Activities per year
Abstract
The reed belt of Lake Neusiedl, covering half the size of the lake, is subject to massive changes due to the strong decline of the water level over the last several years, especially in 2021. In this study, we investigated the spatial and temporal variations within a long-term ecosystem research (LTER) site in a reed ecosystem at Lake Neusiedl in Austria under intense drought conditions. Spatio-temporal data sets from May to November 2021 were produced to analyze and detect changes in the wetland ecosystem over a single vegetation period. High-resolution orthomosaics processed from RGB imagery taken with an unmanned aerial vehicle (UAV) served as the basis for land cover classification and phenological analysis. An image annotation workflow was developed, and deep learning techniques using semantic image segmentation were applied to map land cover changes. The trained models delivered highly favorable results in terms of the assessed performance metrics. When considering the region between their minima and maxima, the water surface area decreased by 26.9%, the sediment area increased by 23.1%, and the vegetation area increased successively by 10.1% over the investigation period. Phenocam data for lateral phenological monitoring of the vegetation development of Phragmites australis was directly compared with phenological analysis from aerial imagery. This study reveals the enormous dynamics of the reed ecosystem of Lake Neusiedl, and additionally confirms the importance of remote sensing via drone and the strengths of deep learning for wetland classification.
Original language | English |
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Article number | 3961 |
Journal | Remote Sensing |
Volume | 15 |
Issue number | 16 |
DOIs | |
Publication status | Published - Aug 2023 |
Austrian Fields of Science 2012
- 106026 Ecosystem research
- 105906 Environmental geosciences
- 105405 Geoecology
- 207402 Remote sensing
Keywords
- Lake Neusiedl
- reed
- LTER
- land cover classification
- deep learning
- DeepLabv3+
- structure from motion
- RGB
- UAV
- Green chromatic coordinates
- Phenocam
- green chromatic coordinates
Fingerprint
Dive into the research topics of 'Spatial Analysis of Intra-Annual Reed Ecosystem Dynamics at Lake Neusiedl Using RGB Drone Imagery and Deep Learning'. Together they form a unique fingerprint.Activities
- 1 Talk or oral contribution
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Auswirkungen der Trockenheit auf das Schilfökosystem des Neusiedlersees
Pamela Alessandra Baur (Speaker), Daniela Henry Pinilla (Contributor), Claudia Buchsteiner (Contributor), Andreas Maier (Contributor), Thomas Zechmeister (Contributor) & Stephan Glatzel (Contributor)
12 Nov 2024Activity: Talks and presentations › Talk or oral contribution › Science to Science
Press/Media
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Wenn der Pegel sinkt: Ökosystemforschung am Neusiedler See
13/09/23
1 item of Media coverage
Press/Media: Research
Research output
- 1 Other
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Spatial and intra-annual datasets on reed ecosystem dynamics at Lake Neusiedl of 2021 using RGB drone imagery, Phenocam and Deep Learning
Buchsteiner, C. & Baur, P. A., 2023, Open Access-Publikation im Repositorium Phaidra.Publications: Other publication › Other
Open Access