and randomly verified for accuracy.SAMPLING METHODS:Biofouling monitoring is conducted using PVC collector plates that are deployed in the water column approximately 1 meter below the sea surface in the spring of each year. Biofouling organisms settle on these plates which are collected in the fall of the same year. Abundances of AIS are given as percent plate cover. Physico-chemical data including temperature, conductivity, and depth as well as weather conditions are noted at each geo-referenced biofouling monitoring site during initial deployment and at time of retrieval. All biofouling organisms settled on the underside of the PVC plates are noted and percent cover of each AIS is estimated. Any AIS present at the location is also noted. A HOBO temperature and light logger was deployed.USE LIMITATION:To ensure scientific integrity and appropriate use of the data, we would encourage you to contact the data custodian.