How green is Austria? An Austrian-wide information layer based on semantic querying of EO data

Martin Sudmanns; Hannah Augustin; Andrea Baraldi; Thomas Strasser; Dirk Tiede

doi:10.2760/46796

How green is Austria? An Austrian-wide information layer based on semantic querying of EO data

Martin Sudmanns^*
, Hannah Augustin
, Andrea Baraldi
, Thomas Strasser
, Dirk Tiede

^*Corresponding author for this work

Geoinformatics

Research output: Chapter in Book/Report/Conference proceeding/Legal commentary › Conference contribution › peer-review

Original language	English
Title of host publication	Proceedings of the 2023 conference on Big Data from Space
Editors	Pierre Soille, Stefanie Lumnitz, Sergio Albani
Publisher	European Commission, Luxembourg: Publications Office of the European Union
ISBN (Electronic)	978-92-68-08696-4
DOIs	https://doi.org/10.2760/46796
Publication status	Published - 2 Nov 2023

Publication series

Name	Proceedings of the 2023 conference on Big Data from Space

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 15 Life on Land

Fields of Science and Technology Classification 2012

107 Other Natural Sciences

Access to Document

10.2760/46796

INTERFACE: INformaTion accEss seRvice For Austrian CopErnicus and contributing missions data
Tiede, D. (Principal Investigator), Augustin, H. L. (Co-Investigator), Sudmanns, M. (Co-Investigator) & Strasser, T. (Co-Investigator)
1/09/22 → 28/02/25
Project: Research
Sen2Cube.at: Sentinel-2 Semantic Data Cube Austria
Tiede, D. (Principal Investigator) & Sudmanns, M. (Co-Investigator)
2/07/18 → 31/07/20
Project: Research

How green is Austria? An Austrian-wide information layer based on semantic querying of EO data
Sudmanns, M. (Speaker), Augustin, H. L. (Speaker), Baraldi, A. (Speaker), Strasser, T. (Speaker) & Tiede, D. (Speaker)
7 Nov 2023
Activity: Talk or presentation › Oral presentation › science to science / art to art

Cite this

Sudmanns, M., Augustin, H., Baraldi, A., Strasser, T., & Tiede, D. (2023). How green is Austria? An Austrian-wide information layer based on semantic querying of EO data. In P. Soille, S. Lumnitz, & S. Albani (Eds.), Proceedings of the 2023 conference on Big Data from Space (Proceedings of the 2023 conference on Big Data from Space). European Commission, Luxembourg: Publications Office of the European Union. https://doi.org/10.2760/46796

Sudmanns, Martin ; Augustin, Hannah ; Baraldi, Andrea et al. / How green is Austria? An Austrian-wide information layer based on semantic querying of EO data. Proceedings of the 2023 conference on Big Data from Space. editor / Pierre Soille ; Stefanie Lumnitz ; Sergio Albani. European Commission, Luxembourg: Publications Office of the European Union, 2023. (Proceedings of the 2023 conference on Big Data from Space).

@inproceedings{d5f4d4c75a6a4d548b2e695546a0cd70,

title = "How green is Austria? An Austrian-wide information layer based on semantic querying of EO data",

author = "Martin Sudmanns and Hannah Augustin and Andrea Baraldi and Thomas Strasser and Dirk Tiede",

year = "2023",

month = nov,

day = "2",

doi = "10.2760/46796",

language = "English",

series = "Proceedings of the 2023 conference on Big Data from Space",

publisher = "European Commission, Luxembourg: Publications Office of the European Union",

editor = "Pierre Soille and Stefanie Lumnitz and Sergio Albani",

booktitle = "Proceedings of the 2023 conference on Big Data from Space",

}

Sudmanns, M, Augustin, H, Baraldi, A, Strasser, T & Tiede, D 2023, How green is Austria? An Austrian-wide information layer based on semantic querying of EO data. in P Soille, S Lumnitz & S Albani (eds), Proceedings of the 2023 conference on Big Data from Space. Proceedings of the 2023 conference on Big Data from Space, European Commission, Luxembourg: Publications Office of the European Union. https://doi.org/10.2760/46796

How green is Austria? An Austrian-wide information layer based on semantic querying of EO data. / Sudmanns, Martin; Augustin, Hannah; Baraldi, Andrea et al.
Proceedings of the 2023 conference on Big Data from Space. ed. / Pierre Soille; Stefanie Lumnitz; Sergio Albani. European Commission, Luxembourg: Publications Office of the European Union, 2023. (Proceedings of the 2023 conference on Big Data from Space).

Research output: Chapter in Book/Report/Conference proceeding/Legal commentary › Conference contribution › peer-review

TY - GEN

T1 - How green is Austria? An Austrian-wide information layer based on semantic querying of EO data

AU - Sudmanns, Martin

AU - Augustin, Hannah

AU - Baraldi, Andrea

AU - Strasser, Thomas

AU - Tiede, Dirk

PY - 2023/11/2

Y1 - 2023/11/2

U2 - 10.2760/46796

DO - 10.2760/46796

M3 - Conference contribution

T3 - Proceedings of the 2023 conference on Big Data from Space

BT - Proceedings of the 2023 conference on Big Data from Space

A2 - Soille, Pierre

A2 - Lumnitz, Stefanie

A2 - Albani, Sergio

PB - European Commission, Luxembourg: Publications Office of the European Union

ER -

Sudmanns M, Augustin H, Baraldi A, Strasser T , Tiede D. How green is Austria? An Austrian-wide information layer based on semantic querying of EO data. In Soille P, Lumnitz S, Albani S, editors, Proceedings of the 2023 conference on Big Data from Space. European Commission, Luxembourg: Publications Office of the European Union. 2023. (Proceedings of the 2023 conference on Big Data from Space). doi: 10.2760/46796

How green is Austria? An Austrian-wide information layer based on semantic querying of EO data

Publication series

UN SDGs

Fields of Science and Technology Classification 2012

Access to Document

Projects

INTERFACE: INformaTion accEss seRvice For Austrian CopErnicus and contributing missions data

Sen2Cube.at: Sentinel-2 Semantic Data Cube Austria

Activities

How green is Austria? An Austrian-wide information layer based on semantic querying of EO data

Cite this