Summary
In this video tutorial the 3DEP FTN PM, Jordan Regenie, is joined by Jinha Jung of Purdue University, who presents the tools and processing pipelines developed by his team as part of Purdue’s Data to Science initiative. They demonstrate how open source tools can support the processing of raw USGS 3DEP lidar point cloud data into multiple derivative products using transparent, reproducible workflows.
The tutorial is part of 3DEP for the Nation initiative (a cooperative agreement between USGS 3DEP and NSGIC) focused on expanding the use of 3DEP data and collaboration among stakeholders. 3DEP FTN is on a mission to highlight practical workflows and tools that make 3DEP data more accessible to a wide range of users, from decision-makers to hands-on practitioners.
Content Overview
• Overview of Data to Science open-source tools and processing pipelines
• Step-by-step Jupyter Notebook walkthrough demonstrating how to process raw 3DEP lidar point clouds
• Generation of multiple derivative products, including terrain and analysis-ready datasets
• Design principles that make the workflow easy to follow for non-technical users, while remaining rigorous enough for research and operational use
Resources
• Data2Science project and Github repositories
• USGS 3DEP data resources
• 3DEP for the Nation (FTN) project information