"Vegetation Zones of Canada: a Biogeoclimatic Perspective" maps Canadian geography in relation to gradients of regional climate, as expressed by potential vegetation on zonal sites. Compared to previous similar national-scale products, "Vegetation Zones of Canada" benefits from the work of provincial and territorial ecological classification programs over the last 30+ years, incorporating this regional knowledge of ecologically significant climatic gradients into a harmonized national map. This new map, reflecting vegetation and soils adapted to climates prior to approximately 1960, can serve as a broad-scale (approximately 1:5 M to 1:10 M) geospatial reference for monitoring and modeling effects of climate changes on Canadian ecosystems. "Vegetation Zones of Canada: a Biogeoclimatic Perspective" employs a two-level hierarchical legend. Level 1 vegetation zones reflect the global-scale latitudinal gradient of annual net radiation, as well as the effects of high elevation and west to east climatic and biogeographic variation across Canada. Within the level 1 vegetation zones, level 2 zones distinguish finer scale variation in zonal vegetation, especially in response to elevational and arctic climatic gradients, climate-related floristics and physiognomic diversity in the Great Plains, and maritime climatic influences on the east and west coasts. Thirty-three level 2 vegetation zones are recognized: High Arctic Sparse Tundra Mid-Arctic Dwarf Shrub Tundra Low Arctic Shrub Tundra Subarctic Alpine Tundra Western Boreal Alpine Tundra Cordilleran Alpine Tundra Pacific Alpine Tundra Eastern Alpine Tundra Subarctic Woodland-Tundra Northern Boreal Woodland Northwestern Boreal Forest West-Central Boreal Forest Eastern Boreal Forest Atlantic Maritime Heathland Pacific Maritime Rainforest Pacific Dry Forest Pacific Montane Forest Cordilleran Subboreal Forest Cordilleran Montane Forest Cordilleran Rainforest Cordilleran Dry Forest Eastern Temperate Mixed Forest Eastern Temperate Deciduous Forest Acadian Temperate Forest Rocky Mountains Foothills Parkland Great Plains Parkland Intermontane Shrub-Steppe Rocky Mountains Foothills Fescue Grassland Great Plains Fescue Grassland Great Plains Mixedgrass Grassland Central Tallgrass Grassland Cypress Hills GlaciersPlease cite this dataset as: Baldwin, K.; Allen, L.; Basquill, S.; Chapman, K.; Downing, D.; Flynn, N.; MacKenzie, W.; Major, M.; Meades, W.; Meidinger, D.; Morneau, C.; Saucier, J-P.; Thorpe, J.; Uhlig, P. 2019. Vegetation Zones of Canada: a Biogeoclimatic Perspective. [Map] Scale 1:5,000,000. Natural Resources Canada, Canadian Forest Service. Great Lake Forestry Center, Sault Ste. Marie, ON, Canada.

Digital terrain models offer a representation of the relief south of the 52nd parallel, in the form of an elevation matrix. This matrix makes it possible to visualize the territory in perspective and to perform three-dimensional spatial analyses, using appropriate software.A module specialized in three-dimensional data processing, such as 3D Analyst or Spatial Analyst, is required to visualize the digital altitude model in three dimensions.This digital altitude model (10-meter pixel matrix) is obtained by processing altimeter data (level curves and elevation points) from ** [topographic databases on a scale of 1/20,000] (https://www.donneesquebec.ca/recherche/fr/dataset/cartes-topographiques-a-l-echelle-de-1-20-000) **.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

The land use and development plan puts forward a frame of reference aimed at better knowing, protecting and promoting heritage. The data available in this set mainly comes from the mapping in section 2.3 of the Land Use and Development Plan of the Agglomération de Montréal, i.e. the __built or archaeological heritage__, the __emblematic and identity landscapes__, as well as the __views of interest__.This urban planning and development plan for the agglomeration of Montreal outlines the main parameters that will guide the Montreal agglomeration council in decisions relating to land use planning in the coming years. From a perspective of sustainable development, this document guides decisions that shape the territory in order to promote compact and greener neighborhoods, increase public and active transportation, support the economic dynamism of the agglomeration and highlight areas of interest.Consult the [interactive map] (https://montreal.ca/services/cartes-interactives-amenagement-du-territoire) of the Planning and Development Plan to visualize the thematic data.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

A direction one looks from a viewpoint towards a visual landscape. When a view is panoramic, it is to the middle of that panoramic view

Level curves with an equidistance of 1 m derived from a lidar survey conducted in 2024.attributes:ID - Unique IDSubtype - Master (1) or secondary (2) level curve SCORE - Elevation value (m) The High Resolution Digital Elevation Model (m) product The High Resolution Digital Elevation Model (HRDM) product is available on the Open Government website.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

This dataset contain the 1:20,000 scale contour elevation text converted from the Provincial Digital Base Mapping Project. These contours require the use of elevation text to properly interpret the elevation value of a specific contour. There are two major types of contours, index contours and intermediate contours. Index contours are identified every 5th contour line. For Alberta, the index contour intervals occur every 50 metres in relatively flat terrain and every 100 metres in mountainous terrain. Intermediate contours are contour lines that occur between the index contours. For Alberta, the intermediate contour intervals are every 10 metres in relatively flat terrain and every 20 metres in mountainous terrain. Where elevation change is sudden, intermediate contours may be deleted and only index contours are shown. The elevation text is associated with the index contours. Currently, no contour information exists for Banff, Jasper and Wood Buffalo National Parks and also for the extreme north east portion of the province. See the Completeness Report in this metadata record for details regarding coverage.

Province-wide SDE spatial view displaying dam locations. The public view displays a subset of the attribute data

The data layer (.shp) presented is the result of an unsupervised classification method for classifying seafloor habitat on German Bank (off South West Nova Scotia, Canada). This method involves separating environmental variables derived from multibeam bathymetry (Slope, Curvature) and backscatter (principal components: Q1, Q2, and Q3) into spatial units (i.e. pixels) and classifying the acoustically separated units into 5 habitat classes (Reef, Glacial Till, Silt, Silt with Bedforms, and Sand with Bedforms) using in situ data (imagery). Benthoscape classes (synonymous to landscape classifications in terrestrial ecology) describe the geomorphology and biology of the seafloor and are derived from elements of the seafloor that were acoustically distinguishable.Unsupervised classifications (acoustic classifications) optimized at 15 classes using Idrisi CLUSTER method (pixel based)Number representing the benthoscape classes (CLASS) derived from in situ imagery and video (See Brown et al., 2012, Figure 3, Table 1).Benthoscape classes (See Brown et al., 2012, Figure 3).Reference:Brown, C. J., Sameoto, J. A., & Smith, S. J. (2012). Multiple methods, maps, and management applications: Purpose made seafloor maps in support of ocean management. Journal of Sea Research, 72, 1–13. https://doi.org/10.1016/j.seares.2012.04.009Cite this data as: Brown, C. J., Sameoto, J. A., & Smith, S. J. Data of: Benthoscape Map of German Bank. Published: February 2021. Population Ecology Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/b7f81d4a-2cb6-4393-b35b-e536ec63e834

The purpose of this feature layer is to provide the 2009 overland flooding boundary in the Red River Valley.This dataset shows the extent of peak overland flooding in the Red River Valley in 20 09 . Data is based on RADARSAT – 1 satellite imagery. During processing, the raw data set was resampled to 12.5 meter pixel resolution, then classified using PCI Geomatica software which is a specialized software designed to manipulate space born imagery. The final output depicting the flooding boundary is available as a TIFF or Shapefile. Launched in November 1995, RADARSAT-1 was a Canadian-led project which provided useful information to both commercial and scientific users in such fields as disaster management, agriculture, cartography, hydrology, forestry, oceanography, ice studies and coastal monitoring. Equipped with a powerful synthetic aperture radar (SAR) instrument, it acquired images of the Earth day or night, in all weather and through cloud cover, smoke and haze. As of March 2013, the satellite was declared non-operational and is no longer collecting data. Many applications were developed to take advantage of RADARSAT-1 capacity for detecting the presence of water. These included monitoring flooding and the build-up of river ice, and mapping the melting of snow-covered areas. When used for flood monitoring, RADARSAT-1 data helped assess the impact of flooding, predicted the extent and duration of floodwaters, analyzed the environmental impact of water diversion projects, and developed flood mitigation measures. Fields Included:FID : Internal feature numberNAME : Flooded area nameAREA_SQKM : Size of flooded area

Forest Elevation(Ht) Mean 2015Mean height of lidar first returns (m). Represents the mean canopy height. It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). Products relating the structure of Canada's forested ecosystems have been generated and made openly accessible. The shared products are based upon peer-reviewed science and relate aspects of forest structure including: (i) metrics calculated directly from the lidar point cloud with heights normalized to heights above the ground surface (e.g., canopy cover, height), and (ii) modelled inventory attributes, derived using an area-based approach generated by using co-located ground plot and ALS data (e.g., volume, biomass). Forest structure estimates were generated by combining information from lidar plots (Wulder et al. 2012) with Landsat pixel-based composites (White et al. 2014; Hermosilla et al. 2016) using a nearest neighbour imputation approach with a Random Forests-based distance metric. These products were generated for strategic-level forest monitoring information needs and are not intended to support operational-level forest management. All products have a spatial resolution of 30 m. For a detailed description of the data, methods applied, and accuracy assessment results see Matasci et al. (2018). When using this data, please cite as follows: Matasci, G., Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., Hobart, G.W., Bolton, D.K., Tompalski, P., Bater, C.W., 2018b. Three decades of forest structural dynamics over Canada's forested ecosystems using Landsat time-series and lidar plots. Remote Sensing of Environment 216, 697-714. Matasci et al. 2018) Wulder et al. 2018)Geographic extent: Canada's forested ecosystems (~ 650 Mha)Time period: 1985–2011