Application of convolutional neural networks on digital terrain models for analyzing spatial relations in archaeology

  • Archaeological research is increasingly embedding individual sites in archaeological contexts and aims at reconstructing entire historical landscapes. In doing so, it benefits from technological developments in the field of archaeological prospection over the last 20 years, including LiDAR-based Digital Terrain Models, special visualizations, and automated site detection. The latter can generate comprehensive datasets with manageable effort that are useful for answering large-scale archaeological research questions. This article presents a highly automated workflow, in which a Convolutional Neural Network is used to detect burial mounds in the proximity of remotely located hollow ways. Detected mounds are then analyzed with respect to their distribution and a possible spatial relation to hollow ways. The detection works well, produces a reasonable number of results, and achieved a precision of at least 77%. The distribution of mounds shows a clear maximum in the radius of 2000–2500 m. This supports future research such as visibility or cost path analysis.

Download full text files

Export metadata

Additional Services

Share in Twitter Search Google Scholar
Metadaten
Author:Matthias Fabian Meyer-HeßORCiDGND, Ingo PfefferGND, Carsten JürgensORCiDGND
URN:urn:nbn:de:hbz:294-102175
DOI:https://doi.org/10.3390/rs14112535
Parent Title (English):Remote sensing
Publisher:MDPI
Place of publication:Basel, Schweiz
Document Type:Article
Language:English
Date of Publication (online):2023/09/29
Date of first Publication:2022/05/25
Publishing Institution:Ruhr-Universität Bochum, Universitätsbibliothek
Tag:Open Access Fonds
CNN; LiDAR; automated detection; burial mound; hollow way; landscape archaeology
Volume:14
Issue:11, Article 2535
First Page:2535-1
Last Page:2535-16
Note:
Article Processing Charge funded by the Deutsche Forschungsgemeinschaft (DFG) and the Open Access Publication Fund of Ruhr-Universität Bochum.
Institutes/Facilities:Geographisches Institut
Geographisches Institut, Arbeitsgruppe Geomatik
Dewey Decimal Classification:Naturwissenschaften und Mathematik / Geowissenschaften, Geologie
open_access (DINI-Set):open_access
faculties:Fakultät für Geowissenschaften
Licence (English):License LogoCreative Commons - CC BY 4.0 - Attribution 4.0 International