Cloud Native Geospatial: Cloud Optimized Point Clouds (COPC): Geospatial Point Cloud Analysis designed for the Web

As geospatial datasets proliferate and expand in size, the distribution model of downloading all data to your local machine is starting to break down. This session will focus specifically on cloud-optimized point clouds (COPC). Point cloud formats such as .las for LiDAR and photogrammetry are often heavy and difficult to move around the web. But once we convert it to a cloud-optimized format, we can easily share data out to visualize in a web browser or for analysis in a jupyter notebook. We will show you how to create, share, and work with COPC data.

This session is part of the NextGen Geospatial workshop series that teaches cutting-edge topics around GIS and remote sensing. Each workshop session is designed to be a discrete lesson where students will walk away with specific knowledge on a tool and resources to explore deeper. Our goal is to demystify vocabulary and show you how to use these tools with straight forward examples.

We welcome students and professionals from any field that are interested in expanding their geospatial skillset. A variety of skill levels are also welcome, though each lesson will assume the audience has limited experience on the topic. Basic knowledge of scripting languages (mostly python) and some prior geospatial experience will be helpful. Some of the lessons will include gentle live coding, but the focus will be on the big picture of what the code is doing. Jupyter notebooks with pre-written python code will be provided for these lessons.

SERIES: NextGen Geospatial: AI & Cloud tools for Geographic Analysis:

When:  Tuesdays, 2:00 - 3:00 PM, Sep 3 - Oct 29, 2024
Where:  Weaver Science-Engineering Library, Rm 212 and on Zoom 
Instructor: Jeffrey Gillan
YouTube: Links will be added after the workshops have been presented.

Workshop Materials