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annual_crop_inventory/2009 (ImageServer)

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Service Description: 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. For more information, visit: https://open.canada.ca/data/en/dataset/ce7873ff-fbc0-4864-946e-6a1b4d739154

Name: annual_crop_inventory/2009

Description: 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. For more information, visit: https://open.canada.ca/data/en/dataset/ce7873ff-fbc0-4864-946e-6a1b4d739154

Single Fused Map Cache: false

Extent: Initial Extent: Full Extent: Pixel Size X: 56.0

Pixel Size Y: 56.0

Band Count: 1

Pixel Type: U8

RasterFunction Infos: {"rasterFunctionInfos": [ { "name": "annual_crop_inventory", "description": "Combined annual crop inventory Remap and Attribute Table raster functions", "help": "" }, { "name": "annual_crop_inventory_simplified", "description": "Simplified annual crop inventory Remap and Attribute Table raster functions", "help": "" }, { "name": "annual_crop_inventory_simplified_more", "description": "More simplified annual crop inventory Remap and Attribute Table raster functions", "help": "" }, { "name": "annual_crop_inventory_simplified_most", "description": "Most simplified annual crop inventory Remap and Attribute Table raster functions", "help": "" }, { "name": "None", "description": "Make a Raster or Raster Dataset into a Function Raster Dataset.", "help": "" } ]}

Mensuration Capabilities: Basic

Has Histograms: true

Has Colormap: false

Has Multi Dimensions : false

Rendering Rule:

Min Scale: 0

Max Scale: 0

Copyright Text: Agriculture and Agri-Food Canada

Service Data Type: esriImageServiceDataTypeThematic

Min Values: 0

Max Values: 230

Mean Values: 149.80387930217947

Standard Deviation Values: 64.47470415817702

Object ID Field: OBJECTID

Fields: Default Mosaic Method: Center

Allowed Mosaic Methods: Center,None,NorthWest,LockRaster,ByAttribute,Nadir,Viewpoint,Seamline

SortField:

SortValue: null

Mosaic Operator: First

Default Compression Quality: 75

Default Resampling Method: Nearest

Max Record Count: 1000

Max Image Height: 70000

Max Image Width: 70000

Max Download Image Count: 20

Max Mosaic Image Count: 20

Allow Raster Function: true

Allow Copy: true

Allow Analysis: true

Allow Compute TiePoints: false

Supports Statistics: true

Supports Advanced Queries: true

Use StandardizedQueries: true

Raster Type Infos: Has Raster Attribute Table: false

Edit Fields Info: null

Ownership Based AccessControl For Rasters: null

Child Resources:   Info   Histograms   Statistics   Key Properties   Legend   Raster Function Infos

Supported Operations:   Export Image   Query   Identify   Measure   Compute Histograms   Compute Statistics Histograms   Get Samples   Compute Class Statistics   Query Boundary   Compute Pixel Location   Compute Angles   Validate   Project