This layer represents Land use polygons as determined by a combination of analytic techniques, mostly using Landsat 5 image mosaics . BTM 1 was done on a federal satellite image base that was only accurate to about 250m. The images were geo-corrected, not ortho-corrected, so there is distortion in areas of high relief. This is not a multipart feature

High-resolution false-color Landsat image composite of Canada's forested ecosystems (2022). This national image product represents the Composite to Change (C2C) proxy composite image derived from thousands of Landsat images acquired between July 1 and August 30, 2022. It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). The overall process followed is described in (Hermosilla et al. 2016 ) with details on the generation of gap-free surface reflectance composites in ( Hermosilla et al. 2015). Following the motivation and rationale presented in White et al. (White et al. 2014), Landsat imagery is subjected to a series of processing steps to remove clouds and shadows as well as haze and other unwanted atmospheric effects. Year-on-year time series of Landsat imagery are interrogated to avoid missing values, and to ensure exhaustive spatial coverage of the national surface reflectance composites. False-colour 3-channel image (bands: shortwave infrared, SWIR1; near infrared; red)When using these data, please cite as: Hermosilla, T., M.A. Wulder, J.C. White, N.C. Coops, G.W. Hobart, L.B. Campbell, 2016. Mass data processing of time series Landsat imagery: pixels to data products for forest monitoring. International Journal of Digital Earth 9(11), 1035-1054 (Hermosilla et al. 2016 ).

These products are derived from RGB (red/green/blue) images, a satellite processing technique that uses a combination of satellite sensor bands (also called channels) and applies a red/green/blue (RGB) filter to each of them. The result is a false-color image, i.e. an image that does not correspond to what the human eye would see, but offers high contrast between different cloud types and surface features. The on-board sensor of a weather satellite obtains two basic types of information: visible light data (reflected light) reflecting off clouds and different surface types, also known as "reflectance", and infrared data (emitted radiation) which are short-wave and long-wave radiation emitted by clouds and surface features. RGBs are specially designed to combine this type of satellite data, resulting in an information-rich final product.Other products are based on the enhancement of channel data for a single wavelength, also aimed at highlighting meteorological features of the observed surface or clouds, but in a simpler way since only a single wavelength is involved. This older approach is still useful today, as its simplicity makes image interpretation easier in some cases.

These products are derived from RGB (red/green/blue) images, a satellite processing technique that uses a combination of satellite sensor bands (also called channels) and applies a red/green/blue (RGB) filter to each of them. The result is a false-color image, i.e. an image that does not correspond to what the human eye would see, but offers high contrast between different cloud types and surface features. The on-board sensor of a weather satellite obtains two basic types of information: visible light data (reflected light) reflecting off clouds and different surface types, also known as "reflectance", and infrared data (emitted radiation) which are long-wave radiations emitted by clouds and surface features. RGBs are specially designed to combine this type of satellite data, resulting in an information-rich final product. Four types of products are currently generated from the GOES-West and GOES-East satellites: "NightIR" and "NightMicrophysics", at 2km resolution, are generated 24 hours a day with infrared channels, so are visible both night and day, and "NaturalColour" and "DayCloudConvection", at 1km resolution, which combine visible light channels with infrared channels; their higher resolution makes the latter two products more popular, but they are not available during most of the night (between 02UTC and 07UTC for GOES-Est, and between 06UTC and 11UTC for GOES-Ouest) given the absence of reflected sunlight. Other RGB products should be added gradually in the future to meet different needs.

Digital orthorectified imagery acquired at a variety of image resolutions, available in New Brunswick Stereographic Double Projection (NBSDP).

Geographic bathymetric grid data at 100 m x 100 m pixel resolution. Datum: WGS84Collaboration of Canada, the United States of America and the European Union as part of the Atlantic Ocean Research Alliance's fifth project under the Galway Statement. Project mapped the North Atlantic seafloor along a transect from Halifax, Canada to Tromsø, Norway to further the understanding of marine habitats, conservation and navigation. Chief Scientist / Primary Investigator name: Paola Travaglini Platform: CCGS Louis S. St- Laurent (Canadian heavy icebreaker)Device 1 type: Multibeam echo-sounder (sonar)Device 1 manufacturer: Kongsberg Device 1 model: EM122 behind an ice protection window Data and Data format:100 m resolution grid of bathymetryBAG format: Bathymetric Attributed Grid ObjectNavigation and positioning: Trimble GNSS receiver + antennae Applanix POS/MV v5 inertial measuring system Horizontal Datum: WGS84 (G1762) Tidal correction:Zero tide applied: tides are not well known for the major part of the data and tides over very deep water are generally negligible. Sound Velocity Profile measurements:In-situ sound velocity profiles were applied.Note on accuracy/S-44 survey standards:Considering the intended output from this survey (IHO Order 1a - Areas shallower than 100 metres where under-keel clearance is less critical but features of concern to surface shipping may exist.) and using an average depth of 2000 m as ‘d’ in the IHO Standard Equation - the allowable Total Vertical Uncertainty (TVU) must be < 26m which indeed the data has achieved (by comparison with overlapping datasets from other surveys/agency data).IHO Order 1aHorizontal positioning accuracy: 5.0 m + 5% of depth (95% Confidence level)(~105 m at a mean depth of 2000 m)Vertical positioning accuracy: 2.5 m < 26.0 m = Sqrt((0.5 m)^2+(0.013 x 2000 m)^2)

Geographic bathymetric grid data at 100 m x 100 m pixel resolution.Datum: WGS84Collaboration of Canada, the United States of America and the European Union as part of the Atlantic Ocean Research Alliance's second project under the Galway Statement. Project mapped the North Atlantic seafloor along a transect from Halifax, Canada to Tromsø, Norway to further the understanding of marine habitats, conservation and navigation. Chief Scientist / Primary Investigator name: Paola Travaglini Platform: CCGS Louis S. St- Laurent (Canadian heavy icebreaker)Device 1 type: Multibeam echo-sounder (sonar)Device 1 manufacturer: Kongsberg Device 1 model: EM122, hull installed behind ice protection window Data and Data format:100 m resolution grid of bathymetryBAG format: Bathymetric Attributed Grid ObjectNavigation and positioning: Trimble GNSS receiver + antennas Applanix POS/MV v5 inertial measuring system Horizontal Datum: WGS84 (G1762) Tidal correction:Zero tide applied: tides are not well known for the major part of the data and tides over very deep water are generally negligible. Sound Velocity Profile measurements:In-situ sound velocity profiles were applied.Note on accuracy/S-44 survey standards:Considering the intended output from this survey (IHO Order 1a - Areas shallower than 100 metres where under-keel clearance is less critical but features of concern to surface shipping may exist.) and using an average depth of 2000m as ‘d’ in the IHO Standard Equation - the allowable Total Vertical Uncertainty (TVU) must be < 26m which indeed the data has achieved (by comparison with overlapping datasets from other surveys/agency data).IHO Order 1aHorizontal positioning accuracy: 5.0 m + 5% of depth (95% Confidence level)(~105 m at a mean depth of 2000 m)Vertical positioning accuracy: 2.5 m < 26 m = Sqrt((0.5 m)^2+(0.013 x 2000 m)^2)

This collection is a legacy product that is no longer supported. It may not meet current government standards.This inventory presents chronologically the satellite images acquired, orthorectified and published over time by Natural Resources Canada. It is composed of imagery from the Landsat7 (1999-2003) and RADARSAT-1 (2001-2002) satellites, as well as the CanImage by-product and the control points used to process the images.Landsat7 Orthorectified Imagery: The orthoimage dataset is a complete set of cloud-free (less than 10%) orthoimages covering the Canadian landmass and created with the most accurate control data available at the time of creation.RADARSAT-1 Orthorectified Imagery: The 5 RADARSAT-1 images (processed and distributed by RADARSAT International (RSI) complete the landsat 7 orthoimagery coverage. They are stored as raster data produced from SAR Standard 7 (S7) beam mode with a pixel size of 15 m. They have been produced in accordance with NAD83 (North American Datum of 1983) using the Universal Transverse Mercator (UTM) projection. RADARSAT-1 orthoimagery were produced with the 1:250 000 Canadian Digital Elevation Data (CDED) and photogrammetric control points generated from the Aerial Survey Data Base (ASDB).CanImage -Landsat7 Orthoimages of Canada,1:50 000: CanImage is a raster image containing information from Landsat7 orthoimages that have been resampled and based on the National Topographic System (NTS) at the 1:50 000 scale in the UTM projection. The product is distributed in datasets in GeoTIFF format. The resolution of this product is 15 metres.Landsat7 Imagery Control Points: the control points were used for the geometric correction of Landsat7 satellite imagery. They can also be used to correct vector data and for simultaneously displaying data from several sources prepared at different scales or resolutions.

Groundwater flow is the movement of water in an aquifer or hydrogeological unit. The dataset shows groundwater flow rate and direction in the hydrogeological unit. Groundwater flow is establish from piezometric surface map. The method used to create the dataset is described in the metadata associated with the dataset. The dataset represents a description of the flow, including rate in m/d, direction, date and source. Typically, the data provided will not be in the form of a shapefile with linked properties but in the form of an image that sketches the groundwater flow. The image could also represent a cross section of the hydrogeologic units showing the regional trends of the groundwater flow.

Matrix representation of surface materials by RVBI aerial photographs. Identification of vegetated and mineralized areas for the purposes of planning and management of the territory.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**