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Enhancing usability and utility of USGS 3D Elevation Program (3DEP) lidar data and web services with Jupyter Notebooks

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poster
posted on 21.07.2022, 16:03 authored by Cole Speed, Matthew Beckley, Christopher Crosby, Viswanath NandigamViswanath Nandigam

 

The 3D Elevation Program (3DEP), managed by the U.S. Geological Survey (USGS), is acquiring quality level 2 or better light detecting and ranging (lidar) data over the conterminous United States, Hawaii, and US Territories to meet the growing need for high-resolution 3-D representations of Earth's surface, vegetation, and other constructed features. Since its operational start in 2015, over 1800 3DEP projects have been acquired, amounting to > 42 trillion lidar points covering an area > 6.5 million sq. km. The resulting data are publicly and freely available in Entwine Point Tile (EPT) format hosted on Amazon Web Services (AWS). While the volume of available 3DEP lidar data is substantial, documented workflows and best practices for most effectively utilizing these cloud-hosted resources are underdeveloped. OpenTopography, supported by the USGS Community for Data Integration (CDI) program, is developing well-documented and customizable Jupyter Notebook-based Python workflows for programmatically accessing, processing, and visualizing 3DEP data products for a variety of use-cases geared toward USGS applications and for users of point cloud data across the geospatial community. We seek and welcome additional input from this community related to specific use-cases and applications where there is currently need for high resolution elevation products. This poster was presented at the 2022 July ESIP Meeting in Pittsburgh, PA.

Funding

USGS Community for Data Integration (CDI) Project Grand: "Enhancing usability of 3DEP data and web services with Jupyter notebooks​"

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