Accumulated Precipitation represents the amount of total precipitation in mm (solid and/or liquid) which has been recorded over a given period of time. Products are produced for the following timeframes: Agricultural Year, Growing Season, Winter Season, as well as rolling products for 7, 14, 30, 60, 90, 180, 270, 365, 730, 1095, 1460 and 1825 days.

This feature delineates enhanced vegetation, forest and cover attributes for the Whitehorse, Yukon area at a scale of 1:10,000. The field work for the inventory was carried out during the winter of 2004/2005 with the project delivered by the contractor in October 2005. Delineation was based on 1:10,000 black and white photography acquired by the City of Whitehorse in 2001. New mapping and DTM were available for this project based on that photography. Vegetation inventory polygons contain a variety of detailed information on, for example, the age and type of trees growing on the land base in the vicinity of Whitehorse.Distributed from [GeoYukon](https://yukon.ca/geoyukon) by the [Government of Yukon](https://yukon.ca/maps) . Discover more digital map data and interactive maps from Yukon's digital map data collection.For more information: [geomatics.help@yukon.ca](mailto:geomatics.help@yukon.ca)

In 2020, 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) 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, Manitoba, & Quebec; point observations from the PEI Department of Environment, Water and Climate Change; 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, Charlottetown, Fredericton, and Guelph. Due to COVID-19 travel restrictions, complete sampling coverages in NL, NS, NB and BC were not possible, as a result the general agriculture class (120) is found in these provinces in areas where there was no ground data collected.

Five meter contour intervals derived from the Whitehorse Inventory data capture. The field work for the inventory was carried out during the winter of 2004/2005 with the project delivered by the contractor in October 2005. Delineation was based on 1:10,000 black and white photography acquired by the City of Whitehorse in 2001. Mapping and DTM were available for this project based on the 2001 photography.Distributed from [GeoYukon](https://yukon.ca/geoyukon) by the [Government of Yukon](https://yukon.ca/maps) . Discover more digital map data and interactive maps from Yukon's digital map data collection.For more information: [geomatics.help@yukon.ca](mailto:geomatics.help@yukon.ca)

In 2009 the Earth Observation Team of the Science and Technology Branch (STB) at Agriculture and Agri-Food Canada (AAFC) began 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) 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.The initial methodology was developed in partnership with AAFC Research Branch, and supported in part by the Canadian Space Agency. The long-term objective of this endeavour is to expand from the Prairies and produce an annual crop inventory of the entire agricultural extent of Canada.

The joint Natural Resources Canada/Department of Fisheries and Oceans Marine Spatial Planning Program requires the highest resolution marine based bathymetric elevation data and adjacent land based topographic elevation data that are available. This digital elevation model of Canada's west coast compiles the best data available from multiple government agencies to create a regional model gridded at 10 meter spacing. The transitions between the marine and terrestrial areas are seamless creating a continuous surface of elevations for scientific research and mapping.

The National Ecological Framework for Canada's "Elevation by Ecoprovince” dataset provides elevation information for ecoprovince framework polygons, in meters. It includes codes and descriptions for minimum elevation, maximum elevation, mean elevation and the difference in elevation.

Seasonal and annual multi-model ensembles of projected change (also known as anomalies) in snow depth based on an ensemble of twenty-eight Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models are available for 1900-2100. Projected change in snow depth is with respect to the reference period of 1986-2005 and expressed as a percentage (%). The 5th, 25th, 50th, 75th and 95th percentiles of the ensemble of snow depth change are available for the historical time period, 1900-2005, and for emission scenarios, RCP2.6, RCP4.5 and RCP8.5, for 2006-2100. Twenty-year average changes in snow depth (%) for four time periods (2021-2040; 2041-2060; 2061-2080; 2081-2100), with respect to the reference period of 1986-2005, for RCP2.6, RCP4.5 and RCP8.5 are also available in a range of formats. The median projected change across the ensemble of CMIP5 climate models is provided. Note: Projections among climate models can vary because of differences in their underlying representation of earth system processes. Thus, the use of a multi-model ensemble approach has been demonstrated in recent scientific literature to likely provide better projected climate change information.

Elevation - Elevation derived product. For example such as Canvec Contours, NWT NTDB Contours, Spot Elevations and MVAP Contours

Level curves with an equidistance of 1 m derived from a lidar survey conducted in 2015.attributes:ID - Unique identifierSubtype - Master (1) or secondary (2) level curve SCORE - Elevation value (m) The product High Resolution Digital Elevation Model (MNEHR) is available on the Open Government website.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**