The Head Tax Permit Zone is comprised of three polygons for determining which zone a head tax permit falls in. These zones are used to apply the rental rate that forest grazing reserve permits, head tax permits (HTP), and provincial grazing reserves (GRR) are charged (Ministerial Order 01/2020).

This point layer dataset contains information on Manitoba waterbody access points including boat launches, overland routes and tunnels.Waterbody Entry Points contains point data primarily of boat launches in Manitoba, but it also includes overland routes and tunnel access to some waterbodies. Each data point has a description of the type of access as well as photos that detail signage and condition of the entry point. The waterbody entry points layer, along with related information, can be found at the Manitoba Lake Information For Anglers app. The project was initiated by Manitoba Wildlife and Fisheries Branch with funding from the Fish and Wildlife Enhancement Fund. Data is provided by Manitoba Wildlife and Fisheries Branch, Swan Valley Sport Fishing and Manitoba Watershed Districts. For additional information visit Manitoba Fisheries. The dataset includes the following fields (Alias (Name): Description) Waterbody ID (WATERBODY_ID): Unique identifier for an individual waterbody. Waterbody Name (WATERBODY_NAME): Name of the waterbody that the entry point belongs to. Entry Type (ENTRY_TYPE): Indicates the type of entry point (e.g. boat launch, tunnel). Photo 1 (PHOTO_1): Link to a photo of the launch/entry point. Photo 2 (PHOTO_2): Link to a photo of the launch/entry point. Photo 3 (PHOTO_3): Link to a photo of the launch/entry point. Long (DD) (LONG_DD): Longitudinal coordinates of the feature in decimal degrees. Lat (DD) (LAT_DD): Latitudinal coordinates of the feature in decimal degrees.

This dataset is a locational record of the meteorological input files publically available on Saskatchewan GeoHub that can be used with the Environmental Protection Agency approved Regulatory Model (AERMOD). Each file represents the meteorology over an area of the province while minimizing the influences of local terrain on air flow. Additional attribute information for each location includes coordinates and a link to download the AERMOD data as a zip file.The Air Quality Section of the Ministry of Environment uses air quality modelling to simulate how air pollutants disperse in the ambient atmosphere in order to help manage the air quality in the province. The models are used to estimate the impact of air pollutants emitted from emission sources, and are typically employed to determine whether existing or new proposed industrial facilities are or will be in compliance with the ambient air quality standards outlined in Table 20 of the province's Environmental Code, June 1, 2015 under The Environmental Management and Protection Act, 2010.  The information needed to run dispersion models consists primarily of emissions and meteorological data. Five years (2012-2016) of preprocessed meteorological datasets in an AERMOD ready format is publicly available. This file is contained in the downloadable zipped file. The zipped file contains five files: the SFC and PFL files are the AERMOD ready files required to run AERMOD (i.e., data, sensible heat flux, frictional velocity, potential temperature gradient, vertical velocity, mixing height, monin-obukhov length, surface roughness, Bowen ratio, albedo, scalar wind speed, wind direction, ambient temperature, precipitation, precipitation rate, relative humidity, surface pressure, and total cloud amounts); the DAT file contains the land use information (i.e., Surface roughness, Bowen ratio and albedo) chosen for each month in the SFC file; the KMZ file contains the wind rose for that location which can be used on Google Earth; and the PNG file contains various graphs of monthly or diurnal meteorological distribution (i.e., temperature, wind speed, daytime mixing heights and sensible heat flux, and stability) which can be used to help determine if that location is representative of the area proposed for modelling.  Please note: Since this data is newly developed, it is possible there may be issues with the data as it gets used in more applications. Ongoing changes, edits and updates may be made by the Air Quality Section of the Ministry of Environment. Is is recommended for any future modelling to download the latest version of the input files and not archive any input files on your own server for future use, unless this notification no longer exists. If there are any issues discovered with data in the zipped file, please contact Dennis Fudge at dennis.fudge@gov.sk.ca or at 306-519-7105. Your support will be greatly appreciated.  There may be times you feel that the input files are not representative of the proposed modelling domain due to the surrounding features (i.e., forest/agricultural or rural/urban) being different than those used to generate the input files. If that is the case, the modeler can generate the input modelling files themselves. The relevant files to generate these input files are available upon request. Please contact Dennis Fudge at dennis.fudge@gov.sk.ca or at 306-519-7105. 

Point feature layer showing locations of public schools in Manitoba that offer the French Immersion Program.Point feature layer showing locations of public schools in Manitoba that offer the French Immersion Program. This is an inclusive program intended for all students with various abilities and needs whose first language is not French. The goal of the Program is to develop proud, confident, engaged, plurilingual global citizens. For more information visit Manitoba Advanced Education, Skills and Immigration. Fields included (Alias (Field Name): Field description) SCHOOL_FR_NAME (SCHOOL_FR_NAME): Name of the school in French SCHOOL_EN_PHONE_NBR (SCHOOL_EN_PHONE_NBR): Phone number for the school SCHOOL_FR_PHONE_NBR (SCHOOL_FR_PHONE_NBR): Phone number for the school, in French format DIV_NAME (DIV_NAME): Name of the school division DIV_FR_NAME (DIV_FR_NAME): Name of the school division in French DIV_EN_PHONE_NBR (DIV_EN_PHONE_NBR): Phone number for the division DIV_FR_PHONE_NBR (DIV_FR_PHONE_NBR): Phone number for the division, in French format SCHOOL_ADDR_LINE1 (SCHOOL_ADDR_LINE1): Street address of school SCHOOL_ADDR_LINE2 (SCHOOL_ADDR_LINE2): Second line, if required, of street address SCHOOL_FR_ADDR_LINE1 (SCHOOL_FR_ADDR_LINE1): Street address of school in French SCHOOL_FR_ADDR_LINE2 (SCHOOL_FR_ADDR_LINE2): Second line, if required, of street address in French SCHOOL_CITY_NAME (SCHOOL_CITY_NAME): Name of the city or town that the school is located in SCHOOL_POSTAL_CODE (SCHOOL_POSTAL_CODE): Postal code of the school TRACKS (TRACKS): This field indicates the delivery model used by the school; either single track or dual track MIDDLE_IM (MIDDLE_IM): This field indicates whether the school has a grade 4 entry point LATE_IM (LATE_IM): This field indicates whether the school has a grade 6 or 7 entry point  SCHOOL_LOW_GRADE_ENG (SCHOOL_LOW_GRADE_ENG): The lowest grade offering the Program SCHOOL_LOW_GRADE_FR (SCHOOL_LOW_GRADE_FR): The lowest grade, in French, offering the Program SCHOOL_HIGH_GRADE (SCHOOL_HIGH_GRADE): The highest grade offering the Program GRADE_LIST_EN (GRADE_LIST_EN): Comma separated list of grades available in the Program GRADE_LIST_FR (GRADE_LIST_FR): Comma separated list of grades available in the Program, in French Latitude (Latitude): Latitudinal coordinate of the school Longitude (Longitude): Longitudinal coordinate of the school

644 datasets of Typical Meteorological Years (TMY) created by joining twelve Typical Meteorological Months selected from a database of up to 20 years of CWEEDS hourly data. The months are chosen by statistically comparing individual monthly means with long-term monthly means for daily total global solar irradiance, mean, minimum and maximum dry bulb temperature, mean, minimum and maximum dew point temperature, and mean and maximum wind speed. These hourly datasets are used by the engineering and scientific community mainly as inputs for solar system design and analysis and building energy systems analysis tools. This dataset has been updated with the most recent changes made in March 2023. The solar values in these files are based on 0.1° x 0.1° (11 km x 11 km grid) for all of Canada. Refer to Data Resources below for additional information on the TMY file format.

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.

Rural district (RD) polygons are a graphical representation of the rural district boundaries as defined in regulation 2022-45 under the Local Governance Act with an associated RD name attribute. Effective date is January 1, 2023.

A coastal surficial substrate layer for the coastal Scotian Shelf and Bay of Fundy. To create the layer, previous geological characterizations from NRCan were translated into consistent substrate and habitat characterizations; including surficial grain size and primary habitat type. In areas where no geological description was available, data including digital elevation models and substrate samples from NRCan, CHS and DFO Science were interpreted to produce a regional scale substrate and habitat characterization. Each characterization in the layer was given a ranking of confidence and original data resolution to ensure that decision makers are informed of the quality and scale of data that went into each interpretation.Cite this data as: Greenlaw, M., Harvey, C. Data of: A substrate classification for the Inshore Scotian Shelf and Bay of Fundy, Maritimes Region. Published: March 2022. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, St. Andrews, N.B. https://open.canada.ca/data/en/dataset/f2c493e4-ceaa-11eb-be59-1860247f53e3

Snow and ice are important hydrological resources. Their minimum spatial extent here referred to as annual minimum snow/ice (MSI) cover, plays a very important role as an indicator of long-term changes and baseline capacity for surface water storage. The MSI probability is derived from sequence of seventeen 10-day clear-sky composites corresponding to April, 1 to September, 20 warm period for each year since 2000. Data from Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra satellite for the period since 2000 have been processed with the special technology developed at the Canada Centre for Remote Sensing (CCRS) as described in Trishchenko, 2016; Trishchenko et al., 2016; 2009, 2006, Trishchenko and Ungureanu, 2021, Khlopenkov and Trishchenko, 2008, Luo et al., 2008. The presence of snow or ice is determined for each pixel of the image based on snow/ice scene identification procedure and the probability if computed for the entire warm season as a ratio of number of snow/ice flags to the total number of pixels available (less or equal to 17). The minimum snow and ice extent can be derived from the probability map by applying a certain threshold. New data version V5.0 replaces previous version V4.0 for all data available since 2000. All MSI files were reprocessed for all MODIS input data based on collection 6.1. The output format has not changed since previous version. It is described in Trishchenko (2024). The impact of input data change is small and can be detected only for time interval 2000-2015. Data starting 2016 has been already derived using MODIS collection 6.1 input.The differences between the MSI data based on MODIS Collection 5 (i.e. MSI V4) versus MODIS Collection 6.1 (i.e. MSI V5), on average, are quite small. The region-wide relative difference in the MSI extent varies from -3.97% to +1.75%. The mean value is -0.14%, the median value is 0.18% and standard deviation is 1.83%. As such, we do not expect any sizeable impact of the version change on our previous conclusions regarding trends and climate variations, except for refining the relative values of statistical parameters within the range of a few percents. References:TRISHCHENKO, A.P., 2024: Probability maps of the annual minimum snow and ice (MSI) presence over April,1 to September, 20 period since 2000 derived from MODIS 250m imagery over Canada and neighbouring regions. Data format description. CCRS, NRCan. 4pp.

This service shows the median household after-tax income in 2015 for Canada, by 2016 census subdivision. The data is from the Census Profile, Statistics Canada Catalogue no. 98-316-X2016001.After-tax income - refers to total income less income taxes of the statistical unit during a specified reference period (for additional information refer to Total Income – 2016 Census Dictionary and After-tax Income – 2016 Census Dictionary). The median income of a specified group is the amount that divides the income distribution of that group into two halves.Census subdivision (CSD) is the general term for municipalities (as determined by provincial/territorial legislation) or areas treated as municipal equivalents for statistical purposes (e.g., Indian reserves, Indian settlements and unorganized territories). Municipal status is defined by laws in effect in each province and territory in Canada.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.Besides the variable described here, the dataset contains the id, name, type, province, population, land area and the number of private households for each census subdivision.If a value is null, it could be because it is not available for a specific reference period, it is not applicable, it is too unreliable to be published or it is suppressed to meet confidentiality requirements of the Statistics Act. To find out the exact reason, refer to the source data from Census in the resources below.