Detection of hunting pits using airborne laser scanning and deep learning Visa övriga samt affilieringar
2024 (Engelska) Ingår i: Journal of field archaeology, ISSN 0093-4690, E-ISSN 2042-4582, Vol. 49, nr 6, s. 395-405Artikel i tidskrift (Refereegranskat) 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.
Ort, förlag, år, upplaga, sidor Routledge, 2024. Vol. 49, nr 6, s. 395-405
Nyckelord [en]
Archaeology, forest history, hunting pits, airborne laser scanning, artificial intelligence, deep learning, machine learning
Nationell ämneskategori
Skogsvetenskap Övrig annan samhällsvetenskap Arkeologi
Identifikatorer URN: urn:nbn:se:umu:diva-228297 DOI: 10.1080/00934690.2024.2364428 ISI: 001284888800001 Scopus ID: 2-s2.0-85200442419 OAI: oai:DiVA.org:umu-228297 DiVA, id: diva2:1887545
Forskningsfinansiär Wallenberg AI, Autonomous Systems and Software Program (WASP) Marianne och Marcus Wallenbergs Stiftelse Stiftelsen Marcus och Amalia Wallenbergs minnesfond Kempestiftelserna 2024-08-082024-08-082024-10-24 Bibliografiskt granskad