Ballistic impact crater modelling using UAV and structure from motion technology : 2012 Te Maari volcanic eruptions, New Zealand
| dc.contributor.author | Pitchika, Ravitej | |
| dc.date.accessioned | 2017-08-01T04:01:02Z | |
| dc.date.available | 2017-08-01T04:01:02Z | |
| dc.date.issued | 2017 | en |
| dc.description.abstract | New Zealand has a strong historical background of producing volcanic eruptions and earthquakes due to its geographical setting. The deformation caused by the collision of Australian and Pacific plates has given rise to New Zealand’s volcanism. Most of NZ’s volcanism has occurred in the Taupo Volcanic Zone (TVZ) in the last 1.6 million years. On 6th August 2012, Upper Te Maari volcanic eruptions occurred on the north-eastern flanks of Tongariro volcano complex, in TVZ region producing a hazard from volcanic ballistic projectiles. The vulnerability of people walking along the Tongariro Alpine Crossing to ballistic impacts was identified by (Fitzgerald, 2014) and the hazard was calculated by remote and field mapping of ballistic craters. This project examines the effectiveness and accuracy of mapping a volcanic crater field near Tongariro, using a Draganfly X4P un-manned aerial vehicle (UAV). The UAV is flown at different elevations above the ground surface to capture the two-dimensional ground images. The UAV imagery datasets and ground truthing survey points are incorporated to Agisoft Photoscan Pro software to build a three-dimensional elevation model, using Structure from motion (SfM) and photogrammetry technology. The use of UAV’s and SfM to study geohazards is a new concept which could prove an alternative to the more expensive Light Detection and Ranging (LiDAR) surveys. The digital elevation models (DEMs) developed in SfM photogrammetric software were used to identify volcanic craters within a 100 m2 survey site selected for this project. A model was built using six different parameters, to distinguish volcanic craters from natural depressions on the ground surface. The UAV’s imagery resolution, altitude of the flight and other atmospheric factors play a crucial role to the accuracy of the results. A total of 135 volcanic craters were identified with 118 pixels per centimetre (ppcm), when the UAV was flown at 40m altitude above the ground surface. When the resolution of images was reduced to 70 ppcm manually, only 101 volcanic craters could be identified successfully. A LiDAR is a remote sensing method used to measure variable distances to the Earth that uses near infrared pulsed laser to map the topographic land surface. A LiDAR and aerial imagery survey was first conducted by NZ Aerial Mapping in November 2012, three months after the 2012 Te Maari volcanic eruptions. Out of the total 3587 volcanic craters yielded from LiDAR and orthophoto analysis, 107 craters fall within the 100 m2 survey site chosen in for this project (Fitzgerald, 2014).The UAV and SfM modelling identified more craters (135) four years post 2012 Te Maari eruptions. This thesis found that UAV’s are both feasible and cost-effective when used in this context; however, the major limiting factor is the small area covered by a UAV when compared to LiDAR surveys. Hence, the SfM and UAV technology can therefore be used at localized sites to achieve maximized results with cost effective measures, when compared to conducting LiDAR surveys. | en |
| dc.identifier.uri | http://hdl.handle.net/10092/13752 | |
| dc.identifier.uri | http://dx.doi.org/10.26021/5664 | |
| dc.language | English | |
| dc.language.iso | en | |
| dc.publisher | University of Canterbury | en |
| dc.rights | All Rights Reserved | en |
| dc.rights.uri | https://canterbury.libguides.com/rights/theses | en |
| dc.title | Ballistic impact crater modelling using UAV and structure from motion technology : 2012 Te Maari volcanic eruptions, New Zealand | en |
| dc.type | Theses / Dissertations | en |
| thesis.degree.discipline | Geography | |
| thesis.degree.grantor | University of Canterbury | en |
| thesis.degree.level | Masters | en |
| thesis.degree.name | Master of Geographic Information Science | en |
| uc.bibnumber | 2498374 | |
| uc.college | Faculty of Science | en |