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Charles M. Russell National Wildlife Refuge Spot Landcover Classification in Relation to Greater Sage Grouse

Metadata Updated: June 15, 2024

This landcover raster was generated through a Random Forest predictive model developed in R using a combination of image-derived and ancillary variables, and field-derived training points grouped into 18 classes. Overall accuracy, generated internally through bootstrapping, was 75.5%. A series of post-modeling steps brought the final number of land cover classes to 28.

Access & Use Information

Public: This dataset is intended for public access and use. License: No license information was provided. If this work was prepared by an officer or employee of the United States government as part of that person's official duties it is considered a U.S. Government Work.

Downloads & Resources

Dates

Metadata Created Date May 31, 2023
Metadata Updated Date June 15, 2024

Metadata Source

Harvested from DOI EDI

Additional Metadata

Resource Type Dataset
Metadata Created Date May 31, 2023
Metadata Updated Date June 15, 2024
Publisher Climate Adaptation Science Centers
Maintainer
@Id http://datainventory.doi.gov/id/dataset/c14d287c4f8f8619718d696af10d822e
Identifier 18eb94ad-d0ee-4a8d-b193-3ea35268b7b2
Data Last Modified 2016-09-02
Category geospatial
Public Access Level public
Bureau Code 010:00
Metadata Context https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld
Metadata Catalog ID https://datainventory.doi.gov/data.json
Schema Version https://project-open-data.cio.gov/v1.1/schema
Catalog Describedby https://project-open-data.cio.gov/v1.1/schema/catalog.json
Harvest Object Id 0ae8389d-127e-4a4e-bec1-9d66d2d84602
Harvest Source Id 52bfcc16-6e15-478f-809a-b1bc76f1aeda
Harvest Source Title DOI EDI
Metadata Type geospatial
Old Spatial -109.287002,47.157489,-106.348395,48.332526
Source Datajson Identifier True
Source Hash 6b27053d743b60d959130d0a610de4352e959e03d6a70b4fe03fafcdeab124e3
Source Schema Version 1.1
Spatial {"type": "Polygon", "coordinates": -109.287002, 47.157489, -109.287002, 48.332526, -106.348395, 48.332526, -106.348395, 47.157489, -109.287002, 47.157489}

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