The National Ecological Framework for Canada's "Land Cover by Ecoprovince” dataset provides land cover information within the ecoprovince framework polygon. It provides landcover codes and their English and French language description as well as information about the percentage of the polygon that the component occupies.

The National Ecological Framework for Canada's "Land Cover by Ecoregion” dataset provides land cover information within the ecoregion framework polygon. It provides landcover codes and their English and French language description as well as information about the percentage of the polygon that the component occupies.

The National Ecological Framework for Canada's "Land Cover by Ecodistrict” dataset provides land cover information within the ecodistrict framework polygon. It provides landcover codes and their English and French language description as well as information about the percentage of the polygon that the component occupies.

The National Ecological Framework for Canada's "Land Cover by Ecozone” dataset provides land cover information within the ecozone framework polygon. It provides landcover codes and their English and French language description as well as information about the percentage of the polygon that the component occupies.

The current and most detailed version of the approved corporate provincial digital Biogeoclimatic Ecosystem Classification (BEC) Zone/Subzone/Variant/Phase map (version 13.1, July 8 2026). Use this version when performing GIS analysis regardless of scale. This mapping is deliberately extended across the ocean, lakes, glaciers, etc to facilitate intersection with a terrestrial landcover layer of your choice

The following dataset correspond to the 1 km agricultural mask from Statistics Canada’s Crop Condition Assessment Program (CCAP). The mask have been generated from the classes 110 to 199 of the 2015 Agriculture and Agri-Food Canada’s landcover classification. The selection was then generalized to a spatial resolution of 1 km. The 2015 mask was used from the 2015 to the 2018 growing seasons inclusively.

The following dataset correspond to the 230 m agricultural mask from Statistics Canada’s Crop Condition Assessment Program (CCAP). The mask have been generated from the classes 110 to 199 of the 2015 Agriculture and Agri-Food Canada’s landcover classification. The selection was then generalized to a spatial resolution of 230 m. The 2015 mask was used from the 2015 to the 2018 growing seasons inclusively.

Collection of Land Cover products for Canada as produced by Natural Resources Canada using Landsat satellite imagery. This collection of cartographic products offers classified Land Cover of Canada at a 30 metre scale, updated on a 5 year basis. - [Landcover of Canada 2010](https://open.canada.ca/data/en/dataset/c688b87f-e85f-4842-b0e1-a8f79ebf1133)- [Landcover of Canada 2015](https://open.canada.ca/data/en/dataset/4e615eae-b90c-420b-adee-2ca35896caf6)- [Landcover of Canada 2020](https://open.canada.ca/data/en/dataset/ee1580ab-a23d-4f86-a09b-79763677eb47)

This land cover data set was derived from the Advanced Very High Resolution Radiometer (AVHRR) sensor operating on board the United States National Oceanic and Atmospheric Administration (NOAA) satellites. Information on the NOAA series of satellites can be found at www.noaa.gov/satellites.html The vegetation and land cover information set has been classified into twelve categories. Information on the classification of the vegetation and land cover, raster to vector conversion, generalization for cartographic presentations is included in the paper "The Canada Vegetation and Land Cover: A Raster and Vector Data Set for GIS Applications - Uses in Agriculture" (https://geogratis.cgdi.gc.ca/download/landcover/scale/gis95ppr.pdf). A soil quality evaluation was obtained by cross-referencing the AVHRR information with Census of Agriculture records and biophysical (Soil Landscapes of Canada) data and is also included in the above paper. AVHRR Land Cover Data approximates a 1:2M scale and was done originally for Agriculture Canada. The projection used is Lambert Conformal Conic (LCC) 49/77 with origin at 49N 95W.

Data include a collection of annual land cover maps derived from MODIS 250 m spatial resolution remotely sensed imagery for the period 2000 to 2011. Processing of the time series was designed to reduce the occurrence of false change between maps. The method was based on change updating as described in Pouliot et al. (2011, 2013). Change detection accounted for both abrupt changes such as forest harvesting and more gradual changes such as recurrent insect defoliation. To determine the new label for a pixel identified as change, an evidential reasoning approach was used to combine spectral and contextual information. The 2005 MODIS land cover of Canada at 250 m spatial resolution described in Latifovic et al. (2012) was used as the base map. It contains 39 land cover classes, which for time series development was considered too detailed and was reduced to 25 and 19 class versions. The 19 class version corresponds to the North America Land Change Monitoring System (NALCMS) Level 2 legend as described in Latifovic et al. (2012). Accuracy assessment of time series is difficult due to the need to assess many maps. For areas of change in the time series accuracy was found to be 70% based on the 19 class thematic legend.This time series captures the spatial distribution of dominant land cover transitions. It is intended for use in modeling, development of remote sensing products such as leaf area index or land cover based albedo retrievals, and other exploratory analysis. It is not appropriate for use in any rigorous reporting or inventory assessments due to the accuracy of the land cover classification and uncertainty as to the capture of all relevant changes for an application.