{"id":{"repo_id":"bradford","oai_identifier":"oai:bradscholars.brad.ac.uk:10454/19275"},"canonical_url":"https://search.dev.ndltd.org/etd/bradford/oai:bradscholars.brad.ac.uk:10454/19275","repository":{"repo_id":"bradford","name":"University of Bradford","base_url":"https://bradscholars.brad.ac.uk/oai/request"},"display":{"title":"Analysis and pattern mapping of organic interfaces by means of seismic geophysical technologies to investigate archaeological palaeolandscapes beneath the Southern North Sea","abstract":"Investigating the archaeology of submerged landscapes beneath many metres of sea and buried under modern sands requires an understanding of the terrestrial surface as it may have been prior to the inundation. To do this, environmental evidence is required from contextualised in-situ locations and the best material evidence for preservation of archaeology, organic remains, dating proxies, pollen, diatoms, microfossils, coleoptera etc. is peat. This research supports the search for peat in submarine environments by interpreting seismic surveys of the sub-sea floor and analysing reflective signals for distinctive organic responses. By means of sedimental analysis and ground observation, the research sets out to differentiate between organic signals, to allow for the identification and location of shallow peat beds within features of a palaeolandscape. Using these results should provide an opportunity to target such peat beds in an archaeologically focused coring programme. The research also examines ways in which organic responses may be mapped over larger areas in order to integrate the results into a wider scale landscape model identifying potential peatland, marsh, valley fen and lowland areas. Finally, the research introduces an artificial intelligence neural networking technology for the identification of organic interfaces in seismic surveys, examining three different ways in which this could be accomplished using specialist computer tools and software.","abstract_html":"Investigating the archaeology of submerged landscapes beneath many metres of sea and buried under modern sands requires an understanding of the terrestrial surface as it may have been prior to the inundation. To do this, environmental evidence is required from contextualised in-situ locations and the best material evidence for preservation of archaeology, organic remains, dating proxies, pollen, diatoms, microfossils, coleoptera etc. is peat. This research supports the search for peat in submarine environments by interpreting seismic surveys of the sub-sea floor and analysing reflective signals for distinctive organic responses. By means of sedimental analysis and ground observation, the research sets out to differentiate between organic signals, to allow for the identification and location of shallow peat beds within features of a palaeolandscape. Using these results should provide an opportunity to target such peat beds in an archaeologically focused coring programme. The research also examines ways in which organic responses may be mapped over larger areas in order to integrate the results into a wider scale landscape model identifying potential peatland, marsh, valley fen and lowland areas. Finally, the research introduces an artificial intelligence neural networking technology for the identification of organic interfaces in seismic surveys, examining three different ways in which this could be accomplished using specialist computer tools and software.","abstract_has_math":false,"creators":["Fraser, Andrew I."],"institution":"University of Bradford","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Gaffney, Vincent","Fitch, Simon"],"committee_chairs":[],"committee_members":[],"year":2021,"date_issued":"2021","date_published":"2021","updated_at":"2026-07-24T01:13:22Z","subjects":["Archaeology","Environment","Sea-level","Palaeolandscape","Seismic","Marine geophysics","Peat","Holocene","Mesolithic","Submerged landscapes","Seismic surveys"],"languages":["en"],"rights":["\"Creative
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