Advancing marine biodiversity monitoring methods: Digital survey techniques and machine learning approaches for automated detection of animal individuals Weiterentwicklung der Erfassungsmethoden im marinen Biodiversitätsmonitoring – digitale Surveymethoden und Machine-Learning-Techniken für eine automatisierte Detektion von Tierindividuen
Hauswirth M, Sommer C, Seuret M (2026)
Publication Type: Journal article
Publication year: 2026
Book Volume: 101
Pages Range: 138-145
Journal Issue: 3-4
Abstract
In order to effectively monitor marine conservation assets, survey methods need to be optimised continuously. The growing use of offshore wind energy, in particular, poses new challenges to traditional monitoring methods of marine vertebrates, especially when this monitoring is conducted by means of aerial surveys through observers in aircraft and data is analysed manually. The German Federal Agency for Nature Conservation (BfN) is therefore employing digital monitoring methods, such as aircraft-based aerial imagery, and is developing automated marine species detection using machine learning as part of an ongoing research project. This article outlines the development and evaluation of innovative digital methods for classifying seabirds and marine mammals in aerial photographs. By applying heuristic approaches and deep learning technologies, efficient and cost-effective monitoring can be achieved in the future, ensuring the long-term availability of robust data on the size and spatial and temporal distribution of marine vertebrate populations as well as the assessment of human impacts on marine ecosystems. The study also examines the future role of automated monitoring methods.
Authors with CRIS profile
Christian Sommer
Institut für Geographie
Mathias Seuret
Lehrstuhl für Informatik 5 (Mustererkennung)
Involved external institutions
Germany (DE)How to cite
APA:
Hauswirth, M., Sommer, C., & Seuret, M. (2026). Advancing marine biodiversity monitoring methods: Digital survey techniques and machine learning approaches for automated detection of animal individuals Weiterentwicklung der Erfassungsmethoden im marinen Biodiversitätsmonitoring – digitale Surveymethoden und Machine-Learning-Techniken für eine automatisierte Detektion von Tierindividuen. , 101(3-4), 138-145. https://doi.org/10.19217/NuL2026-03-05
MLA:
Hauswirth, Mirko, Christian Sommer, and Mathias Seuret. "Advancing marine biodiversity monitoring methods: Digital survey techniques and machine learning approaches for automated detection of animal individuals Weiterentwicklung der Erfassungsmethoden im marinen Biodiversitätsmonitoring – digitale Surveymethoden und Machine-Learning-Techniken für eine automatisierte Detektion von Tierindividuen." 101.3-4 (2026): 138-145.
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