Elevator Pitch
Point clouds make for compelling 3D imagery, but there’s real engineering information in there too! See what we are mining out of airborne laser scanning data to enhance the resilience of coastal communities.
Description
Dr. Stephen Medeiros, a lecturer in Civil Engineering at the University of Central Florida, describes his team’s work in Geospatial Data Fusion for coastal resilience. Dr. Medeiros uses airborne laser scanning data (aka lidar) to characterize surface roughness for use in computer models for hurricane storm surge. All of his students are required to learn and apply Python to their data science tasks such as ETL, machine learning, and statistical analysis of a variety of environmental data such as wind speeds, water levels, and 3D laser scanning point clouds. By describing the coastal floodplain in intricate detail, Dr. Medeiros and his students study how the roughness of the landscape influence hurricane winds and storm surge behavior. This work is carried out on the STOKES HPC at the Advanced Research Computing Center in UCF’s Institute for Simulation and Training.
Notes
No special requirements other than powerpoint. I am very eager to become a bigger part of the Python community here in FL and I think this is the best avenue to do it. It would be great to get my unique application out there and possibly make some connections within the Python Data Science community to generate some new collaboration opportunities. I am an expert in this topic with 25 peer reviewed journal publications in the area of hurricane storm surge modeling, remote sensing, and characterization of surface roughness. One publication that is partiucularly relevant to my proposed lightning talk can be found at http://ieeexplore.ieee.org/document/7089234/