The application of low-altitude near-infrared aerial photography for detecting clandestine burials using a UAV and low-cost unmodified digital camera

Aerial photography and remote sensing has been carried out in the past by numerous different platforms, utilizing imaging from across the electromagnetic (EM) spectrum to gain information about the earth. These techniques have additionally been found effective when locating mass graves and single clandestine graves created by perpetrators when concealing homicide victims. Applications for performing aerial photography and remote sensing are costly and therefore usually overlooked by police investigators, resulting in employing more contemporary geophysical methods for locating burials. Recent advances in technology however have seen the development of small Unmanned Aerial Vehicles (UAVs) for aerial photography which can be executed at low altitude and controlled remotely from the surface. This development has introduced low-cost approaches in detecting surface features, commonly utilised in the archaeological field for its accuracy in detecting anomalies, particularly when using near-infrared (NIR) photography. NIR aerial images have been shown to expose cropmarks of historical value which are unnoticeable in conventional colour photography, deriving from the visual area of the EM spectrum. However, little attempt has been made to investigate the practice of NIR photography to detect clandestine graves using low-cost aerial platforms in the form of UAVs. This paper considers adopting a low-cost and non-invasive approach to detect clandestine graves through the implementation of a small UAV and an unmodified GoPro camera fixed with a near-infrared filter. The results presented here have recognised real-time suitability for using UAVs as an aerial photographic platform in the forensic archaeological field as well as noting the advantage of NIR photography as an ongoing technique for discriminating recent graves from their surroundings. Crown Copyright (c) 2018 Published by Elsevier B.V. All rights reserved.