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Drones 2018, 2(2), 12; https://doi.org/10.3390/drones2020012

Debitage and Drones: Classifying and Characterising Neolithic Stone Tool Production in the Shetland Islands Using High Resolution Unmanned Aerial Vehicle Imagery

1
School of Natural and Built Environment, Queen’s University Belfast, Belfast BT7 1NN, UK
2
School of Archaeology, University College Dublin, Belfield, Dublin 4, Ireland
3
Museum of Archaeology, University of Stavanger, 4036 Stavanger, Norway
*
Author to whom correspondence should be addressed.
Received: 14 February 2018 / Revised: 15 March 2018 / Accepted: 16 March 2018 / Published: 22 March 2018
(This article belongs to the Special Issue (Re)Defining the Archaeological Use of UAVs)
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Abstract

The application of high-resolution imagery from unmanned aerial vehicles (UAV) to classify the spatial extent and morphological character of ground and polished stone tool production at quarry sites in the Shetland Islands is explored in this paper. These sites are manifest as dense concentrations of felsite and artefacts clearly visible on the surface of the landscape. Supervised classification techniques are applied to map material extents in detail, while a topological analysis of surface rugosity derived from an image-based modelling (IBM) generated high-resolution elevation model is used to remotely assess the size and morphology of the material. While the approach is unable to directly characterize felsite as debitage, it successfully captured size and morphology, key indicators of archaeological activity. It is proposed that the classification of red, green and blue (RGB) imagery and rugosity analysis derived from IBM from UAV collected photographs can remotely provide data on stone quarrying processes and can act as an invaluable decision support tool for more detailed targeted field characterisation, especially on large sites where material is spread over wide areas. It is suggested that while often available, approaches like this are largely under-utilized, and there is considerable added value to be gained from a more in-depth study of UAV imagery and derived datasets. View Full-Text
Keywords: UAVs; Neolithic Shetland; quarries; image classification; rugosity; remote characterisation UAVs; Neolithic Shetland; quarries; image classification; rugosity; remote characterisation
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Megarry, W.; Graham, C.; Gilhooly, B.; O’Neill, B.; Sands, R.; Nyland, A.; Cooney, G. Debitage and Drones: Classifying and Characterising Neolithic Stone Tool Production in the Shetland Islands Using High Resolution Unmanned Aerial Vehicle Imagery. Drones 2018, 2, 12.

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