Abstract
Datasets corresponding to the publication:
Buchsteiner, C.; Baur, P.A.; Glatzel, S. (2023): Spatial Analysis of Intra-Annual Reed Ecosystem Dynamics at Lake Neusiedl Using RGB Drone Imagery and Deep Learning. Remote Sensing, 15, 3961. https://doi.org/10.3390/rs15163961
Spatio-temporal data sets of 10 UAV flights from May to November 2021 over the reed belt of Lake Neusiedl near Illmitz in the nature zone of the National Park Neusiedler See - Seewinkel.
- Georeferenced orthomosaics in RGB and with a spatial resolution of at least 2.5 cm/pixel
- Land cover classification of the study site with 3 classes vegetation (reed), water and sediment and their temporal changes over the study period performed with deep learning (CNN)
- Vegetation index maps showing green chromatic coordinates (GCC) of the entire study site for every flight to examine the phenological changes of the vegetation over the study period
Geographical informations:
- extent: 53 ha (study area)
- coordinates of center: 47°46’09"N, 16°45’30"E
- coordinate system: WGS 1984 UTM Zone 33N (EPSG: 32633)
Temporal dataset of the Phenocam attached to the Eddy Covariance Tower, facing northwest and located in the eastern reed belt of Lake Neusiedl (near Ilmitz).
The Phenocam has been studying the phenological changes of the reed plant (Phragmites australis) since September 2020 and is equipped with a normal digital camera that captures RGB images every hour during the day.
The Phenocam dataset has a daily time stamp and contains processed and filtered Green Chromatic Coordinates (GCC) values of 2021.
Format of Phenocam datset: CSV
Coordinates of Phenocam (Eddy Covariance Tower): 47.769150°N, 16.758482°E
Buchsteiner, C.; Baur, P.A.; Glatzel, S. (2023): Spatial Analysis of Intra-Annual Reed Ecosystem Dynamics at Lake Neusiedl Using RGB Drone Imagery and Deep Learning. Remote Sensing, 15, 3961. https://doi.org/10.3390/rs15163961
Spatio-temporal data sets of 10 UAV flights from May to November 2021 over the reed belt of Lake Neusiedl near Illmitz in the nature zone of the National Park Neusiedler See - Seewinkel.
- Georeferenced orthomosaics in RGB and with a spatial resolution of at least 2.5 cm/pixel
- Land cover classification of the study site with 3 classes vegetation (reed), water and sediment and their temporal changes over the study period performed with deep learning (CNN)
- Vegetation index maps showing green chromatic coordinates (GCC) of the entire study site for every flight to examine the phenological changes of the vegetation over the study period
Geographical informations:
- extent: 53 ha (study area)
- coordinates of center: 47°46’09"N, 16°45’30"E
- coordinate system: WGS 1984 UTM Zone 33N (EPSG: 32633)
Temporal dataset of the Phenocam attached to the Eddy Covariance Tower, facing northwest and located in the eastern reed belt of Lake Neusiedl (near Ilmitz).
The Phenocam has been studying the phenological changes of the reed plant (Phragmites australis) since September 2020 and is equipped with a normal digital camera that captures RGB images every hour during the day.
The Phenocam dataset has a daily time stamp and contains processed and filtered Green Chromatic Coordinates (GCC) values of 2021.
Format of Phenocam datset: CSV
Coordinates of Phenocam (Eddy Covariance Tower): 47.769150°N, 16.758482°E
| Originalsprache | Englisch |
|---|---|
| Typ | Data sets |
| Medium | PHAIDRA Repositorium (University of Vienna) |
| Verlag | Open Access-Publikation im Repositorium Phaidra |
| DOIs | |
| Publikationsstatus | Veröffentlicht - 2023 |
UN SDGs
Dieser Output leistet einen Beitrag zu folgendem(n) Ziel(en) für nachhaltige Entwicklung
-
SDG 15 – Leben an Land
ÖFOS 2012
- 207402 Fernerkundung
- 105906 Umweltgeowissenschaften
- 105405 Geoökologie
- 106026 Ökosystemforschung
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Doctoral thesis: Drought-influenced greenhouse gas fluxes and their emission pathways of the subsaline reed ecosystem of Lake Neusiedl
Baur, P. A., 2025, Wien: Universität Wien. 238 S.Veröffentlichungen: Buch › Peer Reviewed
Open Access -
Spatial Analysis of Intra-Annual Reed Ecosystem Dynamics at Lake Neusiedl Using RGB Drone Imagery and Deep Learning
Buchsteiner, C. (Korresp. Autor*in), Baur, P. A. & Glatzel, S., Aug. 2023, in: Remote Sensing. 15, 16, 3961.Veröffentlichungen: Beitrag in Fachzeitschrift › Artikel › Peer Reviewed
Open Access
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