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    3DEP LidarExplorer

    • amerigeo.org
    • hub.arcgis.com
    Updated Jul 9, 2021
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    AmeriGEOSS (2021). 3DEP LidarExplorer [Dataset]. https://www.amerigeo.org/documents/25eab4bcf1dd4fddb8b90fca0c217013
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    Dataset updated
    Jul 9, 2021
    Dataset authored and provided by
    AmeriGEOSS
    Description

    The LidarExplorer was originally created to enable identification of lidar projects having 3D visualization enabled (via Entwine) and having Amazon AWS cloud access. Now that all of the USGS Lidar products are available in the Cloud and 3D visualization is being enabled for all projects, these original requirements have been satisfied.Moving forward this application will bring together the necessary information for discovering and understanding the underlying 3DEP elevation data and provide avenues for efficiently processing the data within the cloud to avoid the need to download and process data locally. Users will be able to define their area of interest, select and filter products based on needs, create processing pipelines for transforming the data into derived products or results and execute the processing using within-cloud processing capabilities.

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Share
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TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
AmeriGEOSS (2021). 3DEP LidarExplorer [Dataset]. https://www.amerigeo.org/documents/25eab4bcf1dd4fddb8b90fca0c217013

3DEP LidarExplorer

Explore at:
19 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Jul 9, 2021
Dataset authored and provided by
AmeriGEOSS
Description

The LidarExplorer was originally created to enable identification of lidar projects having 3D visualization enabled (via Entwine) and having Amazon AWS cloud access. Now that all of the USGS Lidar products are available in the Cloud and 3D visualization is being enabled for all projects, these original requirements have been satisfied.Moving forward this application will bring together the necessary information for discovering and understanding the underlying 3DEP elevation data and provide avenues for efficiently processing the data within the cloud to avoid the need to download and process data locally. Users will be able to define their area of interest, select and filter products based on needs, create processing pipelines for transforming the data into derived products or results and execute the processing using within-cloud processing capabilities.

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