Since camp closure the site has become derelict, and has not been scientifically investigated. This paper reports on the search to locate the PoW escape tunnel that was dug from Hut 9. This hut remains in remarkable condition, with numerous PoW graffiti still present. Also preserved is a prisoner-constructed false wall in a shower room behind which excavated material was hidden, though the tunnel entrance itself has been concreted over. Near-surface geophysics and ground-based LiDAR were used to locate the tunnel. Mid-frequency GPR surveys were judged optimal, with magnetometry least useful due to the above-ground metal objects. Archaeological excavations discovered the intact tunnel and bed-board shoring. With Allied PoW escape camp attempts well documented, this investigation provides valuable insight into German escape efforts.
Across the UK, sandy beaches and dunes protect coastal infrastructure from waves and extreme water levels during large‐scale storms, while providing important habitats and recreational opportunities. Understanding their long‐term evolution is vital in managing their condition in a changing climate. Recently, ground‐penetrating radar (GPR) methods have grown in popularity in geomorphological applications, yielding centimetre‐scale resolution images of near‐surface stratigraphy and structure, thus allowing landscape evolution to be reconstructed. Additionally, abrupt changes in palaeo‐environments can be visualized in three dimensions. Although often complemented by core data, GPR allows interpretations to be extended into areas with minimal ground‐truth control. Nonetheless, GPR data interpretation can be non‐intuitive and ambiguous, and radargrams may not initially resemble the expected subsurface geometry. Interpretation can be made yet more onerous when handling the large 3D data volumes that are facilitated with modern GPR technology. Here we describe the development of novel semi‐automated GPR feature‐extraction tools, based on ‘edge detection’ and ‘thresholding’ methods, which detect regions of increased GPR reflectivity which can be applied to aid in the reconstruction of a range Quaternary landscapes. Since reflectivity can be related to lithological and/or pore fluid changes, the 3D architecture of the palaeo‐landscape can be reconstructed from the features extracted from a geophysical dataset. We present 500 MHz GPR data collected over a buried Holocene coastal dune system in North Wales, UK, now reclaimed for use as an airfield. Core data from the site, reaching a maximum depth 2 m, suggest rapid vertical changes from sand to silty‐organic units, and GPR profiles suggest similar lateral complexity. By applying thresholding methods to GPR depth slices, these lateral complexities are effectively and automatically mapped. Furthermore, automatic extraction of the local reflection power yields a strong correlation with the depth variation of organic content, suggesting it is a cause of reflectivity contrast. GPR‐interpolated analyses away from core control thus offer a powerful proxy for parameters derived from invasive core logging. The GPR data collected at Llanbedr airfield highlight a complex dune system to a depth of 2.8 m, probably deposited in several phases over ~700 years, similar to elsewhere in North Wales.
Phone Number: +44 (0) The last twenty years or so has seen the development of the conflict archaeology 49 and the application of scientific principles to the investigation of sites of battle (see 50 Pollard and Freeman, 2001, and Scott et al., 2007 for overviews, see also Gaffney et 51 al., 2004;Passmore and Harrison 2008;Saunders, 2011;, 2014; Saey et al., 2016), as 52 well as the investigation of the infrastructure and fortifications of war, including 53 trenches, dug-outs, foxholes and tunnels (see, for example, Rosenbaum and Rose, 1992; 54 Doyle et al. 2001 54 Doyle et al. , 2002 54 Doyle et al. , 2005Everett et al. 2006; De Meyer and Pype, 2007; Brown 55 and Osgood 2009;Masters and Stichelbaut, 2009; Banks, 2014; Banks and Pollard, 56 2014; Doyle 2015 Doyle , 2017, hospitals, airfields and logistics (e.g. Dobinson et al. 1997; 57 Schofield, 2001;Passmore et al. 2013; Capps Tunwell et al. 2015) Doyle et al. 2007Doyle et al. , 2010Doyle et al. , 2013Pringle et al. 2007; 59 Doyle 2011; Early 2013; Mytum and Carr, 2013;Schneider 2013). These 60 investigations include investigative archaeology, geophysical surveys as well as the 61 consideration of landscape and topography in relation to battle that has emphasised a 62 growing importance of conflict archaeology and of scientific interpretation informing 63 the understanding of such events. 64As part of the investigations of wartime sites, near-surface, multi-technique 65 geophysical surveys have become increasingly popular (see, for example, Gaffney et al. 66 2004;Everett et al. 2006;Pringle et al. 2007; Fernandez-Alvarez et al. 2016), due to 67 their capability to characterise sites rapidly, as well as pinpointing key buried areas of 68 interest for subsequent intrusive investigations. 69A developing area of interest in conflict archaeology has been the location and 70 characterising of P.O.W. camp escape tunnels, as part of a wider interest in the study of 71 P.O.W. camps (e.g. see Mytum, 2012 and Carr, 2013). 72Underground tunnelling has been a popular method for prisoners to escape confinement 73 for centuries, and particularly so during the two world wars, both of which saw mass 74 internment on a scale not seen before (see, for example, Barbour, 1944;Evans, 1945; 75 Crawley, 1956;Schneck, 1998;Moore, 2006; Doyle 2008 Doyle , 2011 with a large number of accounts published both during and after conflict (Williams 79 1945(Williams 79 , 1949(Williams 79 , 1951Hargest 1946, Brickhill, 1952Reid 1952 Reid , 1956 Burt and Leasor 80 1956;Rogers 1986) with, arguably the so-called 'Great Escape' of 77 Allied P.O.W. 81 airforce officers in 1944 being the most famous (Brickhill, 1952). 82There were generally two types of escape tunnels: (1) relatively short tunnels, 83 excavated quickly to enable small numbers of prisoners to go under camp perimeter 84 fences and escape, and which entailed relatively little work, but which were generally 85 poorly concealed (see Doyle, 2011); and, (2) relatively long tunnels that w...
<p>During the last two decades, ground-penetrating radar (GPR) methods, have grown in popularity for acquiring high-resolution images of the stratigraphy, internal structure and wider context of geomorphology, as well as the reconstruction and evolution of buried landscapes. GPR offers centimetre-scale resolution of the subsurface, allowing 3D visualization of abrupt changes in palaeo-environments. Although often complemented by core data, GPR interpretations can also be extended beyond regions of ground-truth control. However, for all these advantages, GPR data interpretation can be non-intuitive and ambiguous, with the technique seldom giving images that immediately resemble the expected subsurface geometry. Interpretation can be made yet more onerous when handling the large 3D data volumes that are commonly available with modern GPR technology.</p><p>In this paper, we outline the development of a semi-automated GPR feature-extraction tool, based on the image processing techniques &#8216;Edge Detection&#8217; and &#8216;Thresholding&#8217;. Developed initially for medical image analysis, we investigate them as a means of assisting the analysis of GPR data for subsurface geomorphic features. Given that GPR reflectivity can be related to changes in lithology and/or pore fluids, the structure and extent of subsurface depositional environments can be efficiently estimated using these algorithms. When benchmarked against representative core control, the 3D architecture of the palaeo-landscape can be reconstructed from the GPR dataset.</p><p>We present a 500 MHz GPR dataset collected over a buried Holocene coastal dune system in Llanbedr, Gwynedd, North Wales, which has since been reclaimed for use as an airfield. Core data, with maximum depth 2 m, suggest rapid vertical changes from sand to silty-organic units, and GPR profiles suggest that similar lateral complexity is likely across the dataset. By applying thresholding methods to top-down depth slices, the environment is effectively characterised. Furthermore, automatic extraction of the local reflection power with depth yields a strong correlation with the vertical variation of organic content. Similar analyses away from core control could, therefore, deliver a powerful proxy for parameters derived from invasive core logging.</p>
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