The application of high-resolution imagery from unmanned aerial vehicles (UAV) to\nclassify the spatial extent and morphological character of ground and polished stone tool production\nat quarry sites in the Shetland Islands is explored in this paper. These sites are manifest as dense\nconcentrations of felsite and artefacts clearly visible on the surface of the landscape. Supervised\nclassification techniques are applied to map material extents in detail, while a topological analysis of\nsurface rugosity derived from an image-based modelling (IBM) generated high-resolution elevation\nmodel is used to remotely assess the size and morphology of the material. While the approach is\nunable to directly characterize felsite as debitage, it successfully captured size and morphology, key\nindicators of archaeological activity. It is proposed that the classification of red, green and blue (RGB)\nimagery and rugosity analysis derived from IBM from UAV collected photographs can remotely\nprovide data on stone quarrying processes and can act as an invaluable decision support tool for\nmore detailed targeted field characterisation, especially on large sites where material is spread over\nwide areas. It is suggested that while often available, approaches like this are largely under-utilized,\nand there is considerable added value to be gained from a more in-depth study of UAV imagery and\nderived datasets.
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