Volunteered Geographic Information: Interpretation, Visualisation and Social Computing (VGIscience)
Dirk Burghardt
Technical University Dresden, IfK, Dresden, Germany
Wolfgang Nejdl
Leibniz-University Hannover, L3S, Hannover, Germany
Jochen Schiewe
HafenCity University Hamburg, g2lab, Hamburg, Germany
Monika Sester
Leibniz-University Hannover, IKG, Hannover, Germany
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J. Golze, U. Feuerhake, C. Koetsier, and M. Sester
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O. Wage and M. Sester
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Florian Politz, Monika Sester, and Claus Brenner
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Ramish Satari, Bashir Kazimi, and Monika Sester
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Yao Li and Monika Sester
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Mathias Gröbe, Alexander Dunkel, and Dirk Burghardt
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Christopher W. Frank, Frank Kaspar, Jan D. Keller, Till Adams, Miriam Felkers, Bernd Fischer, Marcus Handte, Pedro José Marrón, Hinrich Paulsen, Markus Neteler, Jochen Schiewe, Marvin Schuchert, Christian Nickel, Richard Wacker, and Richard Figura
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Short summary
Short summary
Access to high quality weather and climate data is crucial for a wide range of societal and economic issues. It allows optimising industrial processes with respect to efficiency. The goal of the research project FAIR is to simplify the information exchange between the DWD and economical players. This paper summarizes the results of the requirement analysis of three use cases and presents the deduced technical architecture and FAIR services aiming at a user-friendly exchange of weather data.
V. Kamalasanan and M. Sester
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Y. Feng, C. Yang, and M. Sester
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A. Leichter, M. Werner, and M. Sester
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C. Koetsier, T. Peters, and M. Sester
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F. Politz, M. Sester, and C. Brenner
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B. Kazimi, F. Thiemann, and M. Sester
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Thomas Gründemann and Dirk Burghardt
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B. Kazimi, F. Thiemann, and M. Sester
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Natalia Andrienko, Gennady Andrienko, Siming Chen, Dirk Burghardt, Alexander Dunkel, and Ross Purves
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Georg Gartner, Menno-Jan Kraak, Dirk Burghardt, Liqiu Meng, Juliane Cron, Corné van Elzakker, and Britta Ricker
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F. Politz and M. Sester
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C. Koetsier, S. Busch, and M. Sester
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F. Politz and M. Sester
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-1, 347–354, https://doi.org/10.5194/isprs-archives-XLII-1-347-2018, https://doi.org/10.5194/isprs-archives-XLII-1-347-2018, 2018
U. Feuerhake, O. Wage, M. Sester, N. Tempelmeier, W. Nejdl, and E. Demidova
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4, 185–192, https://doi.org/10.5194/isprs-archives-XLII-4-185-2018, https://doi.org/10.5194/isprs-archives-XLII-4-185-2018, 2018
A. Leichter, D. Wittich, F. Rottensteiner, M. Werner, and M. Sester
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4, 335–342, https://doi.org/10.5194/isprs-archives-XLII-4-335-2018, https://doi.org/10.5194/isprs-archives-XLII-4-335-2018, 2018
J. Schiewe
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4, 551–558, https://doi.org/10.5194/isprs-archives-XLII-4-551-2018, https://doi.org/10.5194/isprs-archives-XLII-4-551-2018, 2018
M. Sester, Y. Feng, and F. Thiemann
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4, 565–572, https://doi.org/10.5194/isprs-archives-XLII-4-565-2018, https://doi.org/10.5194/isprs-archives-XLII-4-565-2018, 2018
Y. Feng, C. Brenner, and M. Sester
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-4-W6, 11–18, https://doi.org/10.5194/isprs-annals-IV-4-W6-11-2018, https://doi.org/10.5194/isprs-annals-IV-4-W6-11-2018, 2018
Fabian Bock, Karen Xia, and Monika Sester
Proc. Int. Cartogr. Assoc., 1, 12, https://doi.org/10.5194/ica-proc-1-12-2018, https://doi.org/10.5194/ica-proc-1-12-2018, 2018
Xiao Wang and Dirk Burghardt
Proc. Int. Cartogr. Assoc., 1, 122, https://doi.org/10.5194/ica-proc-1-122-2018, https://doi.org/10.5194/ica-proc-1-122-2018, 2018
Ehsan Rabiei, Uwe Haberlandt, Monika Sester, Daniel Fitzner, and Markus Wallner
Hydrol. Earth Syst. Sci., 20, 3907–3922, https://doi.org/10.5194/hess-20-3907-2016, https://doi.org/10.5194/hess-20-3907-2016, 2016
Short summary
Short summary
The value of using moving cars for rainfall measurement purposes (RCs) was investigated with laboratory experiments by Rabiei et al. (2013). They analyzed the Hydreon and Xanonex optical sensors against different rainfall intensities. A continuous investigation of using RCs with the derived uncertainties from laboratory experiments for areal rainfall estimation as well as implementing the data in a hydrological model are addressed in this study.
S. Zourlidou and M. Sester
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B2, 269–276, https://doi.org/10.5194/isprs-archives-XLI-B2-269-2016, https://doi.org/10.5194/isprs-archives-XLI-B2-269-2016, 2016
E. Rabiei, U. Haberlandt, M. Sester, and D. Fitzner
Hydrol. Earth Syst. Sci., 17, 4701–4712, https://doi.org/10.5194/hess-17-4701-2013, https://doi.org/10.5194/hess-17-4701-2013, 2013