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The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Articles | Volume XLVIII-2-2024
https://doi.org/10.5194/isprs-archives-XLVIII-2-2024-137-2024
© Author(s) 2024. 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-XLVIII-2-2024-137-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
11 Jun 2024
| 11 Jun 2024
Novel View Synthesis with Neural Radiance Fields for Industrial Robot Applications
Markus Hillemann
Institute of Photogrammetry and Remote Sensing, Karlsruhe Institute of Technology, Germany
Robert Langendörfer
Institute of Photogrammetry and Remote Sensing, Karlsruhe Institute of Technology, Germany
Max Heiken
Institute of Photogrammetry and GeoInformation, Leibniz Universität Hannover, Germany
Max Mehltretter
Institute of Photogrammetry and GeoInformation, Leibniz Universität Hannover, Germany
Andreas Schenk
Institute of Photogrammetry and Remote Sensing, Karlsruhe Institute of Technology, Germany
Martin Weinmann
Institute of Photogrammetry and Remote Sensing, Karlsruhe Institute of Technology, Germany
Stefan Hinz
Institute of Photogrammetry and Remote Sensing, Karlsruhe Institute of Technology, Germany
Christian Heipke
Institute of Photogrammetry and GeoInformation, Leibniz Universität Hannover, Germany
Markus Ulrich
Institute of Photogrammetry and Remote Sensing, Karlsruhe Institute of Technology, Germany
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Short summary
Short summary
In this study, a comprehensive multi-disciplinary dataset for tropospheric water vapor was developed. Geodetic, photogrammetric, and atmospheric modeling and data fusion techniques were used to obtain maps of water vapor in a high spatial and temporal resolution. It could be shown that regional weather simulations for different seasons benefit from assimilating these maps and that the combination of the different observation techniques led to positive synergies.
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M. Coenen, F. Rottensteiner, and C. Heipke
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2-W5, 21–28, https://doi.org/10.5194/isprs-annals-IV-2-W5-21-2019, https://doi.org/10.5194/isprs-annals-IV-2-W5-21-2019, 2019
U. Nguyen, F. Rottensteiner, and C. Heipke
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2-W5, 53–60, https://doi.org/10.5194/isprs-annals-IV-2-W5-53-2019, https://doi.org/10.5194/isprs-annals-IV-2-W5-53-2019, 2019
J. Boehm, M. Rutzinger, B. Yang, M. Weinmann, B. Riveiro, and W. Yao
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2-W5, 313–315, https://doi.org/10.5194/isprs-annals-IV-2-W5-313-2019, https://doi.org/10.5194/isprs-annals-IV-2-W5-313-2019, 2019
M. Weinmann, R. Müller, R. Reulke, E. Honkavaara, D. Tuia, and S. Keller
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2-W5, 607–608, https://doi.org/10.5194/isprs-annals-IV-2-W5-607-2019, https://doi.org/10.5194/isprs-annals-IV-2-W5-607-2019, 2019
L. Halounová, C. Heipke, and A. Radtke
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-A, 1–298, https://doi.org/10.5194/isprs-archives-XLI-A-1-2018, https://doi.org/10.5194/isprs-archives-XLI-A-1-2018, 2018
B. Jutzi, M. Weinmann, and S. Hinz
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-1, 1–3, https://doi.org/10.5194/isprs-annals-IV-1-1-2018, https://doi.org/10.5194/isprs-annals-IV-1-1-2018, 2018
K. Chen, M. Weinmann, X. Sun, M. Yan, S. Hinz, B. Jutzi, and M. Weinmann
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-1, 29–36, https://doi.org/10.5194/isprs-annals-IV-1-29-2018, https://doi.org/10.5194/isprs-annals-IV-1-29-2018, 2018
R. Gabriel, S. Keller, J. Matthes, P. Waibel, H. B. Keller, and S. Hinz
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-1, 53–60, https://doi.org/10.5194/isprs-annals-IV-1-53-2018, https://doi.org/10.5194/isprs-annals-IV-1-53-2018, 2018
S. Keller, F. M. Riese, J. Stötzer, P. M. Maier, and S. Hinz
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-1, 101–108, https://doi.org/10.5194/isprs-annals-IV-1-101-2018, https://doi.org/10.5194/isprs-annals-IV-1-101-2018, 2018
B. Ruf, L. Thiel, and M. Weinmann
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-1, 125–132, https://doi.org/10.5194/isprs-annals-IV-1-125-2018, https://doi.org/10.5194/isprs-annals-IV-1-125-2018, 2018
M. Weinmann, P. M. Maier, J. Florath, and U. Weidner
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-1, 155–162, https://doi.org/10.5194/isprs-annals-IV-1-155-2018, https://doi.org/10.5194/isprs-annals-IV-1-155-2018, 2018
B. Jutzi, M. Weinmann, and S. Hinz
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-1, 1–3, https://doi.org/10.5194/isprs-archives-XLII-1-1-2018, https://doi.org/10.5194/isprs-archives-XLII-1-1-2018, 2018
M. Boldt, A. Thiele, K. Schulz, and S. Hinz
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-1, 59–64, https://doi.org/10.5194/isprs-archives-XLII-1-59-2018, https://doi.org/10.5194/isprs-archives-XLII-1-59-2018, 2018
P. Hübner, M. Weinmann, and S. Wursthorn
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-1, 195–202, https://doi.org/10.5194/isprs-archives-XLII-1-195-2018, https://doi.org/10.5194/isprs-archives-XLII-1-195-2018, 2018
A. Sledz, J. Unger, and C. Heipke
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-1, 413–420, https://doi.org/10.5194/isprs-archives-XLII-1-413-2018, https://doi.org/10.5194/isprs-archives-XLII-1-413-2018, 2018
P. Hübner, M. Weinmann, M. Hillemann, B. Jutzi, and S. Wursthorn
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2, 455–462, https://doi.org/10.5194/isprs-archives-XLII-2-455-2018, https://doi.org/10.5194/isprs-archives-XLII-2-455-2018, 2018
A. Paul, K. Vogt, F. Rottensteiner, J. Ostermann, and C. Heipke
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2, 845–852, https://doi.org/10.5194/isprs-archives-XLII-2-845-2018, https://doi.org/10.5194/isprs-archives-XLII-2-845-2018, 2018
K. Chen, M. Weinmann, X. Gao, M. Yan, S. Hinz, B. Jutzi, and M. Weinmann
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2, 65–72, https://doi.org/10.5194/isprs-annals-IV-2-65-2018, https://doi.org/10.5194/isprs-annals-IV-2-65-2018, 2018
M. Coenen, F. Rottensteiner, and C. Heipke
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2, 73–80, https://doi.org/10.5194/isprs-annals-IV-2-73-2018, https://doi.org/10.5194/isprs-annals-IV-2-73-2018, 2018
X. Wang, F. Rottensteiner, and C. Heipke
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
A. Paul, C. Yang, U. Breitkopf, Y. Liu, Z. Wang, F. Rottensteiner, M. Wallner, A. Verworn, and C. Heipke
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 1355–1362, https://doi.org/10.5194/isprs-archives-XLII-3-1355-2018, https://doi.org/10.5194/isprs-archives-XLII-3-1355-2018, 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
R. Ilehag, M. Weinmann, A. Schenk, S. Keller, B. Jutzi, and S. Hinz
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W3, 65–71, https://doi.org/10.5194/isprs-archives-XLII-3-W3-65-2017, https://doi.org/10.5194/isprs-archives-XLII-3-W3-65-2017, 2017
M. Breunig, A. Borrmann, E. Rank, S. Hinz, T. Kolbe, M. Schilcher, R.-P. Mundani, J. R. Jubierre, M. Flurl, A. Thomsen, A. Donaubauer, Y. Ji, S. Urban, S. Laun, S. Vilgertshofer, B. Willenborg, M. Menninghaus, H. Steuer, S. Wursthorn, J. Leitloff, M. Al-Doori, and N Mazroobsemnani
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4-W4, 341–352, https://doi.org/10.5194/isprs-archives-XLII-4-W4-341-2017, https://doi.org/10.5194/isprs-archives-XLII-4-W4-341-2017, 2017
R. Blomley and M. Weinmann
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2-W4, 43–50, https://doi.org/10.5194/isprs-annals-IV-2-W4-43-2017, https://doi.org/10.5194/isprs-annals-IV-2-W4-43-2017, 2017
J. Kern, M. Weinmann, and S. Wursthorn
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2-W4, 83–90, https://doi.org/10.5194/isprs-annals-IV-2-W4-83-2017, https://doi.org/10.5194/isprs-annals-IV-2-W4-83-2017, 2017
B. Ruf, B. Erdnuess, and M. Weinmann
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W6, 325–332, https://doi.org/10.5194/isprs-archives-XLII-2-W6-325-2017, https://doi.org/10.5194/isprs-archives-XLII-2-W6-325-2017, 2017
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. Weinmann, M. S. Müller, M. Hillemann, N. Reydel, S. Hinz, and B. Jutzi
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W6, 399–406, https://doi.org/10.5194/isprs-archives-XLII-2-W6-399-2017, https://doi.org/10.5194/isprs-archives-XLII-2-W6-399-2017, 2017
R. Ilehag, A. Schenk, and S. Hinz
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W6, 145–151, https://doi.org/10.5194/isprs-archives-XLII-2-W6-145-2017, https://doi.org/10.5194/isprs-archives-XLII-2-W6-145-2017, 2017
M. Hillemann and B. Jutzi
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2-W3, 17–24, https://doi.org/10.5194/isprs-annals-IV-2-W3-17-2017, https://doi.org/10.5194/isprs-annals-IV-2-W3-17-2017, 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
F. Alshawaf, B. Fersch, S. Hinz, H. Kunstmann, M. Mayer, and F. J. Meyer
Hydrol. Earth Syst. Sci., 19, 4747–4764, https://doi.org/10.5194/hess-19-4747-2015, https://doi.org/10.5194/hess-19-4747-2015, 2015
Short summary
Short summary
This work aims at deriving high spatially resolved maps of atmospheric water vapor by the fusion data from Interferometric Synthetic Aperture Radar (InSAR), Global Navigation Satellite Systems (GNSS), and the Weather Research and Forecasting (WRF) model. The data fusion approach exploits the redundant and complementary spatial properties of all data sets to provide more accurate and high-resolution maps of water vapor. The comparison with maps from MERIS shows rms values of less than 1 mm.
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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