The Indigenous Geographical Names dataset presents an extract from the Canadian Geographical Names Data Base (CGNDB) of geographical names with roots in Indigenous cultures. These geographical names reflect heritage, language, personal names, and cultural practices. Terrain and water features, populated places and culturally relevant places are geographical feature types present in the dataset. The Geographical Names Board of Canada (GNBC) is working to increase awareness of existing Indigenous place names and help promote the revitalization of Indigenous cultures and languages. Many more Indigenous place names exist in Canada, and this dataset will be constantly evolving as additional Indigenous place names are officially recognized and identified. The Geographical Names Board of Canada does not warrant or guarantee that the information is accurate, complete or current at all times. For more information, to report data errors, or to suggest improvements, please contact the GNBC Secretariat at Natural Resources Canada with questions or for more information. The CGNDB is the authoritative national database of Canada's geographical names. The purpose of the CGNDB is to store geographical names and their attributes that have been approved by the GNBC, the national coordinating body responsible for standards and policies on place names. This dataset is extracted from the CGNDB on a weekly basis, and consists of current officially approved names, feature type, coordinates of the feature, decision date, source, Indigenous language of origin where known, and other attributes.

Small area data (SAD) on field crops show seeded and harvested area, yield and production estimates for most principal field crops and some special crops in Canada. Most SAD geographies correspond exactly with the Census Agriculture Region (CAR) limits, excepts for some regions of Quebec (where small areas are defined by provincial administrative boundaries), Saskatchewan (where small areas coincide with census divisions boundaries as of 2017) and British Columbia.For exact correspondence between Census Agricultural Regions (CAR) and Small Area Data (SAD) Regions, see the following link:https://www.statcan.gc.ca/eng/statistical-programs/document/3401_D2_V2These regions are associated with Statistics Canada estimates on principal field crops available in the following table: https://www150.statcan.gc.ca/t1/tbl1/en/tv.action?pid=3210000201

In 2012, 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 (except Newfoundland), in support of a national crop inventory. A Decision Tree (DT) based methodology was applied using optical (DMC, SPOT) 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.

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.

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.

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.

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.

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 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

This file outlines the boundaries of the 15 risk areas defined by Manitoba Agricultural Services Corporation./This file describes the boundaries of the 15 risk areas defined by the Manitoba Agricultural Services Corporation.This file outlines the boundaries of the 15 risk areas defined by Manitoba Agricultural Services Corporation. Manitoba Agricultural Services Corporation (MASC) divides Manitoba into 15 Risk Areas of similar crop production risks, which are used to determine the premiums a producer country and the coverage that crops receive. For more information, visit MASC's website: https://www.masc.mb.ca/masc.nsf/maps_risk_areas.html This file describes the boundaries of the 15 at-risk areas defined by the Manitoba Agricultural Services Corporation. The Manitoba Agricultural Services Corporation divides Manitoba into 15 high-risk regions where crop production risks are similar. They are used to determine the premium the producer pays and the coverage the crops receive. For more information, visit the Manitoba Agricultural Services Corporation website: https://www.masc.mb.ca/masc_fr.nsf/maps_risk_areas.html**This third party metadata element was translated using an automated translation tool (Amazon Translate).**