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Found 59 dataset(s) matching "object-based image classification".
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This dataset contains 10 classified raster images identifying the distribution and condition of biological soil crusts using high-resolution imagery from Unmanned Aerial Systems (UAS). Also...
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These products were developed to provide scientific and correspondingly spatially explicit information regarding the distribution and abundance of conifers (namely, singleleaf pinyon (Pinus...
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These products were developed to provide scientific and correspondingly spatially explicit information regarding the distribution and abundance of conifers (namely, singleleaf pinyon (Pinus...
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Data for the classification of coastal land-cover of Barnegat Bay (Fig. 1) were downloaded from the USGS Earth Resources Observation and Science (EROS) Center via the USGS Earth Explorer website....
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Loss of salt marsh habitat at Timucuan Ecological and Historic Preserve (TIMU) due to sea level rise has been identified by park staff as a concern. The purpose of this project is to classify and...
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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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During 2018, uncrewed aerial vehicles (UAVs or 'drones') were used to collect spatially referenced aerial imagery from 20 management units (sites) enrolled in the Phragmites Adaptive Management...
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<div style='text-align:Left;'><div><div><p><span>This image service contains high-resolution land cover data for the states of Nebraska, South Dakota, and North Dakota. These data are a digital...
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<a href='https://doi.org/10.2737/RDS-2017-0025' target='_blank' rel='nofollow ugc noopener noreferrer'>Download this data or get more information</a>. This data publication contains 2015...
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<p style='margin-top:0px; margin-bottom:1.5rem; font-family:"Avenir Next W01", "Avenir Next W00", "Avenir Next", Avenir, "Helvetica Neue", sans-serif;...
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<p>This data layer references data from a high-resolution tree canopy change-detection layer for Seattle, Washington. Tree canopy change was mapped by using remotely sensed data from two time...
