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The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Articles | Volume XLII-3
https://doi.org/10.5194/isprs-archives-XLII-3-1355-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/isprs-archives-XLII-3-1355-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
30 Apr 2018
| 30 Apr 2018
AUTOMATIC CLASSIFICATION OF AERIAL IMAGERY FOR URBAN HYDROLOGICAL APPLICATIONS
A. Paul
Institute of Photogrammetry and GeoInformation, Leibniz Universität Hannover, Germany
C. Yang
Institute of Photogrammetry and GeoInformation, Leibniz Universität Hannover, Germany
U. Breitkopf
Institute of Photogrammetry and GeoInformation, Leibniz Universität Hannover, Germany
Y. Liu
Institute of Photogrammetry and GeoInformation, Leibniz Universität Hannover, Germany
Z. Wang
Institute of Photogrammetry and GeoInformation, Leibniz Universität Hannover, Germany
F. Rottensteiner
Institute of Photogrammetry and GeoInformation, Leibniz Universität Hannover, Germany
M. Wallner
BPI Consulting Engineers, Hannover, Germany
A. Verworn
BPI Consulting Engineers, Hannover, Germany
C. Heipke
Institute of Photogrammetry and GeoInformation, Leibniz Universität Hannover, Germany
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Short summary
Short summary
Rainfall time series are disaggregated from daily to hourly values to be used for rainfall–runoff modeling of mesoscale catchments. Spatial rainfall consistency is implemented afterwards using simulated annealing. With the calibration process applied, observed runoff statistics (e.g., summer and winter peak flows) are represented well. However, rainfall datasets with under- or over-estimation of spatial consistency lead to similar results, so the need for a good representation can be questioned.
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ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2, 295–302, https://doi.org/10.5194/isprs-annals-IV-2-295-2018, https://doi.org/10.5194/isprs-annals-IV-2-295-2018, 2018
Christian Kruse, Franz Rottensteiner, Thorsten Hoberg, Marcel Ziems, Julia Rebke, and Christian Heipke
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-3, 127–134, https://doi.org/10.5194/isprs-annals-IV-3-127-2018, https://doi.org/10.5194/isprs-annals-IV-3-127-2018, 2018
Chun Yang, Franz Rottensteiner, and Christian Heipke
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-3, 251–258, https://doi.org/10.5194/isprs-annals-IV-3-251-2018, https://doi.org/10.5194/isprs-annals-IV-3-251-2018, 2018
J. Unger, F. Rottensteiner, and C. Heipke
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W6, 385–392, https://doi.org/10.5194/isprs-archives-XLII-2-W6-385-2017, https://doi.org/10.5194/isprs-archives-XLII-2-W6-385-2017, 2017
M. Coenen, F. Rottensteiner, and C. Heipke
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-1-W1, 505–512, https://doi.org/10.5194/isprs-archives-XLII-1-W1-505-2017, https://doi.org/10.5194/isprs-archives-XLII-1-W1-505-2017, 2017
Christian Heipke, Karsten Jacobsen, Uwe Stilla, Franz Rottensteiner, Alper Yilmaz, Michael Ying Yang, Jan Skaloud, and Ismael Colomina
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-1-W1, 1–2, https://doi.org/10.5194/isprs-annals-IV-1-W1-1-2017, https://doi.org/10.5194/isprs-annals-IV-1-W1-1-2017, 2017
C. Heipke, K. Jacobsen, U. Stilla, F. Rottensteiner, A. Yilmaz, M. Ying Yang, J. Skaloud, and I. Colomina
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-1-W1, 1–2, https://doi.org/10.5194/isprs-archives-XLII-1-W1-1-2017, https://doi.org/10.5194/isprs-archives-XLII-1-W1-1-2017, 2017
A. Maas, M. Alrajhi, A. Alobeid, and C. Heipke
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-1-W1, 11–16, https://doi.org/10.5194/isprs-archives-XLII-1-W1-11-2017, https://doi.org/10.5194/isprs-archives-XLII-1-W1-11-2017, 2017
A. Maas, F. Rottensteiner, and C. Heipke
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-1-W1, 215–222, https://doi.org/10.5194/isprs-annals-IV-1-W1-215-2017, https://doi.org/10.5194/isprs-annals-IV-1-W1-215-2017, 2017
K. Vogt, A. Paul, J. Ostermann, F. Rottensteiner, and C. Heipke
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-1-W1, 229–236, https://doi.org/10.5194/isprs-annals-IV-1-W1-229-2017, https://doi.org/10.5194/isprs-annals-IV-1-W1-229-2017, 2017
A. Paul, F. Rottensteiner, and C. Heipke
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., III-3, 339–346, https://doi.org/10.5194/isprs-annals-III-3-339-2016, https://doi.org/10.5194/isprs-annals-III-3-339-2016, 2016
C. Heipke
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-5-W7, 543–543, https://doi.org/10.5194/isprs-archives-XL-5-W7-543-2016, https://doi.org/10.5194/isprs-archives-XL-5-W7-543-2016, 2016
The International Society for Photogrammetry and Remote Sensing is a non-governmental organization devoted to the development of international cooperation for the advancement of photogrammetry and remote sensing and their applications. The Society operates without any discrimination on grounds of race, religion, nationality, or political philosophy.
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