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We have found 46 datasets for the keyword "83". You can continue exploring the search results in the list below.
Datasets: 106,578
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46 Datasets, Page 1 of 5
UTM (Universal Transverse Mercator) 100 KM Grid
Many geometrical schemes - or map projections - are used to represent the curved surface of the Earth on map sheets. Canada uses the **Universal Transverse Mercator** (UTM) system. It is called transverse because the strips run north-south rather than east-west along the equator.This data class shows a 100 km x 100 km grid coordinate system based on the UTM projection using the North American Datum 83 (NAD83). It includes: * Military Grid Reference * Atlas identifier
UTM (Universal Transverse Mercator) 5 Km Grid
Many geometrical schemes - or map projections - are used to represent the curved surface of the Earth on map sheets. Canada uses the **Universal Transverse Mercator** (UTM) system. It is called transverse because the strips run north-south rather than east-west along the equator. This data class shows a 5 km x 5 km grid coordinate system based on the UTM projection using the North American Datum 83 (NAD83). It includes a UTM Map Sheet Number.
BCGS 1:2,500 Mapsheet Grid - NAD 83
BCGS 1:2,500 scale grid, North Amercian Datum 1983. The British Columbia Geographic System is a geographic system in which the coverage in minutes and seconds of longitude is double the coverage in minutes and seconds of latitude for sheets at all scales
Ratio of children and seniors to working-age population (0 to 14 and 65 and over versus 15 to 64) by census subdivision, 2016
This service shows the ratio of persons aged 0 to 14 and 65 and over (children and seniors) versus persons aged 15 to 64 (working-age) by census subdivision. The data is a custom extraction from the 2016 Census - 100% data.This data pertains to the total population by age. 'Age' refers to the age at last birthday before the reference date, that is, before May 10, 2016. For additional information refer to 'Age' in the 2016 Census Dictionary.For additional information refer to 'Age' in the 2016 Census Dictionary.To have a cartographic representation of the ecumene with this socio-economic indicator, it is recommended to add as the first layer, the “NRCan - 2016 population ecumene by census subdivision” web service, accessible in the data resources section below.
Ratio of children and seniors to working-age population (0 to 14 and 65 and over versus 15 to 64) by census division, 2016
This service shows the ratio of persons aged 0 to 14 and 65 and over (children and seniors) versus persons aged 15 to 64 (working-age) by census division. The data is a custom extraction from the 2016 Census - 100% data.This data pertains to the total population by age. 'Age' refers to the age at last birthday before the reference date, that is, before May 10, 2016. For additional information refer to 'Age' in the 2016 Census Dictionary.For additional information refer to 'Age' in the 2016 Census Dictionary.To have a cartographic representation of the ecumene with this socio-economic indicator, it is recommended to add as the first layer, the “NRCan - 2016 population ecumene by census division” web service, accessible in the data resources section below.
GNSS data
The GNSS (Global Navigation Satellite System), or satellite positioning system, includes all satellite navigation systems. It allows you to know your location, anywhere in the country.Theoretical GNSS specifications estimate the accuracy of the position obtained from a receiver to be approximately 15 meters in planimetry and 25 meters in altimetry. By combining the data with that of another receiver placed on a known geodesic point, the accuracy of the obtained position can vary from a few centimeters to a few meters, depending on the type of receiver used.In order to increase accuracy, the Government of Quebec records data continuously through a network of 18 GNSS stations. These stations are located on geodetic points that are free of any obstacles and capture data from the GPS and GLONASS constellations. Some of these stations receive signals from the Galileo constellation.This data is available in the standard exchange format*Receiver Independent Exchange Format* (RINEX), version 2.11. This format is recognized by the majority of GNSS data processing software.The data is accessible on the __ [ftp server] (ftp://ftp.mrn.gouv.qc.ca/Public/GPS)__) of the MRNF or using the __ [Interactive Map] (https://geodesie.portailcartographique.gouv.qc.ca/)__) of the geodetic network. It should be noted that only data from the last 366 days is kept.The structure of the directories and files on the __ [ftp server] (ftp://ftp.mrn.gouv.qc.ca/Public/GPS)__) as well as the coordinates of the stations are presented in the document __ [GNSS sensor stations] (https://diffusion.mern.gouv.qc.ca/diffusion/RGQ/Documentation/Geodesie/Stations_GNSS.pdf)__.# #État GNSS stations##You can consult the status of the stations in the document __ [Status of GNSS stations] (https://diffusion.mern.gouv.qc.ca/diffusion/RGQ/Documentation/Geodesie/État_Stations_GNSS.pdf)__. You will be notified if a station is in service, out of service, or if equipment maintenance is planned.# #GNSS in real time by cell phoneThe government also offers GNSS data by cellular telephone, which allows centimetric positioning work to be carried out in real time. Users of georeferenced data can thus, with a single multi-frequency GNSS receiver equipped with a modem by cellular telephone, identify or implement any physical detail with an accuracy of a few centimeters in the NAD 83 reference system (SCRS) (period 1997.0).The signal that contains this data is available to everyone. The range depends on telephone coverage, ionospheric conditions and especially on the instruments used. For more information on using GNSS in real time, see document __ [Guidelines for GNSS RTK/RTN Surveys in Canada] (http://publications.gc.ca/site/fra/9.822883/publication.html)__.# #Détails techniquesThe transmission of GNSS data as well as the station's NAD 83 (SCRS) coordinates (period 1997.0) is transmitted by cellular telephony from an IP address on the Internet. Each station transmits its data in one of the following two formats: CMR+ or RTCM V3.2. The document __ [GNSS capture stations] (https://diffusion.mern.gouv.qc.ca/diffusion/RGQ/Documentation/Geodesie/Stations_GNSS.pdf)__) gives for each city the IP address of the CMR+ or RTCM V3.2 formats as well as the antenna model. It should be noted that the data is not broadcast according to the*Networked Transport of RTCM protocol via Internet Protocol* (NTRIP).**This third party metadata element was translated using an automated translation tool (Amazon Translate).**
Forest Elevation (Ht) Standard Deviation (2022)
This dataset provides wall-to-wall maps of forest structure across Canada's 650 million hectare forested ecosystems for the year 2022, generated at a spatial resolution of 30 m. It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). Structure estimates include key attributes such as canopy height, canopy cover, and aboveground biomass, derived using a combination of airborne lidar and Landsat-based spectral composites. Structure models were trained using the - lidar-plot framework - (Wulder et al. 2012), which integrates co-located airborne lidar data and ground plot measurements with Landsat time-series composites (Hermosilla et al. 2016). A Nearest Neighbour imputation approach was applied to estimate structural attributes across the full extent of Canada's forested area. These nationally consistent products are intended to support strategic-level forest monitoring and assessment and are not designed for operational forest management.For further details on the methods, accuracy assessment, and source data, see Matasci et al. (2018).Matasci, G., Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., Hobart, G.W., Bolton, D.K., Tompalski, P., Bater, C.W., 2018. Three decades of forest structural dynamics over Canada's forested ecosystems using Landsat time-series and lidar plots. Remote Sensing of Environment, 216, 697-714. https://doi.org/10.1016/j.rse.2018.07.024 (Matasci et al. 2018)
VRI - 2025 - Forest Vegetation Composite Rank 1 Layer (R1)
Geospatial forest inventory dataset updated for depletions, such as harvesting, and projected annually for growth. Sample attributes in this dataset include: age, species, volume, height. The Vegetation Resources Inventory (VRI) spatial datasets describe both where a vegetation resource (ie timber volume, tree species) is located and how much of a given resource is within an inventory unit. Suggested citation: Forest Analysis and Inventory Branch (2024). VRI - 2024 - Forest Vegetation Composite Rank 1 Layer (R1). British Columbia Data Catalogue. https://catalogue.data.gov.bc.ca/dataset/2ebb35d8-c82f-4a17-9c96-612ac3532d55
Annual Maximum and Minimum Instantaneous Water Level or Flow
The annual maximum and minimum instantaneous data are the maximum and minimum instantaneous values for a given year.
Bay of Fundy Sea Scallop Meat Weight and Shell Height Data 2011 to 2023
This dataset represents meat weight and shell height data of commercial size Sea Scallop (Placopecten magellanicus; ≥ 80 mm shell height) from 2011-2023 from the Bay of Fundy Inshore Scallop Survey collected from June to mid-August. Wet meat weights were recorded to a tenth of a gram and shell heights are measured in millimeters. Meat weights and shell heights are sampled from a subset of scallops caught on survey and this detailed sampling is conducted from approximately half of the tows conducted. Each row in the dataset represents an individual scallop and contains information such as tow number, tow date, cruise name, geographical coordinates (decimal degrees, WGS 84) and the Scallop Production Area in which the tow took place. Survey protocols are documented in Glass (2017). This dataset contains tow data from a comparative survey conducted in 2012 (Smith et al., 2013). Further, these data correspond to the publication of Hebert et al. (2025).ReferencesGlass, A. 2017. Maritimes Region Inshore Scallop Assessment Survey: Detailed Technical Description. Can. Tech. Rep. Fish. Aquat. Sci. 3231: v + 32 p.Hebert, N, Sameoto, J.A., Keith, D.M., Murphy, O.A., Brown, C.J., Flemming, J. 2025. Interannual variability in the length–weight relationship can disrupt the abundance–biomass correlation of sea scallop (Placopecten magellanicus). ICES. J. Mar. Sci. Smith, S.J., Glass, A., Sameoto. J., Hubley, B., Reeves, A., and Nasmith, L. 2013. Comparative survey between Digby and Miracle drag gear for scallop surveys in the Bay of Fundy. DFO Can. Sci. Advis. Sec. Res. Doc. 2012/161. iv + 20 p.Cite this data as: Sameoto, J.A. Data of: Bay of Fundy Sea Scallop Meat Weight and Shell Height Data 2011 to 2023. Published: December 2025. Population Ecology Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/65d32794-2d81-4682-b0ea-8d8bbe907a58
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