Province du Manitoba
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Geolocator view to be used with Manitoba items. Geolocator view to be used with Manitoba items.
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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.
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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.
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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.
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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.
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This is the web experience created using ArcGIS Web Experience Builder to portray the dynamic precipitation maps derived using various weather model data published by the Environment Canada, National Oceanic and Atmospheric Administration and European Centre for Medium-Range Weather Forecasts. It contains various precipitation layers for each of the models depicting various forecast periods / observation periods. The underlying data is updated regularly as the data gets published by ECCC/NOAA/ECMWF as per the publishing frequency. Following are the forecast weather models depicted in this Web Experience : HRDPS Model (High Resolution Deterministic Prediction System - Continental) for 24 and 48 hours of forecast periods. Regional Ensemble Prediction System (REPS) for 72 hours of forecast period hour. Regional Deterministic Prediction System (RDPS) for 84 hours of forecast period hour. Global Deterministic Prediction System (GDPS) for 168 and 240 hours of forecast periods. Global Forecast System (GFS) for 168 hours of forecast period. Global Ensemble Prediction System (GEPS) for 384 hours of forecast period. European Centre for Medium-Range Weather Forecasts for 168 hours of forecast periodAnd following are the observed weather models depicted in this Web Experience :High Resolution Deterministic Precipitation Analysis (HRDPA) with observation periods of the past 1 day, 3 days and 7 days.Special Thanks to Environment and Climate Change Canada, NOAA’s National Centers for Environmental Prediction, European Centre for Medium-Range Weather Forecasts
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Canadas Managed Forests 2017 Albers Equal Area Canada's Managed Forests 2017 Albers Equal Area
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This polygon layer presents 7‑day and 10‑day accumulated precipitation forecasts from the Global Deterministic Prediction System (GDPS), aggregated by sub-basin. It is designed to help hydrologists, water resource managers, and emergency planners pinpoint watersheds facing higher rainfall or snowfall totals in the medium-to-long range, enabling proactive flood risk assessment, drought monitoring, and resource allocation. Developed by Environment and Climate Change Canada (ECCC), the GDPS is a global numerical weather prediction model running at approximately 15km resolution, updated twice daily (00Z and 12Z). This layer integrates 168-hour (7‑day) and 240-hour (10‑day) precipitation forecasts into sub-basin polygons, offering a comprehensive view of expected cumulative precipitation. By focusing on watershed boundaries, decision-makers can quickly gauge regional vulnerabilities to prolonged rainfall or snowfall events.Key highlights: Global Model Insight: Captures large-scale, multi-day weather systems (e.g., atmospheric rivers, persistent low-pressure systems). Sub-Basin Aggregation: Delivers averaged precip values per basin, simplifying hydrological analysis for flood or drought outlooks. Extended Outlook: Spanning from day 0 to day 10, covers both medium- and longer-term forecast horizons, essential for strategic planning and mitigation efforts. Typical Uses:Flood Forecasting – Identifying basins prone to heavy or prolonged precipitation. Water Resource Management – Adjusting reservoir release schedules or irrigation planning based on expected accumulations. Emergency Preparedness – Deploying resources or issuing advisories in vulnerable watersheds.
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This polygon layer provides medium-range (up to 10 days) accumulated precipitation forecasts from the Global Deterministic Prediction System (GDPS), a worldwide numerical weather model run by Environment and Climate Change Canada. It addresses broad-scale weather systems and supplies boundary conditions for nested regional models. Global Scope: The GDPS covers the entire planet at ~15 km resolution, projecting large-scale atmospheric developments over a 240-hour window. Coupled Model: Integrates atmospheric and oceanic interactions, improving forecast accuracy for cyclones, frontal systems, and long-traveling storm patterns. Operational Backbone: Frequently used as a reference for regional or local models (e.g., RDPS) and for medium-range planning in water resource management or agriculture. Forecast Frequency: Runs twice daily, producing deterministic outputs that guide meteorologists, hydrologists, and emergency preparedness teams.
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This polygon layer represents accumulated precipitation forecasts from the Global Forecast System (GFS), a global numerical weather prediction model operated by NOAA/NCEP. It provides global medium‑range precipitation forecasts, as a 168‑hour (7‑day) accumulation, to support a wide range of weather and hydrological applications. This polygon layer is generated by extracting the accumulated precipitation field from Global Forecast System (GFS) GRIB2 files. The raw data are converted into a TIF raster, then resampled, smoothed, and classified into discrete precipitation ranges. The resulting polygon features depict forecasted precipitation accumulations over a 7‑day (168‑hour) period, allowing users to monitor expected rainfall and snowfall patterns on a global scale.
Arctic SDI catalogue