Automated detection of hillforts in south west England
COLLABORATORS: Dr João Fonte (Co-I) and Dr Ioana Oltean (Archaeology), Professor Leif Isaksen (Digital Humanities) Dr Jacqueline Christmas (Computer Science) (Co-I); Dr Albert Chen (Centre for Water Systems); Jane Galwey (Camborne School of Mines)
IDSAI Research Fellow: Dr Dmitry Kangin
Description: This project uses a machine learning approach to test the automated pattern recognition of, and data enhancement for Iron Age hillforts in South West England based on airborne laser scanning data.
Despite the recognition of their great potential the development of automatic detection methods applied to archaeological remote sensing is still in its infancy and limited to very simple morphologies. However, the increasing availability of remote sensing data of higher resolution, higher acquisition frequency and lower cost, demands a paradigm shift, where traditional man-made identification and mapping of archaeological sites cannot be the only option available.
The project will test the extent to which existing algorithms developed for other purposes can assist the detection in airborne LiDAR datasets of hillforts. The project proposes a meaningful solution to protect archaeological heritage and fight the rate of its destruction due primarily to development and climate change globally. If successful, this approach could be expanded and applied to other case studies involving similar archaeological objects elsewhere; other types of archaeological features; potentially other types of datasets (e.g. multispectral aerial and satellite imagery). This will be highly relevant in particular for cultural heritage management by national and local agencies in Britain and beyond.
