The “Municipal Solid Waste Biomass Inventory” dataset is a stand-alone product that provides information on the calculated amount of Municipal Solid Waste within each BIMAT grid cell that includes a population centre. Data was provided by National Research Council Canada, with estimates based on census data collected in 2016. This dataset was calculated using an area-weighted analysis between population centres across Canada, Municipal Solid Waste data and the Biomass Report Framework fishnet. It includes information for total residential municipal solid waste, total organic waste (food and yard) and total paper waste.

This data shows spatial density of lentil cultivation in Canada. Regions with higher calculated spatial densities represent agricultural regions of Canada in which Lentils lentils are more expected. Results are provided as rasters with numerical values for each pixel indicating the spatial density calculated for that location. Higher spatial density values represent higher likelihood to have Lentils lentils based on analysis of the 2009 to 2021 AAFC annual crop inventory data.

This data shows spatial density of Corn cultivation in Canada. Regions with higher calculated spatial densities represent agricultural regions of Canada in which Corn is more expected. Results are provided as rasters with numerical values for each pixel indicating the spatial density calculated for that location. Higher spatial density values represent higher likelihood to have Corn based on analysis of the 2009 to 2021 AAFC annual crop inventory data.

These products represent crop health indices derived from the Versatile Soil Moisture Budget (VSMB) model using crop specific coefficients and station based precipitation and temperature measurements to simulate crop growth. The VSMB model simulates soil moisture dynamics and water stress conditions based on water availability in the soil profile and simulated evapotranspiration during the crop growing season. Crop phenological stages, which are related to crop water use, are determined by a biometeorlogical time scale model (Robertson, 1968) for cool season crops (wheat, barley etc.) and a Crop Heat Unit (Brown and Bootsma, 1993) algorithm for warm season crops (corn and soybean etc.).

The Nova Scotia Department of Fisheries and Aquaculture is the lead regulatory of rockweed leasing and licensing. This file illustrates all the issued rockweed leases along the coast of Nova Scotia. Fisheries and Aquaculture also provides a Nova Scotia Aquaculture and Rockweed Map viewer at: https://fishaqua.maps.arcgis.com/apps/instant/media/index.html?appid=a7c3520e73894539afadf8602ee57ef1

This data shows spatial density of mustard cultivation in Canada. Regions with higher calculated spatial densities represent agricultural regions of Canada in which mustard is more expected. Results are provided as rasters with numerical values for each pixel indicating the spatial density calculated for that location. Higher spatial density values represent higher likelihood to have mustard based on analysis of the 2009 to 2021 AAFC annual crop inventory data.

This table contains information about 11 animal types associated with assigned cases in the Manitoba Animal Welfare Program. This table contains information about animal types, grouped into 11 categories, associated with assigned cases in the Manitoba Animal Welfare Program for each year, starting in 2016, to the most recent quarter. This data is populated by the Provincial Animal Welfare Database for the Manitoba Animal Welfare Program. It is displayed in the Manitoba Animal Welfare Program – Animal Types chart. The table is updated on a quarterly basis. Fields included [Alias (Field Name): Field description] SpeciesStatsGrouping (SpeciesStatsGrouping): Includes one of the possible 11 animal type groups associated with each assigned case (e.g., Avian, Bison, Bovine) Year (Year): Includes the year, beginning in 2016, to the current year (e.g., 2016, 2017, 2018) Month (Month): Includes the numeric value of all months in a calendar year (e.g., 1, 2, 3) Quarter (Quarter): Includes the numeric values of all quarters in a calendar year (e.g., 1, 2, 3, 4), where quarter 1 corresponds with January, February and March, quarter 2 corresponds with April, May and June, quarter 3 corresponds with July, August and September and quarter 4 corresponds with October, November and December YQ (YQ): Includes the year and quarter of the most recent 12 quarters (e.g., 2021 Q1, 2021 Q2 )

Gögin upplýsingar um strok og tjón sem hefur átt sér stað sjókvíeldi. Hægt er að sjá hvar strokið átti sér stað, hvenær og hverskonar fiskur strauk. Einnig er hægt að sjá hvort hjón var á búnaði eða gat á kví. Fyrir frekari upplýsingar er bent á að hafa samband við matvælastofnun.

In 2022, the Earth Observation Team of the Science and Technology Branch (STB) at Agriculture and Agri-Food Canada (AAFC) repeated the process of generating annual crop inventory digital maps using satellite imagery for all Canadian provinces, in support of a national crop inventory. New this year, a map of the agricultural regions in the Yukon Territory was also produced. A Decision Tree (DT) based methodology was applied using optical (Landsat-8, Landsat-9, Sentinel-2), and radar (RCM) based satellite images, and having a final spatial resolution of 30m. In conjunction with satellite acquisitions, ground-truth information was provided by: provincial crop insurance companies in Alberta, Saskatchewan, Manitoba, & Quebec; point observations from the PEI Department of Environment, Water and Climate Change; Ontario Ministry of Agriculture, Food and Rural Affairs; University of Guelph - Ridgetown campus; British Columbia Ministry of Agriculture; and data collection supported by our regional AAFC Research and Development Centres in St. John's, Kentville, Fredericton, Guelph, Summerland and Whitehorse.

This data shows spatial density of pulses cultivation in Canada. Regions with higher calculated spatial densities represent agricultural regions of Canada in which pulses are more expected. Results are provided as rasters with numerical values for each pixel indicating the spatial density calculated for that location. Higher spatial density values represent higher likelihood to have pulses based on analysis of the 2009 to 2021 AAFC annual crop inventory data. Pulses consist of the following specfic crops types from the AAFC annual crop inventory; Pulses, Beans, Black Beans, Cranberry Beans, Faba Beans, Great Northern Beans, Kidney Beans, Lima Beans, Pinto Beans, Navy Beans, Red Beans, White Beans, Other Beans, Lentils, Peas, Chick Peas, Field Peas, White Peas, Other Peas, and Other Pulse