This dataset was developed to document the procedures for acquiring underwater images in the Banc-des-Américains Marine Protected Area (MPA). Its primary objective is to provide a comprehensive inventory of metadata linked to imagery campaigns that allowed us to conduct a basic characterization of the area, and now that are used for ecological monitoring of the benthic habitats within the MPA.Metadata were collected during imagery surveys conducted since 2012, using three main methods: drop cameras on the crest, baited drop stereoscopic cameras on both the crest and plains, and towed cameras on the plains. For each operation are shared the type of gear used, sampling method, date, geographic coordinates, and acquisition depth.The released dataset contains only descriptive information related to the acquisition of images : file identifier, location, sampling methodology, depth, and technical imaging parameters. It does not include image files themselves, visual content, or the results of image analyses.A systematic quality control is applied to ensure completeness and consistency of the metadata: field format standardization, validation of GPS coordinates, verification of dates and recorded depths. Clear instructions guide the recording of metadata to guarantee their reliability for management and scientific monitoring purposes.

Location of traffic cameras under the responsibility of the Ministry of Transport and Sustainable Mobility. These cameras are located at strategic locations on the road network to ensure the safety of road users. Each camera has a URL that allows you to view the video stream of images. The cameras available are those displayed on the interactive map of Quebec 511.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

This dataset is derived from analyses of photo samples obtained by deploying drop camera photo (DCP) systems conducted during various research surveys in coastal areas of the north shore of the St. Lawrence Estuary and the Gulf between Portneuf-sur-Mer and Sept-Îles between June and October of 2019 to 2022. It contains 4866 species occurrence data of 109 different taxa for epibenthic invertebrates and submerged aquatic vegetation (including algae) at depths ranging from 0 to more than 50 meters. Additional information about this dataset is available in the “Method step description” section.The research surveys were undertaken by the Department of Fisheries and Oceans Canada as part of the baseline program of the Ocean Protection Plan. This initiative aims to acquire environmental baseline data contributing to the characterization of important coastal areas and to support evidence-based assessments and management decisions for preserving marine ecosystems. Data acquired during the research surveys additionally include: 1) fish and invertebrate species occurrence data derived from analyses of video samples collected using a stereoscopic baited remote underwater camera video systems (stereo-BRUVs) 2) fish and invertebrates catch data from beam trawl sampling (occurrence and catch weights by species), 3) substrate classification based on drop camera samples, 4) oceanographic measurements of the water column from Seabird 19plus V2 profiling CTD (conductivity, temperature, depth, photosynthetic active radiation, pH, dissolved oxygen), 5) nutrients (NO2, NO3, NH4, PO4, SiO3) and dissolve organic carbon (DOC) concentrations, and 6) current speed and direction from tilt meters. The datasets of the first two elements will also be available as independent datasets on the OBIS/GBIF portal. To obtain data from items 3-6 and/or biological data collected on fish and invertebrate taxa, please contact David Lévesque or Marie-Julie Roux.The elaboration of conservation objectives based on an ecosystem assessment approach for fishery stock assessment requires the development of sampling methods to maximize the data collection on the ecosystem, while minimizing the impact on organisms and the marine environment. This project aims at characterising the coastal ecosystem of the St. Lawrence Estuary and Gulf between Portneuf-sur-Mer and Sept-Îles (QC), including the physico-chemistry of water, phytoplankton, zooplankton, submerged vegetation, benthic habitats as well as assemblages of fish and invertebrates. Sampling was performed by combining conventional methods such as CTD profiling, zooplankton nets, and beam trawl, with non-extractive methods such as drop camera photo (DCP) and stereoscopic baited remote underwater camera video systems (stereo-BRUVs). The data collected will help define baseline ecosystem conditions in the study area; explore the links between environmental conditions, habitat structure and biological assemblages; identify important habitats for marine species; as well as the evaluation of the performance of visual sampling methods compared to conventional methods. The results will make it possible to optimize the seasonal or annual monitoring in order to better understand the direct and indirect effects of human activities in coastal environments.Method Step Description: 1. Acquisition of photo samples in sequence: The drop camera photo (DCP) system used to sample underwater pictures is a stainless steel frame in the shape of a triangular prism of 50 cm wide, 100 cm long and 76 cm high at the level of the central eyelet. The sampling area is a quadrat of 0.25 m2 (interior dimensions of 50 cm by 50 cm). The system consists of two GoPro Hero 5 cameras (4000 × 3000 pixels) and two 8000 lumens dive lights (Big Blue VL8000). The first camera captures the elements located in the quadrat when viewed from above. The second camera offers an oblique view facilitating the evaluation of the elements present in the quadrat. At all sampling stations, five to nine system deployments (replicas) capturing photos every 10 seconds for 60 to 120 seconds were performed. Surveys took place between : June 28th to July 5th 2019July 13th to July 20th 2019September 30th to October 9th 2019August 10th to August 20th 2020October 1st to October 10th 2020April 22nd to May 5th 2021July 27th to August 10th 2021October 15th to October 24th 2021June 24th to Jully 5th 2022August 15th to August 26th 20222. Image analysis: A photo image analysis method with sequence (moving images) was used for the occurrence data extraction and organism counts; measurements were taken to obtain vegetation cover percentages and substrate analyzes were also carried out. Analyzes were performed with the open-source Fiji software from ImageJ. A quality/visibility rating was assigned to the analyzed image sequences. 3. Taxonomic approach: Epibenthic organisms were identified at the lowest possible taxonomic rank. A morphotype approach has been systematically used (during annotations) for the identification of sponges, hydrozoans and bryozoans, and occasionally for other organisms such as algae. Species codes were also used to distinguish certain species that could not be identified at the time of the annotations (see verbatim Identification). To eliminate observer bias, the same person analyzed all images used in this database. The organisms were identified from underwater images using a combination of identification guides and scientific papers.4. Open nomenclature: The concept of open nomenclature has been integrated into occurrence data to support taxonomic identifications with their level of certainty, as recommended by Horton et al., 2021. The abbreviation stet. (stetit) was used when the decision not to go lower was made but an identification might be possible, whereas indet (Indeterminabilis) was used when a lower level identification was considered uncertain or impossible (see identificationqualifier). In addition, the abbreviation Confer (cf.) was used and integrated into the data tables (see occurrenceRemarks) in order to link identifications that could potentially and/or possibly be associated.5. Remarks: Several remarks have also been incorporated (see organismRemarks, identificationRemarks and taxonRemarks), and are intended to provide additional information that may be useful to some data users; Please note that these sections could be modified or improved.6. Quality control: The taxonomic identifications were verified through a validation process, in collaboration with various expert taxonomists. All scientific names have been checked against the World Register of Marine Species (WoRMS) to match currently recognized standards. The WoRMS match was placed in the taxonID field of the instance file. Data quality control was performed using Robistools and worms packages. All sample locations were plotted on a map for visual verification that the latitude and longitude coordinates were within the described sample area.7. Data sharing: Only metadata and biodiversity occurrence data are shared in this dataset. The two files provided (DarwinCore format) are complementary and are linked by the "eventID" key. The "event" file includes generic event information, including date and location. The "occurrence" file includes the original identifiers of the observed organisms, identification comments and their taxonomy. A data dictionary is also provided to explain the fields used. For access to other data or images, contact David Lévesque.For more details about the project and the methodology, a technical report (Scallon-Chouinard et al., 2022) including sampling methods with drop camera photo systems (DCP) and stereoscopic baited remote underwater camera video systems (stereo-BRUVs) is currently available online (https://waves-vagues.dfo-mpo.gc.ca/library-bibliotheque/41081225.pdf); another technical report detailing photo and video image analysis methods will also be available.This project was funded by the Department of Fisheries and Oceans Canada as part of the baseline program of the Ocean Protection Plan.

Used within the Travellers Road Information Portal Interactive Map to convey transportation related information in both official languages. Camera images are available in real time on certain highways within Central, Eastern & West Ontario. This data is best viewed using Google Earth or similar Keyhole Markup Language (KML) compatible software. For instructions on how to use Google Earth, read the [Google Earth tutorial](http://www.google.com/earth/index.html) **.** This data set is now available via the Ontario 511 Developer API at *[KML]: Keyhole Markup Language

A list of the locations, web addresses and attributes regarding Ministry owned highway web cameras. Attributes include: *DriveBC camera page, image, image thumbnail, Replay-the-Day, camera identifier, highway number, highway description, name, caption, credit/extra information, compass orientation, location (latitude, longitude)*. **PLEASE NOTE:** The source URL for highway camera images has changed, which will cause previously used links to break. The dataset has been updated to reflect this change; some columns are no longer available as a result.

To help wildlife managers obtain information about CWD prevalence in the province, hunters are asked to drop off heads from deer, elk, moose, and caribou for CWD testing at the following locations (see map below). PLEASE NOTE: Each self-serve drop-off site contains a kiosk and a chest freezer. Freezer space at high-traffic drop-off locations may be limited early in the hunting season when temperatures are not consistently below -10C and therefore do not allow for heads to be submitted within the kiosk. Prior to dropping off large elk and moose heads at these busy sites, please call ahead to the phone number associated with each kiosk to ensure there is adequate freezer space to allow for drop-off.

In 2012 and 2013, Fisheries and Oceans Canada surveyed the benthos in two areas closed to bottom contact fishing, the Narwhal Overwintering and Coldwater Coral Zone (now the Disko Fan Conservation Area, DFCA), and the Hatton Basin Voluntary Coral Protection Zone (now the Hatton Basin Conservation Area, HBCA). Samples were collected following protocols recommended by the Arctic Council’s Circumpolar Biodiversity Monitoring Plan for the purposes of providing baseline data for future monitoring of benthic invertebrates in this sensitive region, and for facilitating pan-Arctic comparisons of benthic communities. Five biodiversity monitoring stations were established, four in the DFCA and one in the HBCA, each of which was fully sampled according to those protocols with Van Veen grabs or box corers, drop cameras and temperature recorders attached to the gear. This report summarises the grab/core-sampled benthic fauna collected during the 2012 survey of the Conservation Areas and complements another report documenting the epibenthos from the camera transects in the DFCA. Here we report on macrofauna in the 1-cm size fraction, and on foraminiferan meiofauna.The data provided is presented in the following report (see related link) :Jacobs, K., Bouchard Marmen, M., Rincón, B., MacDonald, B., Lirette, C., Gibb, O., Treble, M., and Kenchington, E. 2022. Biodiversity Monitoring Stations for Benthic Macrofauna and Meiofauna in the Disko Fan and Hatton Basin Conservation Areas. Can. Tech. Rep. Fish. Aquat. Sci. 3487: vi + 86 p.Cite this data as: Bouchard Marmen, Marieve; Rincon, Beatriz ; MacDonald, Barry; Lirette, Camille; Gibb, Olivia; Treble, Margaret ; Jacobs, Kevin; Kenchington, Ellen (2022). Biodiversity Monitoring Stations for Benthic Macrofauna and Meiofauna in the Disko Fan and Hatton Basin Conservation Areas. Published January 2023. Ocean Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/b7bcff18-698b-4d40-a7bd-13d39925cbeb

The bank of oblique photographs of Northern Quebec is composed of georeferenced photos taken on board planes or helicopters during flights carried out as part of the program for the acquisition of ecological knowledge in Northern Quebec as part of the economic, social and environmental development project “Plan Nord”. During these overflights, the personnel on board were equipped with high-resolution cameras connected to a satellite geolocation system (GPS). The photos obtained in this way served as control points to improve the various thematic maps. __Note:__ For the purposes of distributing this bank, the photos could be modified slightly in order to improve the shooting. Georeferencing photos on the map refers to the location of the plane or helicopter at the time the shot was taken. **This third party metadata element was translated using an automated translation tool (Amazon Translate).**

List and contact details of municipal ecocentres and drop-off points**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

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 long-wave radiations emitted by clouds and surface features. RGBs are specially designed to combine this type of satellite data, resulting in an information-rich final product. Four types of products are currently generated from the GOES-West and GOES-East satellites: "NightIR" and "NightMicrophysics", at 2km resolution, are generated 24 hours a day with infrared channels, so are visible both night and day, and "NaturalColour" and "DayCloudConvection", at 1km resolution, which combine visible light channels with infrared channels; their higher resolution makes the latter two products more popular, but they are not available during most of the night (between 02UTC and 07UTC for GOES-Est, and between 06UTC and 11UTC for GOES-Ouest) given the absence of reflected sunlight. Other RGB products should be added gradually in the future to meet different needs.