The "AAFC Annual Unit Runoff in Canada - 2013" report aims to illustrate runoff trends across the country by calculating annual unit runoff for a variety of probabilities of exceedence commonly used by decision makers. Annual unit runoff is a measure of runoff volume per square kilometre. It includes a point data set for the hydrologic stations that were analyzed and seven sets of linework to show the adjusted isolines for 10%, 25%, 50%, 70%, 75%, 80%, and 90% probability of exceedence. It is an update and expansion of the work completed in the 1994 report "Annual Unit Runoff on the Canadian Prairies". For more information, visit: http://open.canada.ca/data/en/dataset/a905bafc-74b5-4ec5-b5f9-94b2e19815d0

Topographic data for lakes within the Qu'Appelle River Valley in central Saskatchewan. This data was collected in the fall of 2008 and consists of contour lines, shorelines, spot heights, and tile index. For more information, visit: http://open.canada.ca/data/en/dataset/d838afd0-8918-42e1-acdd-8c69f9b5a7e1

In 2016, 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, Sentinel-2, Gaofen-1) 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 in Alberta, Saskatchewan, Manitoba, and Quebec; point observations from the BC Ministry of Agriculture, and the Ontario Ministry of Agriculture, Food and Rural Affairs; and data collection supported by our regional AAFC Research and Development Centres in St. John's, Kentville, Charlottetown, Fredericton, Guelph, and Summerland. For more information, visit: http://open.canada.ca/data/en/dataset/b8e4da73-fb5f-4e6e-93a4-8b1f40d95b51

The "South Tobacco Creek Watershed - 10 cm Contours" dataset is a linear representation of the LiDAR DEM data set to the closest 0.1 meters. For more information, visit: http://open.canada.ca/data/en/dataset/734078a9-9aa1-44a1-9e74-dc9387a9ecfe

In 2010 the Earth Observation Team of the Science and Technology Branch (STB) at Agriculture and Agri-Food Canada (AAFC) continued the process of generating annual crop inventory digital maps using satellite imagery. Focusing on the Prairie Provinces, a Decision Tree (DT) based methodology was applied using both optical (AWiFS, Landsat-5, DMC) and radar (RADARSAT-2) based satellite imagery, and having a final spatial resolution of 56m. Methods were also developed to enhance the optical classification with RADARSAT-2 imagery, addressing issues associated with cloud cover. In conjunction with satellite acquisitions, ground-truth information was provided by provincial crop insurance companies and point observations from our regional AAFC colleagues. The overall process for Crop Inventory Map includes: satellite data acquisition; field data acquisition for classification training and accuracy assessment; and, operational implementation of the classification methodology. For more information, visit: http://open.canada.ca/data/en/dataset/6dc5170d-4167-47e4-b80a-93ed2b47f023

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

Topographic data for lakes within the Qu'Appelle River Valley in central Saskatchewan. This data was collected in the fall of 2008 and consists of contour lines, shorelines, spot heights, and tile index. For more information, visit: http://open.canada.ca/data/en/dataset/d838afd0-8918-42e1-acdd-8c69f9b5a7e1

In 2015, 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/3688e7d9-7520-42bd-a3eb-8854b685fef3

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. AAFC's National Agroclimate Information Service (NAIS) updates this dataset on a monthly basis, usually by the 10th of every month to correspond to the end of the previous month, and subsequent Canadian input into the larger North American Drought Monitor (NA-DM). For more information, visit: http://open.canada.ca/data/en/dataset/292646cd-619f-4200-afb1-8b2c52f984a2

The Agriculture and Agri-Food Canada's LiDAR Projects dataset was created from existing spatial data. It contains the footprints (outlines) of all the LiDAR data that is openly distributed by Agriculture and Agri-Food Canada. LiDAR (Light Detection And Ranging) is a method of acquiring survey points using optical remote sensing technology. The dataset indicates basic information about the location, source and properties of the data. For more information, visit: http://open.canada.ca/data/en/dataset/a760f9e0-7013-4187-9261-2e69b01edd9a