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We have found 1,621 datasets for the keyword " images satellitaires historiques québec". You can continue exploring the search results in the list below.
Datasets: 103,401
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1,621 Datasets, Page 1 of 163
Agro-Pedological Atlas of Quebec
The “Agro-Pedological Atlas of Quebec” is a dataset that shows the characteristics, the fertility, the quality of the water regime, the vulnerability to degradation and the potential of the agricultural soils and land in the Monteregian region of the province of Quebec.
Annual Crop Inventory 2011
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.
Canopy 2020
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).**
Canopy 2015
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 two satellite images covering Quebec City taken by the Pléiades satellite pair on June 24 and July 13, 2015 (spatial resolution of 50 cm).**This third party metadata element was translated using an automated translation tool (Amazon Translate).**
Railways - Saint-Hyacinthe
Railway network on the territory of the city.**Collection context** Historical data from the Government of Quebec.Additional data by photointerpretation.**Collection method** Computer-aided mapping.**Attributes*** `ID_VFR` (`integer`): Identifier* `SOURCE` (`varchar`): Source* `DATE_CREATION` (`smalldatetime`): Created on* `DATE_MODIFICATION` (`smalldatetime`): Modified on* `USER_MODIFICATION` (`varchar`): Modified byFor more information, consult the metadata on the Isogeo catalog (OpenCatalog link).**This third party metadata element was translated using an automated translation tool (Amazon Translate).**
Annual Crop Inventory 2019
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.
Annual Crop Inventory 2018
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
Annual Crop Inventory 2016
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.
GeoAI - Change detection use case - Trois-Rivières
Temporal analysis of changes in Trois-Rivières, Québec, based on GeoAI features automatically extracted from satellite images acquired in 2013 and 2021-22. Simple geospatial analysis intersecting Statistics Canada's Open Database of Buildings, version 3 (ODB v3) with GeoAI multidate building features enables the detection of buildings observed in 2021-22 that were not detected in 2013. The addition of new buildings is a good indicator of urban development and/or sprawl.GeoAI enables temporal coverage of various areas in Canada, thus providing a useful tool for change detection and trend analysis at high resolution. While the series is still fairly new, and such examples are limited for the time being, NRCan strives to gradually increase its GeoAI data offering for both spatial and temporal coverage.For more information about the GeoAI - GeoBase Series, please visit the following link: https://open.canada.ca/data/en/dataset/74738ff5-5367-5958-9aee-98fffdcd1876
Annual Crop Inventory 2017
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
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