Search, Detect, Recover: A Systematic Review of UAV-Based Remote Sensing Approaches for the Location of Human Remains and Clandestine Graves

Several approaches are currently being used by law enforcement to locate the remains of victims. Yet, traditional methods are invasive and time-consuming. Unmanned Aerial Vehicle (UAV)-based remote sensing has emerged as a potential tool to support the location of human remains and clandestine graves. While offering a non-invasive and low-cost alternative, UAV-based remote sensing needs to be tested and validated for forensic case work. To assess current knowledge, a systematic review of 19 peer-reviewed articles from four databases was conducted, focusing specifically on UAV-based remote sensing for human remains and clandestine grave location. The findings indicate that different sensors (colour, thermal, and multispectral cameras), were tested across a range of burial conditions and models (human and mammalian). While UAVs with imaging sensors can locate graves and decomposition-related anomalies, experimental designs from the reviewed studies lacked robustness in terms of replication and consistency across models. Trends also highlight the potential of automated detection of anomalies over manual inspection, potentially leading to improved predictive modelling. Overall, UAV-based remote sensing shows considerable promise for enhancing the efficiency of human remains and clandestine grave location, but methodological limitations must be addressed to ensure findings are relevant to real-world forensic cases.

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Publication Details

Journal
Drones
Published
2025-09-26
DOI
https://doi.org/10.3390/drones9100674
Citations
1
Primary Topic
Archaeological Research and Protection
Type
article
Field-Weighted Citation Impact
7.46

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article

Search, Detect, Recover: A Systematic Review of UAV-Based Remote Sensing Approaches for the Location of Human Remains and Clandestine Graves

Heather Panter, T. Komang Ralebitso-Senior, Frédéric Bezombes, Kirstie Scott et al.
1 citations
Drones
Archaeological Research and Protection
7.46
article

Search, Detect, Recover: A Systematic Review of UAV-Based Remote Sensing Approaches for the Location of Human Remains and Clandestine Graves

Heather Panter, T. Komang Ralebitso-Senior, Frédéric Bezombes, Kirstie Scott, Cherene de Bruyn
article en
1 citations

Abstract

Several approaches are currently being used by law enforcement to locate the remains of victims. Yet, traditional methods are invasive and time-consuming. Unmanned Aerial Vehicle (UAV)-based remote sensing has emerged as a potential tool to support the location of human remains and clandestine graves. While offering a non-invasive and low-cost alternative, UAV-based remote sensing needs to be tested and validated for forensic case work. To assess current knowledge, a systematic review of 19 peer-reviewed articles from four databases was conducted, focusing specifically on UAV-based remote sensing for human remains and clandestine grave location. The findings indicate that different sensors (colour, thermal, and multispectral cameras), were tested across a range of burial conditions and models (human and mammalian). While UAVs with imaging sensors can locate graves and decomposition-related anomalies, experimental designs from the reviewed studies lacked robustness in terms of replication and consistency across models. Trends also highlight the potential of automated detection of anomalies over manual inspection, potentially leading to improved predictive modelling. Overall, UAV-based remote sensing shows considerable promise for enhancing the efficiency of human remains and clandestine grave location, but methodological limitations must be addressed to ensure findings are relevant to real-world forensic cases.

DronesVol. 9(10)
Liverpool John Moores University (GB)
Liverpool John Moores University
Openalex Percentile: Top 4%
Archaeological Research and Protection
7.46
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Search, Detect, Recover: A Systematic Review of UAV-Based Remote Sensing Approaches for the Location of Human Remains and Clandestine Graves — Heather Panter, T. Komang Ralebitso-Senior, et al. · Drones (2025) | TGRS Research Map | TGRS