title: Geoinformation analysis with the construction of a neural network model for predicting location of archaeological monuments in the landscapes of South-Eastern Altai.
metadata.name: dc.contributor.author
metadata.value: Glebova, Anastasia B.
metadata.lang: -
metadata.name: dc.contributor.author
metadata.value: Sergeev, Igor S.
metadata.lang: -
metadata.name: dc.contributor.author
metadata.value: Bykov, Nikolay I.
metadata.lang: -
metadata.name: dc.date.accessioned
metadata.value: 2022-11-10T19:22:58Z
metadata.lang: -
metadata.name: dc.date.available
metadata.value: 2022-11-10T19:22:58Z
metadata.lang: -
metadata.name: dc.date.issued
metadata.value: 2022-09
metadata.lang: -
metadata.name: dc.identifier.citation
metadata.value: Glebova, A. B., Sergeev, I. S., Bykov, N. I. (2022). Geoinformation analysis with the construction of a neural network model for predicting location of archaeological monuments in the landscapes of South-Eastern Altai. Vestnik of Saint Petersburg University. Earth Sciences, 67 (3), 491–514. https://doi.org/10.21638/spbu07.2022.306 (In Russian)
metadata.lang: en_GB
metadata.name: dc.identifier.other
metadata.value: https://doi.org/10.21638/spbu07.2022.306
metadata.lang: -
metadata.name: dc.identifier.uri
metadata.value: http://hdl.handle.net/11701/38529
metadata.lang: -
metadata.name: dc.description.abstract
metadata.value: This article identifies landscape patterns of the location of archaeological sites in the South-
  East Altai using GIS and machine learning. The information database of archaeological sites
  of South-Eastern Altai was created based on literary sources, the authors’ own field research.
  Schemes of distribution of archaeological sites according to some landscape features: absolute
  height; position in relation to watercourses; slopes; exposition; solar radiation intensity
  in June; Intensities of solar radiation for December was created on the basis of geoinformation analysis of the relief of the territory and the available archaeological data. The obtained
  statistical regularities of the distribution of archaeological sites in the landscapes of
  South-Eastern Altai were the basis for the creation and verification of the algorithm of a
  machine-learning model — a neural network. Based on the results, a forecast map of the
  location of archaeological sites was created. The greatest probability of discovering new archaeological
  objects could be provided by the following landscape parameters, no further
  than 500-600 m from the river with a slope steepness of up to 4 degrees, with high intensity
  and summer (June) solar radiation and with an exposure of slopes: southern, south-eastern
  and western. Unexplored archaeological sites in South-East Altai are most likely located
  along river valleys in the middle and lower reaches, at the confluence of rivers, along the
  periphery of intermountain basins, or on wide flat areas of above-floodplain terraces of river
  valleys. The data obtained make it possible to assess the contribution of landscape features
  to the spatial distribution of religious buildings of ancient peoples and provide opportunities
  for the search for new archaeological sites.
metadata.lang: en_GB
metadata.name: dc.description.sponsorship
metadata.value: The collection of materials was carried out within the framework of the state task of the Institute of
  Water and Environmental Problems of the Siberian Branch of the Russian Academy of Sciences “Natural
  and natural-economic systems of Siberia in the face of modern challenges: diagnostics of conditions,
  adaptive capabilities, potential of ecosystem services” (No. 0306-2021-0007). Analytical work was carried
  out with the financial support of the Russian Foundation for Basic Research grant project No. 19-05-00535
  “Natural disasters and landscape transformation of southeastern Altai and northwestern Mongolia since the
  maximum of the last glaciation”.
metadata.lang: en_GB
metadata.name: dc.language.iso
metadata.value: ru
metadata.lang: en_GB
metadata.name: dc.publisher
metadata.value: St Petersburg State University
metadata.lang: en_GB
metadata.name: dc.relation.ispartofseries
metadata.value: Vestnik of St Petersburg University. Earth Sciences;Volume 67; Issue 3
metadata.lang: -
metadata.name: dc.subject
metadata.value: landscape
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: archaeological sites
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: geographic information systems
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: DEM
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: neural network
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: South-Eastern Altai
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: Altai Mountains
metadata.lang: en_GB
metadata.name: dc.title
metadata.value: Geoinformation analysis with the construction of a neural network model for predicting location of archaeological monuments in the landscapes of South-Eastern Altai.
metadata.lang: en_GB
metadata.name: dc.type
metadata.value: Article
metadata.lang: en_GB
resources.filename: 06.pdf
resources.url: https://dspace.spbu.ru/bitstream/11701/38529/1/06.pdf
resources.format: Adobe PDF
resources.size: 13,31 MB