The 2010 AAFC Land Use is a culmination and curated metaanalysis of several high-quality spatial datasets produced between 1990 and 2021 using a variety of methods by teams of researchers as techniques and capabilities have evolved. The information from the input datasets was consolidated and embedded within each 30m x 30m pixel to create consolidated pixel histories, resulting in thousands of unique combinations of evidence ready for careful consideration. Informed by many sources of high-quality evidence and visual observation of imagery in Google Earth, we apply an incremental strategy to develop a coherent best current understanding of what has happened in each pixel through the time series.

The “Soils of Canada, Derived” national scale thematic datasets display the distribution and areal extent of soil attributes such as drainage, texture of parent material, kind of material, and classification of soils in terms of provincial Detailed Soil Surveys (DDS) polygons, Soil Landscape Polygons (SLCs), Soil Order and Great Group. The relief and associated slopes of the Canadian landscape are depicted on the local surface form thematic dataset. The purpose of the “Soils of Canada, Derived” series is to facilitate the cartographic display and basic queries of the Soil Landscapes of Canada at a national scale. For more detailed or sophisticated analysis, users should investigate the full “Soil Landscapes of Canada” product.

Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM+) sensors were used to generate the circa 2010 Mosaic of Canada at 30 m spatial resolution. All scenes were processed to Standard Terrain Correction Level 1T by the United States Geological Survey (USGS). Further processing performed by the Canada Centre for Remote Sensing included conversion of sensor measurements to top of atmosphere reflectance, cloud and cloud shadow detection, re-projection, selection of best measurements, mosaic generation ,noise removal and quality control. To provide a clear sky measurement for each location in Canada, data from the years 2009, 2010, and 2011 were used, but 2010 was preferentially selected. Bands 3 (0.63-0.69 µm), 4 (0.76-0.90 µm), 5 (1.55-1.75 µm), and 7 (2.08-2.35 µm) are provided in this version as significant atmosphere effects strongly limit the quality of the blue (0.45-0.52 µm) and green (0.52-0.60 µm) bands. Multi-criteria compositing was used for the selection of the most representative pixel. For ETM+ onboard Landsat 7 a scan line malfunction caused missing lines of data in all scenes collected after May 2003. Atmosphere and target variability between scenes cause these lines to have significant radiometric differences in some cases. A Fourier transformation approach was applied to correct this occurrence. This mosaic was developed for land cover and biophysical mapping applications across Canada. Other applications of these data are also possible, but should consider the temporal and spectral limitations of the product. Research to enhance the spatial, spectral and temporal aspects are in development for future versions of moderate resolution products from historical Landsat sensors, Landsat 8, and Sentinel 2 data.

Each pixel value corresponds to the mean historical “Best-quality” Max-NDVI value for a given week, as calculated from the previous 20 years in the MODIS historical record (i.e. does not include data from the current year). These data are also often referred to as “weekly baselines” or “weekly normals”.

CHS offers 500-metre bathymetric gridded data for users interested in the topography of the seafloor. This data provides seafloor depth in metres and is accessible for download as predefined areas.

McElhanney Consulting Services Ltd (MCSL) has performed a LiDAR and Imagery survey in southern Saskatchewan. The acquisition was completed between the 16th and 25th of October, 2009. The survey consisted of approximately 790 square kilometers of coverage. While collecting the LiDAR data, we also acquired aerial photo in RGB and NIR modes consisting of 1649 frames each.

This dataset includes the extent of the boreal forest as well as the extent of managed boreal forest worldwide. The extent of boreal forest was produced from Brandt et al. (2013) and a modified version of Goudilin (1987). Managed forest was defined as suggested by IPCC (2003) using data from FAFS (2009), Gauthier et al. (2014), See et al. (2015) and AICC maps. The extent of managed forest mostly includes areas managed for wood production, areas protected from large-scale disturbances as well as formal protected areas. Both boreal forest extent and managed boreal forest extent are available in raster and vector data. Please cite this data product as: Boucher, D., D.G. Schepaschenko, S. Gauthier, P. Bernier, T. Kuuluvainen, A. Z. Shvidenko. 2024. World boreal forest and managed boreal forest extent. DOI: 10.23687/88d70716-2600-4995-8d5f-86f96e383abf These data were presented in the following article: Gauthier, S., P. Bernier, T. Kuuluvainen, A. Z. Shvidenko, D. G. Schepaschenko. 2015. Boreal forest health and global change. Science 349:819-822. DOI: 10.1126/science.aaa9092 References: J. P. Brandt, M. D. Flannigan, D. G. Maynard, I. D. Thompson, W. J. A. Volney, Environ. Rev. 21, 207–226 (2013) I. S. Goudilin, Landscape map of the USSR. Legend to the landscape map of the USSR. Scale 1:2 500 000. Moscow, Ministry of Geology of the USSR (1987) [in Russian]. Inter-governmental panel on climate change (IPCC). J. Penman, M. Gytarsky, T. Hiraishi, T. Krug, D. Kruger, et al., Eds., Good practice guidance for land use, land-use change and forestry (IPCC/NGGIP/IGES, Kanawaga, 2003) Federal Agency of Forest Service (FAFS), Forest Fund of the Russian Federation (state by 1 January 2009) (Federal Agency of Forest Service, Moscow, 2009) [in Russian] S. Gauthier et al., Environ. Rev. 22, 256–285 (2014). See et al., Harnessing the power of volunteers, the internet and Google Earth to collect and validate global spatial information using Geo-Wiki. Technological Forecasting and Social Change. (2015). doi:10.1016/j.techfore.2015.03.002 Alaska Interagency Coordination Center (AICC). Fire Information. https://fire.ak.blm.gov/content/maps/aicc/Large%20Maps/Alaska_Fire_Management_Options.pdf (the version of 2014 was used)

The 1 cm resolution digital surface model (DSM) was created from unmanned aerial vehicle (UAV) imagery acquired from a single day survey, July 28th 2016, in Cambridge Bay, Nunavut. Five control points taken from a Global Differential Positioning System were positioned in the corners and the center of the vegetation survey. The DSM covering 525m2 was produced by Canada Centre for Remote Sensing /Canada Centre for Mapping and Earth Observation. The UAV survey was completed in collaboration with the Canadian High Arctic Research Station (CHARS) for northern vegetation monitoring research. For more information, refer to our current Arctic vegetation research: Fraser et al; "UAV photogrammetry for mapping vegetation in the low-Arctic" Arctic Science, 2016, 2(3): 79-102. http://www.nrcresearchpress.com/doi/abs/10.1139/AS-2016-0008

The 1 cm resolution vegetation digital height model was extracted using a bare earth model and digital surface model (DSM) derived from unmanned aerial vehicle (UAV) imagery acquired from a single day survey on July 28th 2016, in Cambridge Bay, Nunavut. The mapping product covers 525m2 and was produced by Canada Centre for Remote Sensing /Canada Centre for Mapping and Earth Observation. The UAV survey was completed in collaboration with the Canadian High Arctic Research Station (CHARS) for northern vegetation monitoring research. For more information, refer to our current Arctic vegetation research: Fraser et al; "UAV photogrammetry for mapping vegetation in the low-Arctic" Arctic Science, 2016, 2(3): 79-102. http://www.nrcresearchpress.com/doi/abs/10.1139/AS-2016-0008