Data · dataset · 2026
A proposed search strategy for the use of drones in detecting unmarked burials
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Drone detection of clandestine burials is an emerging field lacking a comprehensive dataset that demonstrates detection across complex variables of burial environments.
Description
This study summarises published trends in drone-derived burial signatures and complements them with 20 additional case studies comprising burials in a variety of contexts, which use three primary drone outputs for grave detection: orthomosaics, digital surface models, and vegetation indices.<br><br>Study sites include analogue case studies, which are natural burial sites that act as proxies for clandestine burials; forensic case studies, which imply a criminal element to burial; and historical/archaeological case studies, which involve burials over 100 years old.
These 20 study sites, encompassing over 1,000 burials, include successful detection across three continents, glaciated terrain and residual soils, arctic and equatorial climates, and burial ages from weeks to over 134 years old. In addition, GPR data was collected at seven of these sites to verify drone anomalies.<br><br>Expressions of burial anomalies in each of the three primary drone outputs for all 20 sites are summarised below.
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Anomalies from graves ranging from interment to 107 years old are detected using visual changes in RGB orthomosaics. Burials detected using digital surface models begin as mounds, level out between two and three years post-burial and become depressions detectable up to 134 years. Vegetation indices, such as NDVI, are useful in detecting ground disturbances where bare soil is easily differentiated from healthy vegetation, as well as quantifying the health of pioneer vegetation, which was able to distinguish grave and non-grave vegetation in burials up to 107 years old.<br><br>Lessons learned in the drone search process as well as burial trends established over these 20 sites and published studies are integrated into a Geoforensic Drone Search Protocol, which not only demonstrates a step-by-step guide to conducting clandestine grave searches using drones but serves as a decision-making tool whereby investigators can set expectations, prioritise outputs, conduct necessary desk study and site preparation, and select supplementary search tools.<br><br><i>Thesis embargoed until 31st December 2026</i>.<br>
Links
Where it is published
- DOI doi.org/10.17034/32641566.v1 ↗
DOI / persistent id · from zivahub uct ac za
Catalogue records · 1
- OAI-PMH record api.figshare.com/v2/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Af… ↗
metadata API · from zivahub uct ac za
Topics
- From keywords
- Earth & Environmental Science
- Inferred from text
- Soil sciences 70%
Provenance · 1 source records, 7 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ZivaHub | oai:figshare.com:article/32641566 | 4 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | |
| concepts[field].anzsrc:group:4106 | enrichment · zivahub uct ac za | taxonomy-embedding@1.1.0 | title+keywords+description (70%) |
| concepts[field].local:field:earth-environmental | mapping · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | |
| description | source · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | /metadata/dc/description |
| license_text | source · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | |
| publication_date | source · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | |
| title | source · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | /metadata/dc/title |