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This land cover data set was derived from the Advanced Very High Resolution Radiometer (AVHRR) sensor operating on board the United States National Oceanic and Atmospheric Administration (NOAA) satellites. Information on the NOAA series of satellites can be found at www.noaa.gov/satellites.html The vegetation and land cover information set has been classified into twelve categories. Information on the classification of the vegetation and land cover, raster to vector conversion, generalization for cartographic presentations is included in the paper "The Canada Vegetation and Land Cover: A Raster and Vector Data Set for GIS Applications - Uses in Agriculture" (https://geogratis.cgdi.gc.ca/download/landcover/scale/gis95ppr.pdf). A soil quality evaluation was obtained by cross-referencing the AVHRR information with Census of Agriculture records and biophysical (Soil Landscapes of Canada) data and is also included in the above paper.

The “Land Cover for Agricultural Regions of Canada, circa 2000” is a thematic land cover classification representative of Circa 2000 conditions for agricultural regions of Canada. Land cover is derived from Landsat5-TM and/or 7-ETM+ multi-spectral imagery by inputting imagery and ground reference training data into a Decision-Tree or Supervised image classification process. Object segmentation, pixel filtering, and/or post editing is applied as part of the image classification. Mapping is corrected to the GeoBase Data Alignment Layer.

This series of datasets has been created by AAFC’s National Agroclimate Information Service (NAIS) of the Agro-Climate, Geomatics and Earth Observations (ACGEO) Division of the Science and Technology Branch. The Canadian Drought Monitor (CDM) is a composite product developed from a wide assortment of information such as the Normalized Difference Vegetation Index (NDVI), streamflow values, Palmer Drought Index, and drought indicators used by the agriculture, forest and water management sectors. Drought prone regions are analyzed based on precipitation, temperature, drought model index maps, and climate data and are interpreted by federal, provincial and academic scientists. Once a consensus is reached, a monthly map showing drought designations for Canada is digitized.

LiDAR data collected in 2018 of water control structures in Tennaille, Newton, and Huff Lake in Saskatchewan, Canada. Includes Digital Terrain Models, Contours, and Orthorectified imagery.

LiDAR Data to be used by AAFC to assess whether additional land control should be pursued and other hydrological studies including potential dam break failure scenarios.

The ‘Land use allocation to Soils and Landforms by year’ dataset links agricultural land use activities to soils and landscapes within Soil Landscapes of Canada (SLC) polygons. The land use allocations to soils area datasets were generated on an annual time step (1971-2015). Agricultural land use is categorized and allocated based on the following general land use types: Annual cropland, Perennial cropland, Specialty Crops, Improved pasture and Unimproved Pasture.

The Manitoba Detailed Soil Survey dataset series at a scale of 1:100 000 consists of geo-referenced soil polygons with linkages to attribute data found in the associated Component File (CMP), Soil Names File (SNF) and Soil Layer File (SLF).

Together, these datasets describe the spatial distribution of soils and associated landscapes for nearly all agricultural areas in southern Manitoba, as well as some parts of northern and eastern Manitoba.

The “Prairie Agricultural Landscapes (PAL)” datasets identify areas of the agricultural portions of the Canadian Prairies with similar land and water resources, land use and farming practices. They are represented by vector polygons. Based on selected attributes from the Soil Landscapes of Canada (SLC) and the 1996 Census of Agriculture, the Prairies were classified into 13 (thirteen) classes of Land Practices Group and five (5) Major Land Practices Groups. Typical attributes used to define the Land Practice Groups include: land in pasture, land in summerfallow, crop mixture, farm size and the level of chemical and fertilizer inputs.

LiDAR Services International (LSI), a Calgary-based LiDAR company completed an airborne LiDAR survey for the Redberry Lake Biosphere Reserve (RLBR) and Agriculture and Agri-Foods Canada (AAFC) in October 2011. The project involved collection of LiDAR data for a 362.97 km2 block area, 252.77 km2 for Redberry Lake and 110.20 km2 for AAFC northwest of Saskatoon, SK.

Deliverables included:

• 1 m bare earth and full feature grids in 1 km x 1 km tiles (ASCII XYZ format)

• 1 m bare earth and full feature greyscale hillshades (GeoGeoTIF format)

• Classified LiDAR point clouds and ASCII extractor program (LAS v1.2 format)

The “Soil Landscapes of Canada (SLC) Version 3.2” dataset series provides a set of geo-referenced soil areas (polygons) that are linked to attribute data found in the associated Component Table (CMP), Component Rating Table (CRT), Soil Names Table (SNT), Soil Layer Table (SLT), Landscape Segmentation Table (LST), Landform Extent Table (LET), Landform Definition Table and Ecological Framework Table (EFT). Together, these datasets describe the spatial distribution of soils and associated landscapes for the agricultural areas of Canada. However, some provinces (Alberta, Nova Scotia, and Prince Edward Island) contain CMP, SNT and SLT data for the entire province (that is, beyond the agricultural areas). This version is complemented by the previous SLC version 2.2, which covers the entire country.

The Drought Impact Label dataset is used on all drought polygons from D1 to D4 to specify the longitude and magnitude of impacts. Impact labels are often used in association with the Drought Impact Line dataset. The impact labels are classified as follows:

S – Short-Term, typically less than 6 months. L – Long-Term, typically more than 6 months.