Research digital skills training 2021
Rapid monitoring of infrastructural health using remote sensing
Dr Lucas Hogan. Lecturer, Dr Max Stephens, Lecturer, Civil and Environmental Engineering, Dr Chris Seal, Centre for eResearch
Aotearoa, New Zealand, and the Ring of Fire
Located on the Pacific ‘Ring of Fire’, Aotearoa is a seismically active country, experiencing on the order of 15,000 earthquakes every year. While only a small fraction of these is large enough to be felt, this still leads to around 100 earthquakes of this magnitude every year. Historically, several magnitude 6 earthquakes can be expected to affect Aotearoa, New Zealand every year. (https://www.gns.cri.nz/Home/Learning/Science-Topics/Earthquakes/New-Zealand-Earthquakes).
Photogrammetry is defined as the science and technology of making measurements using photographic images and has found use across the electromagnetic spectrum. With appropriate calibration, accurate measurements of surface features can be made and there are a range of software tools that can be used to facilitate this process.
Structural damage assessment
Research in the Faculty of Engineering is leveraging photogrammetry and remote sensing platforms, specifically cameras mounted on drones, to enable rapid monitoring of damage to infrastructure in response to this challenge. Images captured by these drones can be compiled to form a 3D model of the structure complete with evidence of surface damage that is indicative of the state of health of the structure assessed. This requires the use of software and GPU-enabled compute to create the 3D model which is often beyond the capabilities of a typical desktop. Once 3D reconstruction is completed, these models can then be exported and traditional image processing techniques can be utilized to identify cracks and other damage.
Open source software and GPU enabled compute
Drone in use capturing images for reconstruction.
Overview of the crack detection process
Crack detections at different tolerance levels, using the Canny Method
Face rendered from 3D reconstruction using Blender