0546213 - ÚTIA 2022 RIV CH eng C - Conference Paper (international conference)
Moudrá, A. - Haindl, Michal
Underground Archeological Structures Detection.
Advances in Computational Collective Intelligence. Cham: Springer International Publishing, 2021 - (Wojtkiewicz, K.; Treur, J.; Pimenidis, E.; Maleszka, M.), s. 690-702, č. článku 56. Communications in Computer and Information Science, 1463. ISBN 978-3-030-88113-9. ISSN 1865-0929.
[International Conference on Computational Collective Intelligence 2021 /13./. Kallithea, Rhodes (GR), 29.09.2021-01.10.2021]
R&D Projects: GA ČR(CZ) GA19-12340S
Institutional support: RVO:67985556
Keywords : Remote sensing archeology * underground heritage site recognition * aerial image-based automated site detection
OECD category: Communication engineering and systems
Result website:
http://library.utia.cas.cz/separaty/2021/RO/haindl-0546213.pdf

DOI: https://doi.org/10.1007/978-3-030-88113-9_56

This paper introduces and compares three approaches for automatic archaeological heritage site detection hidden under soil cover from public aerial images. The methods use low quality public aerial RGB spectral data restricted by the land-use map to agricultural regions in the vegetation season to detect underground structure influencing plants growing on the surface soil layer.
Permanent Link: http://hdl.handle.net/11104/0323756