This collection is a legacy product that is no longer maintained. It may not meet current government standards. The correction matrices for the National Topographic Data Base (NTDB), also known under the acronym CORMAT, are products derived from the planimetric enhancement of NTDB data sets at the 1:50 000 scale. The correction matrix enables users to enhance the geometric accuracy of the less accurate NTDB. The matrix is a set of points arrayed on a regular 100-m grid. Each point describes the planimetric correction (DX, DY) to be applied at this location. The position of the points is given in UTM (Universal Transverse Mercator projection) coordinates based on the North American Datum of 1983 (NAD83) . Each file constitutes a rectangular area covering the entire corresponding NTDB data set. Its delimitation corresponds more or less to National Topographic System (NTS) divisions at the 1:50 000 scale. All NTDB data sets at the 1:50 000 scale whose original accuracy was less than 30 m can thus be geometrically corrected. A CORMAT data set contains a list of coordinates and the corresponding corrections to be applied in the form X Y DX DY. Related Products: [National Topographic Data Base (NTDB), 1944-2005](https://open.canada.ca/data/en/dataset/1f5c05ff-311f-4271-8d21-4c96c725c2af)

This collection is a legacy product that is no longer supported. It may not meet current government standards. Land Cover information is the result of vectorization of raster thematic data originating from classified Landsat 5 and Landsat 7 ortho-images, for agricultural and forest areas of Canada, and for Northern Territories. The forest cover was produced by the Earth Observation for Sustainable Development (EOSD) project, an initiative of the Canadian Forest Service (CFS) with the collaboration of the Canadian Space Agency (CSA) and in partnership with the provincial and territorial governments. The agricultural coverage is produced by the National Land and Water Information Service (NLWIS) of Agriculture and Agri-Food Canada (AAFC). Northern Territories land cover was realized by the Canadian Centre of Remote Sensing (CCRS). Land Cover data are classified according to a harmonized legend build from the partner's legends. This legend is principally based on the legend described in following publication: EOSD publication: EOSD Land Cover Classification Legend Report, on which CFS and AAFC collaborated. Some classes related to Northern environments where added in order to meet the interpretation of the Northern land cover classification experts. Initially, Land Cover vector data are closest as possible to the source (original raster data). Slight differences can occur because the raster data goes through a data portrayal before being vectorized in order to enhance visual representation such as minimum size, smoothness of polygons and geometry.

Each pixel value corresponds to the best quality maximum NDVI recorded within that pixel over the week specified. Poor quality pixel observations are removed from this product. Observations whose quality is degraded by snow cover, shadow, cloud, aerosols, and/or low sensor zenith angles are removed (and are assigned a value of “missing data”). In addition, negative Max-NDVI values, occurring where R reflectance > NIR reflectance, are considered non-vegetated and assigned a value of 0. This results in a Max-NDVI product that should (mostly) contain vegetation-covered pixels. Max-NDVI values are considered high quality and span a biomass gradient ranging from 0 (no/low biomass) to 1 (high biomass).

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”.

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

Each pixel value corresponds to the difference (anomaly) between the mean “Best-Quality” Max-NDVI of the week specified (e.g. Week 18, 2000-2014) and the “Best-Quality” Max-NDVI of the same week in a specific year (e.g. Week 18, 2015). Max-NDVI anomalies < 0 indicate where weekly Max-NDVI is lower than normal. Anomalies > 0 indicate where weekly Max-NDVI is higher than normal. Anomalies close to 0 indicate where weekly Max-NDVI is similar to normal.

The 2000 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.

Orthophotos of the Communities in the Northwest Territories taken over the past 20 years.  For more infomation on the imagery and dates of the images, please see the metadata link above.

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.

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) 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 coregistrated. For this dataset, the spatial resolutions are: 25 cm for the year 1950, 75 cm for the year 1960, 50 cm for the year 1964, 75 cm for the year 1973, 75 cm for the year 1994 and 50 cm for the year 2001. 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