This data shows spatial density of Wheat cultivation in Canada. Regions with higher calculated spatial densities represent agricultural regions of Canada in which Wheat 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 Wheat based on analysis of the 2009 to 2015 AAFC annual crop inventory data. For more information, visit: http://open.canada.ca/data/en/dataset/a9e958ab-94db-484b-9a6e-7ec74f6b5a25

This data shows spatial density of Canola cultivation in Canada. Regions with higher calculated spatial densities represent agricultural regions of Canada in which Canola 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 Canola based on analysis of the 2009 to 2015 AAFC annual crop inventory data. For more information, visit: http://open.canada.ca/data/en/dataset/a1da661a-55b6-4ef5-936a-fb1b6f4fa486

This data series represents the volumetric soil moisture (percent saturated soil) for the surface layer, expressed as a difference from the long term average. The average is calculated from all available years for each location and each time period, based on the length of the satellite data record. Values higher than zero represent areas that are wetter than the long term average, and areas lower than zero represent areas drier than the long term average. The data is created daily and is averaged for the ISO standard week and month. The data is produced from passive microwave satellite data collected by the Soil Moisture and Ocean Salinity (SMOS) satellite and converted to soil moisture using version 6.20 of the SMOS soil moisture processor. The data are produced by the European Space Agency and obtained under a Category 1 proposal for Level 2 soil moisture data. The data are gridded to a resolution of 0.25 degrees. Data quality flags have been applied to remove areas where rainfall is present during the acquisition, where snow cover is detected and when Radio Frequency Interference (RFI) is above an acceptable threshold. For more information, visit:http://open.canada.ca/data/en/dataset/723bbb4c-d209-4599-b39b-0ede5a0a0371

The Census of Agriculture is disseminated by Statistics Canada's standard geographic units (boundaries). Since these census units do not reflect or correspond with biophysical landscape units (such as ecological regions, soil landscapes or drainage areas), Agriculture and Agri-Food Canada, in collaboration with Statistics Canada's Agriculture Division, have developed a process for interpolating (reallocating or proportioning) Census of Agriculture information from census polygon-based units to biophysical polygon-based units. In the "Interpolated census of agriculture", suppression confidentiality procedures were applied by Statistics Canada to the custom tabulations to prevent the possibility of associating statistical data with any specific identifiable agricultural operation or individual. Confidentiality flags are denoted where "-1" appears in data cell. This indicates information has been suppressed by Statistics Canada to protect confidentiality. Null values/cells simply indicate no data is reported. For more information, visit: http://open.canada.ca/data/en/dataset/1dee8513-5c73-43b6-9446-25f7b985cd00

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. For more information, visit: http://open.canada.ca/data/en/dataset/c12645b7-4f70-4c37-808d-0b1ff3bd0051

In 2013, 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 to for all of Canada, in support of a national crop inventory. A Decision Tree (DT) based methodology was applied using optical (Landsat-8) and radar (RADARSAT-2) 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 and point observations from the BC Ministry of Agriculture and our regional AAFC colleagues. For more information, visit: http://open.canada.ca/data/en/dataset/4b1d45b0-5bfe-4c6d-bcd3-96c9d821ad3b

In 2012, 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 to for all of Canada (except Newfoundland), in support of a national crop inventory. A Decision Tree (DT) based methodology was applied using optical (DMC, SPOT) and radar (Radarsat-2) 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 and point observations from our regional AAFC colleagues. For more information, visit: http://open.canada.ca/data/en/dataset/621bb298-116f-4931-8350-741855b007bc

In 2011, the Earth Observation Team of the Science and Technology Branch (STB) at Agriculture and Agri-Food Canada (AAFC) expanded the process of generating annual crop inventory digital maps using satellite imagery to include British Columbia, Ontario, Quebec, and the Maritime provinces, in support of a national crop inventory. A Decision Tree (DT) based methodology was applied using optical (Landsat-5, DMC) and radar (RADARSAT-2) 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 and point observations from our regional AAFC colleagues.For more information, visit: http://open.canada.ca/data/en/dataset/58ca7629-4f6d-465a-88eb-ad7fd3a847e3

Contour Lines generated from LiDAR data captured by McElhanney Consulting Services Ltd (MCSL). The contour lines connect points of equal elevation for the landscape covered by this project. For more information, visit: http://open.canada.ca/data/en/dataset/9bdc1a9c-baf7-4eb0-a532-c1057b284b8f

The AAFC Infrastructure Flood Mapping in Saskatchewan - 50 centimetres is the LiDAR contours with an interval of 0.5m of the capture area of Saskatchewan. The contours were modeled from the ground class at a maximum vertical distance of 0.5m and a horizontal distance of 20 m. Breaklines were not used around water features therefore a uniform height of water bodies is not necessarily present if overlapping data was collected on different days. Major contours were defined every 5m and minor contours every 0.5 m. For more information, visit: http://open.canada.ca/data/en/dataset/4e964f96-1821-4214-9247-1faacda5af9c