In the "Weekly Best-Quality Maximum-NDVI anomalies" dataset series, each pixel value corresponds to the difference (anomaly) between the mean n-year "Best-Quality" Max-NDVI of the week specified (e.g. Week 18, 2000-2014) and the "Best-Quality" Max-NDVI of the same week in a specific year (e.g. Week 18, 2014). Max-NDVI anomalies < 0 indicate where weekly Max-NDVI is lower than normal. Anomalies > 0 indicate where weekly Max-NDVI is higher than normal. Anomalies close to 0 indicate where weekly Max-NDVI is similar to normal. For more information, visit: http://open.canada.ca/data/en/dataset/ea6b4be2-9826-47f3-a387-33ddf02592f4

The Grain Elevators in Canada dataset maps the list of grain elevators in Canada as provided by the Canadian Grain Commission (CGC). The elevators have been located as much as possible to an actual location rather than generalizing to the station name centroid. Additionally car spot information from CN, CP and the grain companies has been added where this has been published. This dataset attempts to provide a temporal and geographical extent of the grain elevators in Canada. For more information, visit: www.agr.gc.ca/atlas/metadata/5e0b5778-80cd-4697-8b84-23b4a814c1ae

The 2010 Land Use (LU) map covers all areas of Canada south of 60oN at a spatial resolution of 30 metres. The LU classes follow the protocol of the Intergovernmental Panel on Climate Change (IPCC) and consist of: Forest, Water, Cropland, Grassland, Settlement and Otherland. The 2010 Land Use (LU) map was developed in response to a need for explicit, high-accuracy, high-resolution land use data to meet AAFC's commitments in international reporting.For more information, visit: http://open.canada.ca/data/en/dataset/9e1efe92-e5a3-4f70-b313-68fb1283eadf

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 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 2015 AAFC annual crop inventory data. For more information, visit: http://open.canada.ca/data/en/dataset/92f73de5-5f46-4a8c-bc5f-c3872f268ecb

The 2000 Land Use (LU) map covers all areas of Canada south of 60oN at a spatial resolution of 30 metres. The LU classes follow the protocol of the Intergovernmental Panel on Climate Change (IPCC) and consist of: Forest, Water, Cropland, Grassland, Settlement and Otherland. The 2000 Land Use (LU) map was developed in response to a need for explicit, high-accuracy, high-resolution land use data to meet AAFC's commitments in international reporting.For more information, visit: http://open.canada.ca/data/en/dataset/b5f413d9-9acc-4ad7-b9a7-38486ed5fee7

This data shows spatial density of Soybean cultivation in Canada. Regions with higher calculated spatial densities represent agricultural regions of Canada in which Soybeans 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 Soybeans based on analysis of the 2009 to 2015 AAFC annual crop inventory data. For more information, visit: http://open.canada.ca/data/en/dataset/7c444a60-3b82-48d9-a197-efdff0154aaf

The Canadian Drought Monitor (CDM) brings together Agriculture and Agri-Food Canada's drought monitoring capabilities and collaboration with external agencies (federal and provincial) to produce, through analysis and consolidation of multiple indices and indicators, an easily understood comprehensive national drought severity map and report each month. The monitor provides specific details on agricultural impacts of the current drought situation, including statistics on land area, cattle, and the number of producers impacted. The Canadian Drought Monitors are based on a five class system ranking the severity of the drought condition. The Monitor map identifies general drought areas, labelling droughts by intensity, with D1 being the least intense and D4 being the most intense. The classifications are as follows: D0 (Abnormally Dry) - represents an event that occurs once every 3-5 years; D1 (Moderate Drought) - represents an event that occurs every 5-10 years; D2 (Severe Drought) - represents an event that occurs every 10-20 years; D3 (Extreme Drought) - represents an event that occurs every 20-25 years; and D4 (Exceptional Drought) - represents an event that occurs every 50 years. D0 is not recognized as a drought classification; however, it provides a warning of areas that are currently vulnerable to drought or areas that are recovering from drought. For more information visit: https://open.canada.ca/data/en/dataset/292646cd-619f-4200-afb1-8b2c52f984a2

These datasets show the areas where major crops can be expected within the agricultural regions of Canada. Results are provided as rasters with numerical values for each pixel indicating the level of spatial density calculated for a specific crop type in that location. Regions with higher spatial density for a certain crop have higher likelihood to have the same crop based on the previous years mapped crop inventories. For more information, visit: http://open.canada.ca/data/en/dataset/fdf82539-5a74-440b-86ef-a16b7801c706

This data shows spatial density of Cereals cultivation in Canada. Regions with higher calculated spatial densities represent agricultural regions of Canada in which Cereals 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 Cereals based on analysis of the 2009 to 2015 AAFC annual crop inventory data.For more information, visit: http://open.canada.ca/data/en/dataset/e0df876e-f56f-4797-8a7d-758e23bfa2b8