Thesis
Use of unmanned aerial vehicles to identify topsoil characteristics associated with clandestine graves and buried weapon caches
Masters by Research, Murdoch University
2022
Abstract
Current methods of burial site identification rely heavily on the establishment of an area of interest before they are viable, these areas of interests often come from testimonies of witnesses or persons of interest. Once these areas are established common methods such as line searches are used to locate evidence or burial sites. These methods are often time consuming and require substantial law enforcement resources. Unmanned Aerial Vehicle (UAV) or drone, technology has recently seen rapid development and is becoming both a common recreational hobby as well as a useful commercial tool, with many law enforcement agencies already adopting them for surveillance purposes The aim of this study is to assess the effectiveness of a drone equipped with an unmodified RGB camera being used to locate clandestine graves and buried weapon caches during automated aerial survey flights over a period of four months. The test site was established by creating mock triplicates of both a clandestine grave and a buried weapons cache. A drone was then used to capture a large number of smaller aerial images of the test site at varying intervals after time of burial. These smaller images were then used to create one large orthomosaic image, this orthomosaic image was then analysed by both an algorithm and human participants in attempts to identify the burial sites. Both the algorithm and the human participants can identify burial sites for approximately four months after burial. This aerial survey and subsequent image analysis technique have the potential to drastically reduce the amount of time and resources needed to survey areas of interest in a missing persons or criminal investigation.
Details
- Title
- Use of unmanned aerial vehicles to identify topsoil characteristics associated with clandestine graves and buried weapon caches
- Authors/Creators
- Jackson White
- Contributors
- David Keatley (Supervisor) - Murdoch University, Centre for Biosecurity and One HealthBrendan Chapman (Supervisor) - Murdoch University, School of Medical, Molecular and Forensic Sciences
- Awarding Institution
- Murdoch University; Masters by Research
- Identifiers
- 991005606970207891
- Murdoch Affiliation
- School of Medical, Molecular and Forensic Sciences
- Resource Type
- Thesis
- Note
- Accelerated Masters with Training (aRMT)
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