Articles | Volume 21, issue 6
https://doi.org/10.5194/bg-21-1411-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-21-1411-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
19 Mar 2024
Research article |
| 19 Mar 2024
| 19 Mar 2024
Synergistic use of Sentinel-2 and UAV-derived data for plant fractional cover distribution mapping of coastal meadows with digital elevation models
Institute of Agriculture and Environmental Sciences, Estonian University of Life Sciences, Kreutzwaldi 5, 51006 Tartu, Estonia
Miguel Villoslada
Department of Geographical and Historical Studies, University of Eastern Finland, P.O. Box 111, 80101 Joensuu, Finland
Institute of Agriculture and Environmental Sciences, Estonian University of Life Sciences, Kreutzwaldi 5, 51006 Tartu, Estonia
Raymond D. Ward
Institute of Agriculture and Environmental Sciences, Estonian University of Life Sciences, Kreutzwaldi 5, 51006 Tartu, Estonia
School of Geography, Queen Mary University of London, London E1 4NS, UK
Thaisa F. Bergamo
Institute of Agriculture and Environmental Sciences, Estonian University of Life Sciences, Kreutzwaldi 5, 51006 Tartu, Estonia
Department of Geographical and Historical Studies, University of Eastern Finland, P.O. Box 111, 80101 Joensuu, Finland
Chris B. Joyce
Institute of Agriculture and Environmental Sciences, Estonian University of Life Sciences, Kreutzwaldi 5, 51006 Tartu, Estonia
JBA Consulting, Haywards Heath, East Sussex, UK
Kalev Sepp
Institute of Agriculture and Environmental Sciences, Estonian University of Life Sciences, Kreutzwaldi 5, 51006 Tartu, Estonia
Related authors
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Alexander Störmer, Timo Kumpula, Miguel Villoslada, Pasi Korpelainen, Henning Schumacher, and Benjamin Burkhard
The Cryosphere, 19, 3949–3970, https://doi.org/10.5194/tc-19-3949-2025, https://doi.org/10.5194/tc-19-3949-2025, 2025
Short summary
Short summary
Snow has a major impact on palsa dynamics, yet our understanding of its distribution at the small scale remains limited. We used unoccupied aerial system (UAS) light detection and ranging (lidar) and ground truth data in combination with machine learning to model snow distribution at three palsa sites. We identified extremes in snow depth corresponding to palsa topography, providing insights into the influence of the distribution on their dynamics. The results demonstrate the usability of machine learning and UAS lidar for small-scale snow distribution mapping.
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Short summary
Despite hosting a wide range of ecosystem services, coastal wetlands face threats from global changes. This study models the plant fractional cover of plant communities in Estonian coastal meadows with a synergistic use of drone, satellite imagery and digital elevation models. This approach highlights the significant contribution of digital elevation models to multispectral data, enabling the modelling of heterogeneous plant community distributions in such wetlands.
Despite hosting a wide range of ecosystem services, coastal wetlands face threats from global...
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