These three satellite mosaics cover the entire territory of Quebec and include images taken in 2018, 2019 and 2020. The spectral bands are blue (band 2), near infrared (band 8), and short wave infrared (band 11).The Copernicus Sentinel-2 mission includes a constellation of two satellites in orbit that are in tandem and 180° apart from each other. The orbital configuration allows coverage with a revisit rate varying from two to ten days depending on the latitude. The Sentinel-2 constellation captures multispectral satellite images at a resolution of 10 m for the next generation of operational products, such as land use maps, land change detection maps, and geophysical variables. [Product Technical Specifications] (https://diffusion.mern.gouv.qc.ca/diffusion/RGQ/Matriciel/Satellite/Regional/Mosaiques_Sentinel-2/Document/Sentinel-2_User_Handbook.pdf)**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

The annual Landsat mosaics offer a unique portrait of the whole of Quebec. They make it possible to analyze environmental and territorial changes over more than 40 years, in particular the evolution of natural environments, urban sprawl, agricultural and forestry activities, the transformations of protected areas as well as the modifications of water networks, such as reservoirs and dams.## #Principales characteristics of mosaics###* 30m resolution* GeoTIFF format* Images acquired between July and August * Time series covering 1984 to the present * Production based on the selection of the best optical quality pixel* Designed to provide a consistent representation from year to yearThese mosaics are produced in collaboration with the Laurentian Forestry Center of the Canadian Forest Service (CFS). The SCF produces the mosaics and the Directorate-General for Geospatial Information of the Ministry of Natural Resources and Forests prepares them for dissemination.The main components are as follows:### #Images GeoTIFF by spectral bands####* Unenhanced mosaics available by spectral bands in 16-bit GeoTIFF format (ex.: SR_L5789_HARM_BP_2013_B1_gapfill_mrnf_masked.tif). Each mosaic includes bands 1 (Blue), 2 (green), 2 (green), 3 (red), 3 (red), 4 (near infrared), 5 (medium infrared) and 7 (medium infrared);* Matrix showing the year of the images where the highest quality pixels were extracted (ex.: SR_L5789_HARM_BP_2013_year_gapfill_mrnf_masked.tif);* Matrix showing the Julian days of the highest quality pixels extracted. Julian days start on January 1, 1970, hence the JJ70 label (e.g.: SR_L5789_HARM_BP_2013_JJ70_gapfill_mrnf_masked.tif). They make it possible to find the exact date when the pixels were captured in each mosaic;* Matrix showing which Landsat satellite corresponds to each higher-quality pixel extracted (ex.: SR_L5789_HARM_BP_2013_sensor_gapfill_mrnf_masked.tif).### #Images enhanced mosaics####GeoTIFF mosaics bringing together the six spectral bands enhanced by Contrast Limited Adaptive Histogram Equalization (CLAHE) for each year (e.g.: Mosaique_Landsat_2013_CLAHE.tif). Notes to the user: 1. Some artifacts may be present where no Landsat images acquired during the same year were free of clouds, airveils, or shadows. 2. Mosaics from 1984 to 1989 include certain areas where there is no data due to limited acquisition capacity. The number of Landsat satellites in orbit at that time was not sufficient to ensure complete imaging coverage during the months of July and August.3. Use of images: This is not a requirement, but the following source citation may be used in publications or presentation materials to recognize the United States Geological Survey. Landsat Collection 2 Surface Reflectance (SR) courtesy of the U.S. Geological Survey.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Cartography of the vegetation cover of Quebec City. The canopy represents the projection on the ground of the tops (crown) of trees (including leaves, branches, and trunks), which is visible from the sky. The data comes from an automated classification of two satellite images covering Quebec City by the pair of World-View-3 and Pléiades satellites acquired in July 2020 (spatial resolution of 31 cm) and from the 2017 Lidar survey of Quebec City.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

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

In 2011, the Earth Observation Team of the Science and Technology Branch (STB) at Agriculture and Agri-Food Canada (AAFC) expanded the process of generating annual crop inventory digital maps using satellite imagery to include British Columbia, Ontario, Quebec, and the Maritime provinces, in support of a national crop inventory. A Decision Tree (DT) based methodology was applied using optical (Landsat-5, DMC) 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 and point observations from our regional AAFC colleagues.

The bank of oblique photographs of Northern Quebec is composed of georeferenced photos taken on board planes or helicopters during flights carried out as part of the program for the acquisition of ecological knowledge in Northern Quebec as part of the economic, social and environmental development project “Plan Nord”. During these overflights, the personnel on board were equipped with high-resolution cameras connected to a satellite geolocation system (GPS). The photos obtained in this way served as control points to improve the various thematic maps. __Note:__ For the purposes of distributing this bank, the photos could be modified slightly in order to improve the shooting. Georeferencing photos on the map refers to the location of the plane or helicopter at the time the shot was taken. **This third party metadata element was translated using an automated translation tool (Amazon Translate).**

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 2017, 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, Gaofen-1) 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 BC Ministry of Agriculture, & the Ontario Ministry of Agriculture, Food and Rural Affairs; and data collection supported by our regional AAFC Research and Development Centres in St. John’s, Kentville, Charlottetown, Fredericton, Guelph, and Summerland

In 2018, 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 BC Ministry of Agriculture, & the Ontario Ministry of Agriculture, Food and Rural Affairs; and data collection supported by our regional AAFC Research and Development Centres in St. John’s, Kentville, Charlottetown, Fredericton, Guelph, and Summerland

In 2016, 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, Gaofen-1) 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 BC Ministry of Agriculture, & the Ontario Ministry of Agriculture, Food and Rural Affairs; and data collection supported by our regional AAFC Research and Development Centres in St. John’s, Kentville, Charlottetown, Fredericton, Guelph, and Summerland.