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Title (eng)
Land cover classification 2021-09-10
Analyst
Claudia Buchsteiner
Researcher
Pamela Alessandra Baur
Description (eng)
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. doi.org/10.3390/rs15163961 Flight 2021-09-10 over the reed belt of Lake Neusiedl near Illmitz in the nature zone of the National Park Neusiedler See - Seewinkel. - Land cover classification of the study site with three classes vegetation (reed), water and sediment and their temporal changes over the study period performed with deep learning (CNN) Land cover classes: - 1: vegetation (reed) - 2: water - 3: sediment (open soil) Format: Shapefile (polygon) 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)
Keywords (eng)
ReedPhragmites australisLake NeusiedlIllmitzdeep learningUAVLand cover classification
Subject (eng)
ÖFOS 2012 -- 105906 -- Environmental geosciences
Subject (eng)
ÖFOS 2012 -- 105405 -- Geoecology
Subject (eng)
ÖFOS 2012 -- 207402 -- Remote sensing
Subject (eng)
ÖFOS 2012 -- 106026 -- Ecosystem research
Type (eng)
dataset
Type (eng)
map
Type (eng)
cartographic material
Language
English [eng]
Persistent identifier
https://phaidra.univie.ac.at/o:1649400
DOI
10.25365/phaidra.397
Version type (eng)
author's original
Date created
2023
Temporal coverage
2021-09-10
Depicted / Represented place
Reed Belt of Lake Neusiedl Research Site
[Reed Belt of Lake Neusiedl Research Site--Illmitz--Neusiedl am See--Burgenland--Austria]
Association (eng)
Department of Geography and Regional Research
Access rights (eng)
open access
License
CC BY-SA 4.0 International
Bibliography
Cites (eng)
Buchsteiner, C.; Baur, P.A. (2023): Spatial and intra-annual datasets on reed ecosystem dynamics at Lake Neusiedl of 2021 using RGB drone imagery, Phenocam and Deep Learning. V1. PHAIDRA Repositorium (University of Vienna).https://doi.org/10.25365/phaidra.397