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

In 2014, 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 our regional AAFC colleagues. For more information, visit: http://open.canada.ca/data/en/dataset/ae61f47e-8bcb-47c1-b438-8081601fa8fe

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

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

The "Canada's First Fall Frost Normals (1981-2010)" dataset contains the Mean and Median First Fall Frost Julian day calculated from the ANUSPLIN gridded data set using the date range from January 1, 1981 - December 31, 2010. The dataset also includes the Mean and Median Frost Free Period (given as a count of calendar days). For the purposes of this dataset a Frost Free day is defined as a day where the minimum daily temperature is greater than 0.0 Celsius.For more information, visit: http://open.canada.ca/data/en/dataset/c293739c-4e16-4384-bff8-e3fdaddc5e5f