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KansasLandCover/KansasLandCover_GAP (ImageServer)

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Service Description:

Citation: Kansas Applied Remote Sensing Program. 2001. Kansas GAP Land Cover Map. Available at http://kars.ku.edu/geonetwork/srv/en/main.home(accessed {DATE}; verified {DATE}. Kansas Applied Remote Sensing Program, Kansas Biological Survey, University of Kansas, Lawrence, Kansas.

The Kansas GAP land cover map was developed to meet the requirements of Gap Analysis and to fill the need for a detailed map of land cover at the vegetation alliance level. Sponsorship for the Kansas GAP land cover map came from a number of state and federal agencies that provided support through both direct funding and in-kind aid (Table 1 of the final report). The alliance-level land cover map was developed using multi-seasonal Landsat Thematic Mapper imagery and a hybrid classification approach. Assessment of the map’s accuracy was conducted using independent ground verification samples and standard accuracy assessment analysis and reporting procedures. Details of the classification methodology, accuracy assessment, results, and discussion are presented in the final report.

GAP data and final report can be downloaded at the Kansas Biological Survey Metadata Catalog;

http://kars.ku.edu/geonetwork/srv/en/main.home



Name: KansasLandCover/KansasLandCover_GAP

Description:

Citation: Kansas Applied Remote Sensing Program. 2001. Kansas GAP Land Cover Map. Available at http://kars.ku.edu/geonetwork/srv/en/main.home(accessed {DATE}; verified {DATE}. Kansas Applied Remote Sensing Program, Kansas Biological Survey, University of Kansas, Lawrence, Kansas.

The Kansas GAP land cover map was developed to meet the requirements of Gap Analysis and to fill the need for a detailed map of land cover at the vegetation alliance level. Sponsorship for the Kansas GAP land cover map came from a number of state and federal agencies that provided support through both direct funding and in-kind aid (Table 1 of the final report). The alliance-level land cover map was developed using multi-seasonal Landsat Thematic Mapper imagery and a hybrid classification approach. Assessment of the map’s accuracy was conducted using independent ground verification samples and standard accuracy assessment analysis and reporting procedures. Details of the classification methodology, accuracy assessment, results, and discussion are presented in the final report.

GAP data and final report can be downloaded at the Kansas Biological Survey Metadata Catalog;

http://kars.ku.edu/geonetwork/srv/en/main.home



Single Fused Map Cache: false

Extent: Initial Extent: Full Extent: Pixel Size X: 29.999999999999996

Pixel Size Y: 30.0

Band Count: 1

Pixel Type: U8

RasterFunction Infos: {"name":"ks_final1002","description":"A raster function template.","help":""}, {"name":"None","description":"","help":""}

Mensuration Capabilities: Basic

Has Histograms: true

Has Colormap: true

Has Multi Dimensions : false

Rendering Rule:

Min Scale: 0

Max Scale: 0

Copyright Text: Kansas Applied Remote Sensing Program / Kansas Biological Survey

Service Data Type: esriImageServiceDataTypeThematic

Min Values: 0

Max Values: 82

Mean Values: 32.438323223842

Standard Deviation Values: 16.563029121925

Object ID Field:

Fields: None

Default Mosaic Method: Center

Allowed Mosaic Methods:

SortField:

SortValue: null

Mosaic Operator: First

Default Compression Quality: 75

Default Resampling Method: Nearest

Max Record Count: null

Max Image Height: 4100

Max Image Width: 15000

Max Download Image Count: null

Max Mosaic Image Count: null

Allow Raster Function: true

Allow Compute TiePoints: false

Supports Statistics: false

Supports Advanced Queries: false

Use StandardizedQueries: true

Raster Type Infos: Has Raster Attribute Table: true

Edit Fields Info: null

Ownership Based AccessControl For Rasters: null

Child Resources:   Info   Raster Attribute Table   Histograms   Key Properties   Color Map   Legend   MultiDimensionalInfo   rasterFunctionInfos

Supported Operations:   Export Image   Identify   Measure   Compute Histograms   Compute Statistics Histograms   Get Samples   Compute Class Statistics