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We have found 33 datasets for the keyword " potato". You can continue exploring the search results in the list below.
Datasets: 106,031
Contributors: 42
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33 Datasets, Page 1 of 4
Annual Crop Inventory 2010
In 2010 the Earth Observation Team of the Science and Technology Branch (STB) at Agriculture and Agri-Food Canada (AAFC) continued the process of generating annual crop inventory digital maps using satellite imagery. Focusing on the Prairie Provinces, a Decision Tree (DT) based methodology was applied using both optical (AWiFS, Landsat-5, DMC) and radar (RADARSAT-2) based satellite imagery, and having a final spatial resolution of 56m. Methods were also developed to enhance the optical classification with RADARSAT-2 imagery, addressing issues associated with cloud cover. In conjunction with satellite acquisitions, ground-truth information was provided by provincial crop insurance companies and point observations from our regional AAFC colleagues. The overall process for Crop Inventory Map includes: satellite data acquisition; field data acquisition for classification training and accuracy assessment; and, operational implementation of the classification methodology.
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
Kokanee Shore Spawner Data - Okanagan Region
The Okanagan Lake kokanee shore spawner data set is comprised of multiple combined data sets. The historical data sets for the years 1974, 77, 78, 79 and 80 and more recent data sets collected from 2001 to 2016, and 2018. The historical data was derived from information collected in the field and hand drawn onto air photographs. Ministry staff circled Okanagan Lake in a boat one time each year and recorded fish numbers and spawner locations onto air photographs that were digitized in 2006 to make up the historical data set. This data set may not capture the peak reach count for these years. The data collected from 2001 to 2018 was derived from boat counts undertaken along the shoreline of Okanagan, Wood and Kalamalka Lakes. A GPS was used to record shore spawner locations and numbers. Multiple counts were undertaken over the entire spawning cycle and covered the peak spawning period for each year of data provided. The data collected for Christina Lake began in 2003 and ended in 2006. Christina Lake kokanee spawn at night in late December and early January. Kokanee spawning redd locations are available for the 2003/2004 count. Kokanee enumerations were undertaken at night for the 2004/2005 and 2005/2006 seasons and spawning redds were counted at the end of spawning cycle. For these two years there is both spawning and redd count data available.
Annual Crop Inventory 2024
In 2024, 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 for all Canadian provinces and the Yukon Territory, in support of a national crop inventory. A Decision Tree (DT) based methodology was applied using optical (Landsat-8, Landsat-9, Sentinel-2), and radar (RCM) 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, Fredericton, Guelph, Summerland and Whitehorse. Forest Fire Perimeter Estimate polygons from Natural Resources Canada’s Canadian Forest Service are used to show burned areas of landcover (Class - 60).
Annual Crop Inventory 2015
In 2015, 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) 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 the BC Ministry of Agriculture and our regional AAFC colleagues.
Landsat Image Catalogue Acquisition Dates Spatial View (SII)
Polygons containing the date of capture of the Landsat images used to create the first version of the Baseline Thematic Mapping v1 (BTM1). This spatial view is only meaningful in conjunction with the satellite images or the BTM data derived from the satellite images. The images were captured from 1990 to 1997
Gilpinia hercyniae
Historical finds of Gilpinia hercyniae
Annual Crop Inventory 2009
In 2009 the Earth Observation Team of the Science and Technology Branch (STB) at Agriculture and Agri-Food Canada (AAFC) began the process of generating annual crop inventory digital maps using satellite imagery. Focusing on the Prairie Provinces, a Decision Tree (DT) based methodology was applied using both optical (AWiFS, Landsat-5) and radar (RADARSAT-2) based satellite imagery, and having a final spatial resolution of 56m. Methods were also developed to enhance the optical classification with RADARSAT-2 imagery, addressing issues associated with cloud cover. In conjunction with satellite acquisitions, ground-truth information was provided by provincial crop insurance companies and point observations from our regional AAFC colleagues. The overall process for Crop Inventory Map includes: satellite data acquisition; field data acquisition for classification training and accuracy assessment; and, operational implementation of the classification methodology.The initial methodology was developed in partnership with AAFC Research Branch, and supported in part by the Canadian Space Agency. The long-term objective of this endeavour is to expand from the Prairies and produce an annual crop inventory of the entire agricultural extent of Canada.
Annual Crop Inventory 2014
In 2014, 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) 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 the BC Ministry of Agriculture and our regional AAFC colleagues.
Agriculture
A series of relevant spatial datasets were compiled to construct an Agricultural Potential Index model which combines multiple criteria that influence agricultural suitability. For more information on the Agriculutural Potential Index Model, please see the metadata link.
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