Computer vision applications in terrestrial lidar point clouds
Computer vision applications in terrestrial lidar point clouds
Graduate Student Name:
Will Hirsch
Email Address:
Faculty mentor/Supervisor:
Michael Wing
Email Address (Faculty mentor/Supervisor):
Department Affiliation:
Forest Engineering Resources & Management
Job Location:
Corvallis
Description of project or research opportunity:
Accurate, efficient survey and characterization of forested, riparian, and aquatic environments is a challenge in monitoring these systems. This research investigates the use of novel mobile terrestrial laser scanning survey and analysis methods across a range of landscapes. The student will have the opportunity to learn terrestrial lidar survey technique, 3D point cloud manipulation and annotation, data management, field measurement, and advanced GIS skills.
Tasks student will perform:
Point cloud object annotation
Training dataset assembly
Lidar survey
Field mensuration
Special skills required:
Geospatial analysis
Forest mensuration
Proposed dates of employment (must be between June 19 and September 4):
Monday, July 1, 2024 to Thursday, August 1, 2024
Anticipated hours worked per week:
20