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.

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.

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.

Footprintsfor all imagery in the Government of Yukon Medium Resolution Satellite ImageryService.Distributed from [GeoYukon](https://yukon.ca/geoyukon) by the [Government of Yukon](https://yukon.ca/maps) . Discover more digital map data and interactive maps from Yukon's digital map data collection.Formore information: [geomatics.help@yukon.ca](mailto:geomatics.help@yukon.ca).

Yukon highresolution satellite imagery is distributed from the Government of Yukonimagery repository. This is a dynamic service containing satellite imagery forlocations in the Yukon, Canada.This data is hostedin Yukon Albers equal area projection. It can be viewed and queried in theGeoYukon application: [https://mapservices.gov.yk.ca/GeoYukon](https://mapservices.gov.yk.ca/GeoYukon).For more informationcontact geomatics.help@yukon.ca.

In 2013, 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.

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.

Yukon mediumresolution satellite imagery is distributed from the Government of Yukonimagery repository. This is a dynamic service containing satellite imagery forlocations in the Yukon, Canada.This data is inYukon Albers equal area projection. It can be viewed and queried in theGeoYukon application: [https://mapservices.gov.yk.ca/GeoYukon](https://mapservices.gov.yk.ca/GeoYukon).For more informationcontact [geomatics.help@yukon.ca](mailto:geomatics.help@yukon.ca).

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.

RADARSAT-1, in operation from 1995 to 2013, is Canada's first earth observation satellite. Developed and operated by the Canadian Space Agency (CSA), it has provided essential information to government, scientists and commercial users.Ultimately, the RADARSAT-1 mission generated the largest synthetic-aperture radar (SAR) data archive in the world. In April 2019, 36,000 images were made accessible through the Earth Observation Data Management System (eodms-sgdot.nrcan-rncan.gc.ca).A heatmap of processed images was produced by the CSA and helps visualize the density of images available by mapped sector during the RADARSAT-1 mission.