Enhancing usability of 3DEP data and web services with Jupyter notebooks
We propose to develop a suite of Jupyter notebooks that leverage existing APIs, cloud storage, and open source tools to make it easier for users to efficiently access USGS 3DEP data and to produce data processing and visualization workflows. These notebooks will enhance data utilization, stimulate creative applications, and generate significant return on investment for 3DEP.
The 3D Elevation Program (3DEP) has been actively collecting Quality 2 or better lidar since its operational start in 2015. 3DEP is a partnership program that USGS manages in order to acquire and provide high quality elevation data for the Nation. There are currently over 1700 3DEP projects containing over 37 Trillion lidar points, covering 6.3 million km2 available for applications across the United States. One meter raster data products derived from these lidar point cloud data are also available. While the availability of data might be impressive, accessing and using these data has received less attention by the Program. This project proposes to help make access and use of these data easier by developing a suite of Jupyter Notebooks that leverage existing USGS and third party APIs, cloud resources, and open source software tools and packages to efficiently access USGS 3DEP data and to produce data processing and visualization workflows.
We propose to develop a suite of Jupyter notebooks that leverage existing APIs, cloud storage, and open source tools to make it easier for users to efficiently access USGS 3DEP data and to produce data processing and visualization workflows. These notebooks will enhance data utilization, stimulate creative applications, and generate significant return on investment for 3DEP.
The 3D Elevation Program (3DEP) has been actively collecting Quality 2 or better lidar since its operational start in 2015. 3DEP is a partnership program that USGS manages in order to acquire and provide high quality elevation data for the Nation. There are currently over 1700 3DEP projects containing over 37 Trillion lidar points, covering 6.3 million km2 available for applications across the United States. One meter raster data products derived from these lidar point cloud data are also available. While the availability of data might be impressive, accessing and using these data has received less attention by the Program. This project proposes to help make access and use of these data easier by developing a suite of Jupyter Notebooks that leverage existing USGS and third party APIs, cloud resources, and open source software tools and packages to efficiently access USGS 3DEP data and to produce data processing and visualization workflows.