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Found 829 dataset(s) matching "tree cover".
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This dataset represents the characterization of global forest extent and change by year from 2001 through 2013 within individual local and accumulated upstream catchments for NHDPlusV2 Waterbodies...
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The RCMAP (Rangeland Condition Monitoring Assessment and Projection) dataset quantifies the percent cover of rangeland components across the western U.S. using Landsat imagery from 1985-2021. The...
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The RCMAP (Rangeland Condition Monitoring Assessment and Projection) dataset quantifies the percent cover of rangeland components across the western U.S. using Landsat imagery from 1985-2021. The...
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The RCMAP (Rangeland Condition Monitoring Assessment and Projection) dataset quantifies the percent cover of rangeland components across the western U.S. using Landsat imagery from 1985-2021. The...
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The RCMAP (Rangeland Condition Monitoring Assessment and Projection) dataset quantifies the percent cover of rangeland components across the western U.S. using Landsat imagery from 1985-2021. The...
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The RCMAP (Rangeland Condition Monitoring Assessment and Projection) dataset quantifies the percent cover of rangeland components across the western U.S. using Landsat imagery from 1985-2021. The...
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The RCMAP (Rangeland Condition Monitoring Assessment and Projection) dataset quantifies the percent cover of rangeland components across the western U.S. using Landsat imagery from 1985-2021. The...
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The RCMAP (Rangeland Condition Monitoring Assessment and Projection) dataset quantifies the percent cover of rangeland components across the western U.S. using Landsat imagery from 1985-2021. The...
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The RCMAP (Rangeland Condition Monitoring Assessment and Projection) dataset quantifies the percent cover of rangeland components across the western U.S. using Landsat imagery from 1985-2021. The...
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The RCMAP (Rangeland Condition Monitoring Assessment and Projection) dataset quantifies the percent cover of rangeland components across the western U.S. using Landsat imagery from 1985-2021. The...
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This data set contains proportional estimates for the vegetative cover types of tree cover, herbaceous vegetation, and bare ground over South America for the period 2000-2001. These products were...
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<b>FIA Modeled Abundance:�</b><div>This dataset portrays the live tree mean basal area (square feet per acre) of the species across the contiguous United States. The underlying data publication...
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The NASA Making Earth System Data Records for Use in Research Environments ([MEaSUREs](https://earthdata.nasa.gov/community/community-data-system-programs/measures-projects)) Vegetation Continuous...
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The Focal Terrestrial Plant Communities Monitoring database is the main storage location for all data related to the Focal Terrestrial Plant Communities Monitoring Protocol. It contains spatial...
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Meter-scale Urban Land Cover (MULC), a unique, high resolution (one meter2 per pixel) land cover dataset, has been developed for 30 US communities for the United States Environmental Protection...
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This is a MD iMAP hosted service. Find more information at http://imap.maryland.gov. The dataset displays the presence and absence of forested areas within a 100 foot-buffer of a stream or...
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This is the story of tree cover in Washington, DC from the role of trees since the earliest planning, through current measures taken to ensure a green legacy for all that follow. Washington, DC...
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National Land Cover Database (NLCD) 2006 Land Cover Conterminous United States (ver. 2.0, July 2024)
The National Land Cover Database products are created through a cooperative project conducted by the Multi-Resolution Land Characteristics (MRLC) Consortium. The MRLC Consortium is a partnership...
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The National Land Cover Database products are created through a cooperative project conducted by the Multi-Resolution Land Characteristics (MRLC) Consortium. The MRLC Consortium is a partnership...
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The Land Processes Distributed Active Archive Center (LP DAAC) archives and distributes Global Forest Cover Change (GFCC) data products through the NASA Making Earth System Data Records for Use in...
