Landsat-derived forest age for Canada 2022Satellite-based forest age map for 2022 across Canada's forested ecozones at a 30-m spatial resolution, developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). Remotely sensed data from Landsat (disturbances, surface reflectance composites, forest structure) and MODIS (Gross Primary Production) are utilized to determine age. Age can be determined where disturbance can be identified directly (disturbance approach) or inferred using spectral information (recovery approach) or using inverted allometric equations to model age where there is no evidence of disturbance (allometric approach). The disturbance approach is based upon satellite data and mapped changes and is the most accurate. The recovery approach also avails upon satellite data plus logic regarding forest succession, with an accuracy that is greater than pure modeling. Given the lack of widespread recent disturbance over Canada's forests, the allometric approach is required over the greatest area (86.6%). Using information regarding realized heights and growth and yield modeling, ages are estimated where none are otherwise possible. Trees of all ages are mapped, with trees >150 years old combined in an - old tree - category.See Maltman et al. (2023) for an overview of the methods, data, image processing, as well as information on agreement assessment using Canada's National Inventory (NFI). Maltman, J.C., Hermosilla, T., Wulder, M.A., Coops, N.C., White, J.C., 2023. Estimating and mapping forest age across Canada's forested ecosystems. Remote Sensing of Environment 290, 113529. ( Maltman et al. 2023).

This dataset includes all MPMO projects at various stages in the review process, including those that are currently undergoing review and those that have completed a review.

Tick data collected by Geneticks and Mount Allison University, including test results for various types of pathogens. For instructions on how to view and search this dataset there are posted resources at https:/

High-resolution map of leading tree species distribution for Canada’s forested ecosystems (2019). Leading tree species map produced from a 2019 Landsat image composite, geographic and climate data, elevation derivatives, and remote sensing derived phenology following the framework described in Hermosilla et al. (2022). Regional classification models were generated based on Canada’s National Forest Inventory using a 150x150 km tiling system. The leading tree species are defined by representing the most voted tree species from the Random Forests classification models (i.e. the class with the highest class membership probability).The data represents leading tree species of Canada's forested ecosystems in 2019. An image compositing window of August 1 ± 30 days was used to generate the best-available-pixel (BAP) image composites utilized as source data for the classification.The science and methods developed to generate the information outcomes shown here, that track and characterize the history of Canada’s forests, were led by Canadian Forest Service of Natural Resources Canada, developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS), partnered with the University of British Columbia, augmented by processing capacity from Digital Research Alliance of Canada.For an overview on the data, image processing, and methods applied, as well as information on independent accuracy assessment of the data, see Hermosilla et al. (2022) https://doi.org/10.1016/j.rse.2022.113276When using this data, please cite as: Hermosilla, T., Bastyr, A., Coops, N.C., White, J.C., Wulder, M.A., 2022. Mapping the presence and distribution of tree species in Canada’s forested ecosystems. Remote Sensing of Environment 282, 113276.

A federal electoral district is an area represented by a member of the House of Commons. The Federal Electoral Districts (FED) dataset is a digital representation of the 338 electoral districts proclaimed by the Representation Order of 2013. This dataset is an update of the 2013 Federal Electoral Districts (FED) 2013.

Satellite-based forest area consistent with FAO definitions for Canada. It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). The forest area is based on the Food and Agricultural Organization of the United Nations (FAO) definition. The FAO definition incorporates land use, whereby trees removed by fire and harvesting for instance, remain forest as the trees will return. The included map displays the current forest cover for year as noted (i.e. 2022), plus the satellite-based temporally informed forest area where tree cover has been temporarily lost due to stand replacing disturbances (i.e., fire, harvest). For an overview of the methods, data, image processing, as well as information on accuracy assessment see Wulder et al. (2020).Open Access: Wulder, M.A., T. Hermosilla, G. Stinson, F.A. Gougeon, J.C. White, D.A. Hill, B.P. Smiley. (2020). Satellite-based time series land cover and change information to map forest area consistent with national and international reporting requirements. Forestry: An International Journal of Forest Research 93(3), 331-34, https://doi.org/10.1093/forestry/cpaa0063 . ( Wulder et al. 2020)

Since 1 March 2022, the Special Intervention Zones (ZIS) have been lifted. However, the territory flooded during the exceptional spring floods of 2017 and 2019, as illustrated in Annex 2 adjusted to Decree 814-2019, is considered by the Regulation concerning the provisional implementation of the amendments made by chapter 7 of the laws of 2021 on the management of risks related to floods (Transitional Regulation) as an area comparable to a low-current zone. The adjusted Annex 2 corresponds to the delimitation of the territory flooded during the spring floods of 2017 and 2019 in connection with the decree establishing the ZIS published on 15 July 2019, from which the portions of territory covered by the ministerial orders published on 30 December 2019 were subtracted.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Historical earthquakes recorded by Earthquakes Canada. This dataset contains the earthquakes recorded in decade 2010. However, the National Earthquake Database makes available seismic bulletin data from 1985 and onward. For a complete listing of current and historical earthquakes, visit https://www.earthquakescanada.nrcan.gc.ca/.

In 2019, 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) 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, & Quebec; point observations from the PEI Department of Environment, Water and Climate Change and data collection supported by our regional AAFC Research and Development Centres in St. John’s, Kentville, Charlottetown, Fredericton, and Guelph.

In July and August of 2019, a remotely piloted aircraft system (RPAS) project was undertaken in Canada’s western Arctic along the Inuvik to Tuktoyaktuk (ITH) and Dempster highways. The objective of this project was to test long-range RPAS missions for photogrammetric data acquisition and processing of these two Arctic highway corridors with embankments, bridges and culverts at risk of changing environmental and climatic regimes. The imagery was used to derive an orthomosaic and digital elevation model that could be used to measure road infrastructure and landscape change over time (e.g., fish habitat). The RPAS missions were conducted with a Griffon SeaHunter and full-frame DSLR sensor and scoped to obtain <10 cm spatial resolution imagery along a combined 396 linear km. The final deliverables covered over 22,000 ha and 29,000 ha for the ITH and Dempster Highways, respectively, and represent one of the first non-military beyond-visual-line-of-sight RPAS data products of its kind and scale in Canada, and likely elsewhere. At the time of collection the data constituted the most current and detailed photo surveys of two of Canada’s most northern highways constructed over ice-rich permafrost terrain, and will provide a valuable baseline to study past and future landscape change.