TY - JOUR
T1 - Comparison of Time-Lapse Ground-Penetrating Radar and Electrical Resistivity Tomography Surveys for Detecting Pig (Sus spp.) Cadaver Graves in an Australian Environment
AU - Berezowski, Victoria
AU - Mallett, Xanthé
AU - Seckiner, Dilan
AU - Crebert, Isabella
AU - Ellis, Justin
AU - Rau, Gabriel C
AU - Moffat, Ian
PY - 2024/9/2
Y1 - 2024/9/2
N2 - Locating clandestine graves presents significant challenges to law enforcement agencies, necessitating the testing of grave detection techniques. This experimental study, conducted under Australian field conditions, assesses the effectiveness of time-lapse ground-penetrating radar (GPR) and electrical resistivity tomography (ERT) in detecting pig burials as simulated forensic cases. The research addresses two key questions: (1) observability of graves using GPR and ERT, and (2) changes in geophysical responses with reference to changing climatic conditions. The principal novelty of this research is its Australian focus—this is the first time-lapse GPR and ERT study used to locate clandestine graves in Australia. The results reveal that both GPR and ERT can detect graves; however, ERT demonstrates greater suitability in homogeneous soil and anomalously wet climate conditions, with the detectability affected by grave depth. This project also found that resistivity values are likely influenced by soil moisture and decomposition fluids; however, these parameters were not directly measured in this study. Contrastingly, although GPR successfully achieved 2 m penetration in each survey, the site’s undeveloped soil likely resulted in inconsistent detectability. The findings underscore the significance of site-specific factors when employing GPR and/or ERT for grave detection, including soil homogeneity, climate conditions, water percolation, and body decomposition state. These findings offer practical insights into each technique’s utility as a search tool for missing persons, aiding law enforcement agencies with homicide cases involving covert graves.
AB - Locating clandestine graves presents significant challenges to law enforcement agencies, necessitating the testing of grave detection techniques. This experimental study, conducted under Australian field conditions, assesses the effectiveness of time-lapse ground-penetrating radar (GPR) and electrical resistivity tomography (ERT) in detecting pig burials as simulated forensic cases. The research addresses two key questions: (1) observability of graves using GPR and ERT, and (2) changes in geophysical responses with reference to changing climatic conditions. The principal novelty of this research is its Australian focus—this is the first time-lapse GPR and ERT study used to locate clandestine graves in Australia. The results reveal that both GPR and ERT can detect graves; however, ERT demonstrates greater suitability in homogeneous soil and anomalously wet climate conditions, with the detectability affected by grave depth. This project also found that resistivity values are likely influenced by soil moisture and decomposition fluids; however, these parameters were not directly measured in this study. Contrastingly, although GPR successfully achieved 2 m penetration in each survey, the site’s undeveloped soil likely resulted in inconsistent detectability. The findings underscore the significance of site-specific factors when employing GPR and/or ERT for grave detection, including soil homogeneity, climate conditions, water percolation, and body decomposition state. These findings offer practical insights into each technique’s utility as a search tool for missing persons, aiding law enforcement agencies with homicide cases involving covert graves.
KW - Forensic geophysics
KW - Ground-penetrating radar
KW - Electrical resistivity tomography
KW - Clandestine grave
KW - Missing person
KW - Homicide
UR - http://purl.org/au-research/grants/ARC/LE210100037
UR - http://purl.org/au-research/grants/ARC/DE160100703
UR - http://purl.org/au-research/grants/ARC/FT220100184
U2 - 10.3390/rs16183498
DO - 10.3390/rs16183498
M3 - Article
SN - 2072-4292
VL - 16
JO - Remote Sensing
JF - Remote Sensing
IS - 18
M1 - 3498
ER -