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Journal on Computing and Cultural Heritage
Article . 2026 . Peer-reviewed
License: CC BY
Data sources: Crossref
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Extracting Linear Features in Archaeological Contexts

Authors: Ivan Gutierrez; Roderik Lindenbergh; Lisa Watson; Kim Shelton;

Extracting Linear Features in Archaeological Contexts

Abstract

The detection and recording of tens to hundreds of centimeter-scale features in archaeological sites represent a challenge in data collection during field work. Traditionally, archaeological field documentation relies on sketches and line drawings made by hand. Sensors facilitate the characterization, mapping, and quantification of millimetre-scale features, which are otherwise difficult to detect with the naked eyes. High-resolution terrestrial laser scanning is an optimal method for documenting cultural heritage sites due to its transportability and efficient collection time, while processed 3D models facilitate detailed analysis. To demonstrate this approach, a Late Bronze Age Mycenaean cemetery in Greece was selected as a study site due to its size and active excavation status despite ongoing looting activities. The cemetery consists of several chamber tombs, which were hewn from a soft marl hillside using sharp tools. Chisel marks were observed in one of the chamber tombs. The cemetery was surveyed, resulting in point clouds with 0.7 mm spacing. The resulting 3D point cloud model was analyzed as a proof of concept to test the semi-automatic detection of the observed chisel marks. Two separate, but complementary methods, were applied to one surveyed tomb, resulting in the identification of 39 chisel marks divided into four linear feature families. Future work can improve the efficiency of detection as well as further classification of features, especially in sites where natural and anthropogenic features need differentiation or to reconstruct the sequence in which features were created.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average