This is the 5 year investment plan for Manitoba Highway and Infrastructure Capital Projects. This dataset will show all the proposed infrastructure projects for the next 5 years. This Feature layer is similar to the "Manitoba Capital Plans Project Status" and will be updated once a year.This dataset contains points showing the locations of the capital projects such as asphalt surface treatment, grading, bituminous rehabilitation, concrete reconstruction, culvert jacking, intersection improvement, structures improvement, traffic signal improvements, and traffic safety improvements. This dataset was created by digitizing high-resolution imagery of Manitoba road network, bridge sites, and culvert locations. The details of the capital projects are available as attributes of the dataset.Fields included (Alias (Field Name): Field description.)Hwy (Hwy): The highway number where the project is located.  Location Description (Location_Description): A detailed description of the project location. Project Distance in km (km): The physical length of the project Project Type (Project_Type): A particular category assigned to the project based on the nature of work. Investment Category : (Investment_Category): Category of future investment for the project. (Ex: Renewal, Economic Development, Connectivity and Innovation, Climate Resiliency)  Municipality Name (MUNI_NAME): The name of the municipality where the project is located. Department Program (Department_Program): The name of the MI department responsible for the project.This dataset is used in Manitoba Infrastructure Projects an interactive map that shows Manitoba infrastructure's new, approved, and continuing capital project locations.

This table contains data on food processing facilities in the province. This table, created by the Food Safety and Inspection Branch-Manitoba Agriculture, contains data on food processing facilities in the province. Fields included ( Alias (Field Name): Field description.) Site Address (Site_Address): Address of the facility. Facility Number (Facility_Number): Number assigned to the facility. Facility Name (Facility_Name): Registered name of the facility. Facility Type (Facility Type): Facilities’ permits issued are specific to the type of product manufactured.  Facility Category: The different permit categories include: Processed Products – Facilities with permits in this category include food operations that produce processed food products (ex: condiments, candy, snack food, other prepared food). Food Warehousing, Distribution and Repackaging – Facilities with permits in this category include operations that store and distribute food products and may conduct basic repackaging ex: bulk dry goods into smaller retail packages. Meat Processing – Facilities with permits in this category include operations that make various meat products ranging from raw meat cuts to products such as sausage and jerky. Also in this category are facilities that make products like smoked fish. Their permits only allow the products to be sold within Manitoba. Bottling – Facilities with permits in this category include water bottling plants, soft drink manufacturers, breweries, wineries, distilleries, juice manufacturers, ice making plants and other similar plants. Grain/Oil Seed Processing – Facilities with permits in this category include grain and seed cleaning and packaging facilities, flourmills, oil processors, etc. Abattoirs – Facilities with permits in this category are abattoirs that slaughter animals under the oversight of a government inspector to produce meat for sale within the province. Dairy Products Processing – Facilities with permits in this category process dairy products (ex: raw milk cheese). Program Area (Program_Area): Program area. Work Area (Work_Area): Work area. Community (Community): Community where the facility is located Area (Area): Area of the city where the facility is located.  Zone (Zone): Zone of the city where the facility is located. Region (Region): Name of the region where the facility is located. Legal Name (Legal_Name): Legal name of the facility. Lot (Lot): Lot where the facility is located. Block (Block): Block where the facility is located. Plot (Plot): Plot where the facility is located. Quadrant (Quadrant): Quadrant where the facility is located. Section (Section): Section where the facility is located. Township (Township): Township where the facility is located. Meridian (Meridian): Meridian where the facility is located. Site Unit Number (Site_Unit_Number): number of the unit where the facility is located. Site Street Number (Site_Street_Number): Street number where the facility is located. Site City (Site_City): City where the facility is located. Site Province (Site_Province): Province where the facility is located. Site Country (Site_Country): Country where the facility is located. Site Postal Code (Site_Postal_Code) : Postal code of the facility. Latitude (Latitude): north-south coordinates of the facility. Longitude (Longitude): east-west coordinates of the facility. Species Harvested (Species_Harvested): species being processed in each abattoir.

Geolocator view to be used with Manitoba items. Geolocator view to be used with Manitoba items. 

This table contains data on whole and partial condemnation and slaughtering from 2015 to 2022. This table contains data on whole and partial condemnation and slaughtering from 2015 to 2022. The data is also classified by its Slaughter Class: Cattle, Swine, Chiken,  Spent layer hens, Ducks, Geese, Rabbits, Spent Breeder hens, 5 kg and under, Bison, Elk, Goats, Horses, Lambs, Llama/Alpaca, Mature turkey, over 11 kg, over 5 but no more than 7 kg, over 7 but no more than 9 kg, over 9 but no more than 11 kg, Sheep, and Wild boars.Field Names (Field Alias): Field description.SlaughterFigureID (SlaughterFigureID): unique indexed number assigned to each record in the database. BodyPart (BodyPart): code for the different body parts affected in partial condemnations. CondemnationReasonCode (CondemnationReasonCode): code for all the different reasons for condemnation. CondemnationType (CondemnationType): This identifies whether the condemnations are either Whole or Partial. SlaughterYear (SlaughterYear): Year when the slaughter occurred. NumberSlaughtered (NumberSlaughtered): Total number of animals slaughtered during the indicated period of time. NumberCondemned (NumberCondemned): Total number of animals condemned (whole) or total  number of parts of animals condemned (partial) during the indicated period of time. SlaughterClass (SlaughterClass): Species or class of the animal or part of the animal condemned. Quarter (Quarter): Number of the quarter.                   - January to March – 1                     - April to June – 2                     - July to September – 3                     - October to December - 4 QuarterYear (Quarter/Year): Corresponding quarter and year.

This WebMap comprises of three layers , namely, HRDPA Observed Accumulated Precipitation - Past 1 day, 3 days and 7 days (feature layer) ; HRDPA SubBasin Precipitation Distribution - Past 1 day, 3 day, and 7 days (feature layer) and Supporting Layers (group layer) - Comprising of Main Cities, Nelson River Basin and Basin Boundaries (feature layers). HRDPA is ECCC’s high-resolution precipitation analysis, merging gauge, radar, and HRDPS model data. CaPA-HRDPA produces four analyses of 6 hour amounts per day, valid at synoptic hours (00, 06, 12 and 18 UTC) and two 24 hour analysis valid at 06 and 12 UTC. A preliminary production is started 1 hour after valid time and a final one is launched 7 hours later. This translates into a production of 12 analyses per day.

This polygon layer visualizes actual observed precipitation polygons (classed by amounts) from the HRDPA product, offering a clear map-based depiction of recent rainfall or snowfall distribution. Observation periods depicted are past 1 day, past 3 days and past 7 days. This polygon layer is generated by taking HRDPA’s gridded precipitation data (6h, 24h, or multi-day accumulations) and grouping them into precipitation ranges, then polygonizing. Each feature shows how much precipitation truly fell in that zone. This is essential for event verification against forecasts, analyzing localized extremes, and updating water resource or flood models with real observed input.

This polygon layer showcases ultra-fine (2.5 km) short-range precipitation forecasts from the High Resolution Deterministic Prediction System (HRDPS), a convection-permitting model by Environment and Climate Change Canada. It identifies local-scale rainfall or snowfall patterns up to 48 hours, supporting urban flood forecasting, severe weather response, and detailed water resource planning. Convection-Permitting: The HRDPS can explicitly resolve thunderstorms and other small-scale weather events by running at ~2.5 km. Short-Range Focus: Typically provides forecasts out to 36–48 hours, updated several times daily. Local Impact: Valuable for pinpointing high-impact precipitation in complex terrain or urban environments, aiding emergency managers and hydrologists in short-lead-time decisions. Nested Model: Receives lateral boundary conditions from RDPS, maintaining consistency with regional forecasts while refining detail in local domains.

This feature class represents Manitoba's Forest Management Unit (FMU) boundaries. Forest Management Units (FMU's) define a forested area with common forest conditions that are managed in a similar manner. Forest Sections are comprised of FMU's. Forest inventories within Forest Management Units are analysed to determine allowable harvest limits of softwood and hardwood tree species within each Forest Management Unit. Version 3: The southern portion of FMU 67 within the Highrock Forest Section has been adjusted to align with base features captured in 2009. Additionally, an 11 hectare portion of the Saskatchewan River Forest Section (FMU 59) has been added to the Highrock Forest Section. Version 4: The northern portion of FMU 68 along the Rail Haul within the Highrock Forest Section has been adjust so that the boundary falls within water only. Additionally, version 4 splits the 'White Zone' forest section (FMU 76) by ecozones, creating FMU 76 (Taiga Shield), FMU 77 (Southern Arctic), FMU 78 (Hudson Plain) and FMU 79 (Boreal Shield). Version 4 is dated February 8, 2013. Fields Included: OBJECTID: Sequential unique whole numbers that are automatically generated . MANAGEMENT_UNIT_NUMBER : Management Unit (MU) number . S ECTION : Forest section number . SECTION_NAME : Forest section name .

This application is created to allow public to access and apply for authorization under Section 14(4) of the Manitoba Water Resources Administration Act. This application allows public to access and apply for authorization under section 14(4) of Manitoba Water Resources Administration Act. The map within the application contains lines and polygons showing the locations of provincial waterways, such as drains, dikes, diversions, detention basins, floodways, dams and reservoirs. The datasets were created by digitizing high-resolution imagery of the water features and by digitizing the titled Water Control Work plans associated with the features for drains which have been designated as provincial waterways by Order-in-Council. Manitoba Municipal Boundaries and Manitoba Property Assessment information are also displayed on the map for reference purposes.

This polygon layer displays ensemble-based, medium-range precipitation forecasts from the Global Ensemble Prediction System (GEPS), offering a probabilistic view of future rainfall or snowfall over a 16‑day horizon. It aids in uncertainty analysis, risk assessment, and strategic resource planning. Ensemble Approach: GEPS runs multiple perturbed members of ECCC’s GEM model, capturing a range of atmospheric evolutions and yielding probability distributions for precipitation. Global Domain: Similar coverage to the GDPS but focuses on ensemble mean, spreads, and probabilities rather than a single deterministic outcome. Longer-Range Outlook: Extends up to 16 days, supporting risk-based planning for potential floods, extended rainfall events, or dryness. Data Utility: Allows decision-makers to weigh confidence levels in precipitation scenarios, vital for water management, agriculture, and emergency contingency strategies.