Detection of hunting pits using airborne laser scanning and deep learningShow others and affiliations
2024 (English)In: Journal of field archaeology, ISSN 0093-4690, E-ISSN 2042-4582, Vol. 49, no 6, p. 395-405Article in journal (Refereed) Published
Abstract [en]
Forests worldwide contain unique cultural traces of past human land use. Increased pressure on forest ecosystems and intensive modern forest management methods threaten these ancient monuments and cultural remains. In northern Europe, older forests often contain very old traces, such as millennia-old hunting pits and indigenous Sami hearths. Investigations have repeatedly found that forest owners often fail to protect these cultural remains and that many are damaged by forestry operations. Current maps of hunting pits are incomplete, and the locations of known pits have poor spatial accuracy. This study investigated whether hunting pits can be automatically mapped using national airborne laser data and deep learning. The best model correctly mapped 70% of all the hunting pits in the test data with an F1 score of 0.76. This model can be implemented across northern Scandinavia and could have an immediate effect on the protection of cultural remains.
Place, publisher, year, edition, pages
Routledge, 2024. Vol. 49, no 6, p. 395-405
Keywords [en]
Archaeology, forest history, hunting pits, airborne laser scanning, artificial intelligence, deep learning, machine learning
National Category
Forest Science Other Social Sciences not elsewhere specified Archaeology
Identifiers
URN: urn:nbn:se:umu:diva-228297DOI: 10.1080/00934690.2024.2364428ISI: 001284888800001Scopus ID: 2-s2.0-85200442419OAI: oai:DiVA.org:umu-228297DiVA, id: diva2:1887545
Funder
Wallenberg AI, Autonomous Systems and Software Program (WASP)Marianne and Marcus Wallenberg FoundationMarcus and Amalia Wallenberg FoundationThe Kempe Foundations2024-08-082024-08-082024-10-24Bibliographically approved