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imageryBaseMapsEarthCover

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    Portions of Universal Transverse Mercator Zones 7 - 12 which cover British Columbia, Northern Hemisphere only, formed into polygons, in BC Albers projection

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    The ‘Circa 1995 Landcover of the Prairies’dataset is a geospatial raster data layer portraying the rudimentaryland cover types of all grain-growing areas of Manitoba, Saskatchewan, Alberta and northeastern British Columbia at a 30-metre resolution for the 1995 timeframe. It is the collection of all the classified imagery (1993 to 1995) of the Western Grain Transition Payment Program (WGTPP) assembled into a single seamless raster data layer.

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    The 2005 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.

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    IBL - Imagery, basemaps, and land cover (imageryBaseMapsEarthCover) Basemaps. For example, resources describing land cover, topographic maps, and classified and unclassified images

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    Vegetation biophysical parameters correspond to physical properties of vegetation structure (e.g. density, height, biomass), biochemistry (e.g. chlorophyll and water content) or energy exchange (e.g. albedo, temperature). These parameters have been identified by the Global Climate Observing System as an essential climate variable required for ecosystem, weather and climate modelling and monitoring. The Canada wide products are derived from systematically acquired satellite imagery with spatial resolution from 10m to 30m and provided as monthly temporal or peak-season composites due to cloud cover. Products are derived applying algorithms developed at Canada Centre for Remote Sensing (NRCan) to Copernicus Sentinel 2 satellite imagery. Select a related product first to view content.

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    Note: To visualize the data in the viewer, zoom into the area of interest. The National Air Photo Library (NAPL) of Natural Resources Canada archives over 6 million aerial photographs covering all of Canada, some of which date back to the 1920s. This collection includes Time Series of aerial orthophoto mosaics over a selection of major cities or targeted areas that allow the observation of various changes that occur over time in those selected regions. These mosaics are disseminated through the Data Cube Platform implemented by NRCan using geospatial big data management technologies. These technologies enable the rapid and efficient visualization of high-resolution geospatial data and allow for the rapid generation of dynamically derived products. The data is available as Cloud Optimized GeoTIFF (COG) files for direct access and as Web Map Services (WMS) or Web Coverage Services (WCS) with a temporal dimension for consumption in Web or GIS applications. The NAPL mosaics are made from the best spatial resolution available for each time period, which means that the orthophotos composing a NAPL Time Series are not necessarily coregistered. For this dataset, the spatial resolutions vary from 150 cm to 200 cm. The NAPL indexes and stores federal aerial photography for Canada, and maintains a comprehensive historical archive and public reference centre. The Earth Observation Data Management System (EODMS) online application allows clients to search and retrieve metadata for over 3 million out of 6 million air photos. The EODMS online application enables public and government users to search and order raw Government of Canada Earth Observation images and archived products managed by NRCan such as aerial photos and satellite imagery. To access air photos, you can visit the EODMS web site: https://eodms-sgdot.nrcan-rncan.gc.ca/index-en.html

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    Leaf area index (LAI) quantified the density of vegetation irrespective of land cover. LAI quantifies the total foliage surface area per ground surface area. LAI has been identified by the Global Climate Observing System as an essential climate variable required for ecosystem, weather and climate modelling and monitoring. This product consists of a national scale coverage (Canada) of monthly maps of the maximum LAI during a growing season (May-June-july-August-September) at 20m. References: L. Brown, R. Fernandes, N. Djamai, C. Meier, N. Gobron, H. Morris, C. Canisius, G. Bai, C. Lerebourg, C. Lanconelli, M. Clerici, J. Dash. Validation of baseline and modified Sentinel-2 Level 2 Prototype Processor leaf area index retrievals over the United States IISPRS J. Photogramm. Remote Sens., 175 (2021), pp. 71-87, https://doi.org/10.1016/j.isprsjprs.2021.02.020. https://www.sciencedirect.com/science/article/pii/S0924271621000617 Richard Fernandes, Luke Brown, Francis Canisius, Jadu Dash, Liming He, Gang Hong, Lucy Huang, Nhu Quynh Le, Camryn MacDougall, Courtney Meier, Patrick Osei Darko, Hemit Shah, Lynsay Spafford, Lixin Sun, 2023. Validation of Simplified Level 2 Prototype Processor Sentinel-2 fraction of canopy cover, fraction of absorbed photosynthetically active radiation and leaf area index products over North American forests, Remote Sensing of Environment, Volume 293, https://doi.org/10.1016/j.rse.2023.113600. https://www.sciencedirect.com/science/article/pii/S0034425723001517

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    Mackenzie Valley Air Photo Digital Orthotiles

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    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. NOTE: To see this entire product in the map viewer, use a base map in the "World" section (EPSG: 3857).

  • This is a Mosaic of Canada which is made from 121 images captured by Canadian satellite RADARSAT-2. These images were acquired from May 1, 2013 to June 1, 2013. The color variation represents the changes in soil texture, roughness and the level of soil moisture. (Credit: RADARSAT-2 Data and Products © MacDonald, Dettwiler and Associates Ltd. (2013) - All Rights Reserved. RADARSAT is an official mark of the Canadian Space Agency.)