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Abstract:In this paper, we report the results of our work on automated detection of qanat shafts on the Cold War-era CORONA Satellite Imagery. The increasing quantity of air and space-borne imagery available to archaeologists and the advances in computational science have created an emerging interest in automated archaeological detection. Traditional pattern recognition methods proved to have limited applicability for archaeological prospection, for a variety of reasons, including a high rate of false positives. Since 2012, however, a breakthrough has been made in the field of image recognition through deep learning. We have tested the application of deep convolutional neural networks (CNNs) for automated remote sensing detection of archaeological features. Our case study is the qanat systems of the Erbil Plain in the Kurdistan Region of Iraq. The signature of the underground qanat systems on the remote sensing data are the semi-circular openings of their vertical shafts. We choose to focus on qanat shafts because they are promising targets for pattern recognition and because the richness and the extent of the qanat landscapes cannot be properly captured across vast territories without automated techniques. Our project is the first effort to use automated techniques on historic satellite imagery that takes advantage of neither the spectral imagery resolution nor very high (sub-meter) spatial resolution.Keywords: remote sensing; archaeology; qanat; karez; deep learning; convolutional neural networks (CNNs); image segmentation; CORONA; Kurdistan Region of Iraq (KRG)

Therefore, the key to generating frigid temperatures seems to be that there are very few cracks at the base of the thick structure below, but there is a significant air gap above the qanat (a water management system used to provide a reliable supply of water to human settlements or for irrigation in hot, arid and semi-arid climates). A qanat has quite a lot of water inside, because there are frequent well-like reservoirs along its path. Completely shaded from the sun, a qanat also aggregates the cold, sinking air of the night, which is then trapped within, unable to rise up to the less dense surface air. A windcatcher, however, can create a pressure gradient which sucks at least a small amount of air upwards through a house. This cool, dry night air, being pulled over a long passage of water, evaporates some of it and is cooled down further.

Over the last 30 years, the use of thermoplastic adhesives has become an established choice of treatment in the support of fragile textiles. During that time, the Textile Conservation Section at the Victoria and Albert Museum has evolved an expertise in the application of the poly (vinyl acetate) emulsion Mowilith DMC2 when such a treatment is appropriate. The methods of application are continually being refined. The recent conservation of an early 18th century chintz qanat for the Nehru Gallery of Indian Art afforded an opportunity to clarify thinking about the use of adhesive techniques and to further refine methods, in particular, the use of low pressures on the vacuum hot table.

The qanat (Museum no. IM29 1928) is one panel, measuring 71 by 217 cm, cut from a larger length of repeated niches which would have formed a tent wall (Fig.1). Off-set from the centre there is a vertical seam made with long loose running stitches along the selvedge allowances of two part loom-widths of plain weave cotton. The chintz design is made in the traditional kalamkari technique of printing, mordant dyeing and overpainting to produce a predominance of red and green with purple, brown and yellow, the natural ground of the cotton left to depict the main motifs of the irises and surrounding flowers.

To use a stitching technique alone to support the qanat would only cause more disintegration of the degraded brown and purple motifs and leave them vulnerable to further deterioration: the passage of a needle through these would invariably break u