Alawadhi, A (2024) The Detection of Simulated Clandestine Graves in an Arid Environment Using Unmanned Aerial Vehicle Remote Sensing. Doctoral thesis, Liverpool John Moores University.

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Abstract

The Middle East has frequently suffered from armed conflicts that resulted in mass burials. However, the detection of graves in such an arid environment by deploying remote sensing payload on unmanned aerial vehicles (UAVs) has received little attention. This study used UAVs equipped with different sensors aimed at narrowing down the search area of possible simulated gravesites. It sought to detect variation in topsoil temperature and soil moisture between the simulated graves and their surroundings, detect surface anomalies both manually and automatically, find grave mounds using the digital elevation model and evaluate the use of normalised difference vegetation index (NDVI) in grave detection. The enclosed research area included both control and experimental graves and was imaged for 18 months. The results demonstrated the effectiveness of thermal imaging in detecting heat produced from buried sheep carcasses and detecting the change in grave soil moisture for 7 and 10 months, respectively. Moreover, the buried animals significantly influenced the topsoil temperature of the mass graves (p = 0.044). Meanwhile, the anomaly detection was possible for up to 18 months. Near-IR and red-edge bands were the most suitable for the manual detection (Near-IR 66.66%, red-edge 33.33%), whilst the best-performing automated method varied depending on the sensor used. Standard RXD (RXD) and Uniform Target Detector (UTD) algorithms were the most suitable methods for the RGB sensor (RXD 56.25%, UTD 43.75%). The best outcomes for the multispectral sensor were obtained using Hybrid of the RXD and UTD algorithms (RXD-UTD) (60%), UTD (26.67%) and RXD (13.33%). Despite the fact that the research took place in a very hot and dry environment, a high (0.33) difference in NDVI values was observed between the graves and their surroundings. The results from these cost-and time- effective search methods presented in this study affirm their potential for detecting burial sites in an arid environment.

Item Type:	Thesis (Doctoral)
Uncontrolled Keywords:	forensic anthropology; remote sensing; UAV; burial detection; graves
Subjects:	G Geography. Anthropology. Recreation > GN Anthropology T Technology > T Technology (General) > T58.5 Information Technology
Divisions:	Biological & Environmental Sciences (from Sep 19)
SWORD Depositor:	A Symplectic
Date Deposited:	08 Jan 2024 13:44
Last Modified:	08 Jan 2024 13:44
DOI or ID number:	10.24377/LJMU.t.00022211
Supervisors:	Eliopoulos, C and Bezombes, F
URI:	https://researchonline.ljmu.ac.uk/id/eprint/22211

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