What lies beneath? Machine learning and imaging of lichen-covered surfaces at Stonehenge to reveal rock art

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• 批准号: 1930971
• 金额: --
• 依托单位: University of Brighton
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2017
• 资助国家: 英国
• 起止时间: 2017 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-1930971
• 关键词: What; lies; beneath; Machine; learning

A quarter of the stone surface of Stonehenge is inaccessible to conventional archaeological survey techniques such as laser scanning due to the dense coverage of lichen. This project will aim to: (i) create a novel method, combining machine learning and surface imaging techniques such as photogrammetry, to reveal carvings that may be hidden by lichen covered stone surfaces; and (ii) verify any findings using a subsurface imaging technique such as terahertz imaging. The project will answer the question of whether there are more prehistoric rock carvings hidden by lichen on Stonehenge, and whether, with only an understanding of the topography of the lichen, we can find these carvings.The results will be of use for further unravelling archaeological detail at Stonehenge, and aid conservation, presentation and management of the site. Outcomes will have wider applicability as a rapid non-invasive technique for measuring and monitoring the microtopography of vegetation-covered stone surfaces at other monuments and historic buildings.

由于地衣覆盖，巨石阵四分之一的石头表面无法通过激光扫描等传统考古调查技术到达。该项目的目标是：（i）创建一种新颖的方法，将机器学习和表面成像技术（例如摄影测量）相结合，以揭示可能隐藏在地衣覆盖的石头表面的雕刻； (ii) 使用太赫兹成像等地下成像技术验证任何发现。该项目将回答巨石阵上是否存在更多被地衣隐藏的史前岩刻，以及仅了解地衣地形是否能找到这些石刻的问题。研究结果将有助于进一步揭示巨石阵的考古细节，并有助于该遗址的保护、展示和管理。作为一种快速非侵入性技术，其成果将具有更广泛的适用性，用于测量和监测其他纪念碑和历史建筑的植被覆盖的石头表面的微地形。