Identification of Burials via GPR Signal Classification and Spatial Cluster Analysis at a Prehistoric Thai Site
Year: 2025
Type: article
Abstract: ABSTRACT Ground‐penetrating radar (GPR) methods are particularly effective at detecting subsurface features with contrasting electromagnetic properties in archaeological contexts. At the undeveloped prehistoric site of Don Up Mung in northeastern Thailand, GPR surveys were conducted to identify potential burial features within the complex stratigraphic sequences characteristic of multiphase settlements. To assess this potential, we employed a MALÅ Easy Locator Pro WideRange HDR GPR system across a 7.5 × 8 m grid adjacent to a previously excavated area containing confirmed burials dated to 571–404 cal. bce . Radar signatures were systematically classified into six distinct trait classes based on their reflection patterns, and local statistic was applied to identify significant spatial clustering. Results revealed prominent GPR anomalies at depths of 0.4–1.2 m (10–30 ns of radar two‐way travel time). The significance maps identified two primary clusters of high‐amplitude reflections in the southwestern portion and one cluster of low‐amplitude reflections in the eastern portion of the survey area. Despite limitations imposed by the spatial offset between survey and excavation areas, the correspondence between anomaly depths and documented burial horizons provides compelling evidence for burial identification. This research establishes a systematic framework that combines GPR signature classification with point pattern analysis to enhance prehistoric burial detection capabilities in similar geological settings, offering valuable guidance for future archaeological investigations at the site.
Source: Archaeological Prospection
DOI: 10.1002/arp.70029
Institutions: Khon Kaen University, Texas A&M University
Language: English
Subfield: Ocean Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W7117382534