Integration of ground-based and remote sensing data with deep learning algorithms for mapping habitats in Natura 2000 protected oak forests

Integration of ground-based and remote sensing data with deep learning algorithms for mapping habitats in Natura 2000 protected oak forests

Landscape changes caused by climate change require new methods for forest research, analysis, mapping, and monitoring. This study aims to combine ground-based and remote sensing data utilising deep learning techniques to map protected forest habitats and communities within the Natura 2000 network. T...

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Bibliographic Details
Main Authors: Lucia Čahojová, Ivan Jarolímek, Barbora Klímová, Michal Kollár, Michaela Michalková, Karol Mikula, Aneta A. Ožvat, Denisa Slabejová, Mária Šibíková
Format: Article
Language:English
Published: Elsevier 2025-03-01
Series:Basic and Applied Ecology
Subjects:
Earth observation
Habitat mapping
Natural numerical network
Natura 2000
Quercus cerris
Online Access:http://www.sciencedirect.com/science/article/pii/S1439179125000064
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