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ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Articles | Volume X-2-2024
https://doi.org/10.5194/isprs-annals-X-2-2024-57-2024
© 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-annals-X-2-2024-57-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
10 Jun 2024
| 10 Jun 2024
UAS Photogrammetry for Precise Digital Elevation Models of Complex Topography: A Strategy Guide
Melanie Elias
Institute of Photogrammetry and Remote Sensing, TUD Dresden University of Technology, Germany
Steffen Isfort
Institute of Photogrammetry and Remote Sensing, TUD Dresden University of Technology, Germany
Anette Eltner
Institute of Photogrammetry and Remote Sensing, TUD Dresden University of Technology, Germany
Hans-Gerd Maas
Institute of Photogrammetry and Remote Sensing, TUD Dresden University of Technology, Germany
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S. C. L. Ribeiro, M. Jarzabek-Rychard, J. P. Cintra, and H.-G. Maas
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2-W5, 437–444, https://doi.org/10.5194/isprs-annals-IV-2-W5-437-2019, https://doi.org/10.5194/isprs-annals-IV-2-W5-437-2019, 2019
H.-G. Maas, D. Mader, K. Richter, and P. Westfeld
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W10, 113–117, https://doi.org/10.5194/isprs-archives-XLII-2-W10-113-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W10-113-2019, 2019
M. Kröhnert, R. Anderson, J. Bumberger, P. Dietrich, W. S. Harpole, and H.-G. Maas
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2, 539–542, https://doi.org/10.5194/isprs-archives-XLII-2-539-2018, https://doi.org/10.5194/isprs-archives-XLII-2-539-2018, 2018
M. Kröhnert and A. Eltner
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2, 543–550, https://doi.org/10.5194/isprs-archives-XLII-2-543-2018, https://doi.org/10.5194/isprs-archives-XLII-2-543-2018, 2018
D. Lin, M. Jarzabek-Rychard, D. Schneider, and H.-G. Maas
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2, 585–591, https://doi.org/10.5194/isprs-archives-XLII-2-585-2018, https://doi.org/10.5194/isprs-archives-XLII-2-585-2018, 2018
C. Mulsow, R. Kenner, Y. Bühler, A. Stoffel, and H.-G. Maas
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2, 739–744, https://doi.org/10.5194/isprs-archives-XLII-2-739-2018, https://doi.org/10.5194/isprs-archives-XLII-2-739-2018, 2018
K. Richter, D. Mader, P. Westfeld, and H.-G. Maas
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2, 961–967, https://doi.org/10.5194/isprs-archives-XLII-2-961-2018, https://doi.org/10.5194/isprs-archives-XLII-2-961-2018, 2018
H. Sardemann, A. Eltner, and H.-G. Maas
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2, 1023–1027, https://doi.org/10.5194/isprs-archives-XLII-2-1023-2018, https://doi.org/10.5194/isprs-archives-XLII-2-1023-2018, 2018
E. Watson, H.-G. Maas, F. Schäfer, and S. Hiermaier
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2, 1175–1181, https://doi.org/10.5194/isprs-archives-XLII-2-1175-2018, https://doi.org/10.5194/isprs-archives-XLII-2-1175-2018, 2018
F. Liebold and H.-G. Maas
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2, 193–200, https://doi.org/10.5194/isprs-annals-IV-2-193-2018, https://doi.org/10.5194/isprs-annals-IV-2-193-2018, 2018
D. Lin, A. Eltner, H. Sardemann, and H.-G. Maas
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2, 201–208, https://doi.org/10.5194/isprs-annals-IV-2-201-2018, https://doi.org/10.5194/isprs-annals-IV-2-201-2018, 2018
Ellen Schwalbe and Hans-Gerd Maas
Earth Surf. Dynam., 5, 861–879, https://doi.org/10.5194/esurf-5-861-2017, https://doi.org/10.5194/esurf-5-861-2017, 2017
Short summary
Short summary
The simple use of time-lapse cameras as a visual observation tool may already be a great help for environmental investigations. However, beyond that, they have the potential to also deliver precise measurements with high temporal and spatial resolution when applying appropriate processing techniques. In this paper we introduce a method for the determination of glacier motion fields from time-lapse images, but it might also be adapted for other environmental motion analysis tasks.
A. Eltner, D. Schneider, and H.-G. Maas
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B5, 813–819, https://doi.org/10.5194/isprs-archives-XLI-B5-813-2016, https://doi.org/10.5194/isprs-archives-XLI-B5-813-2016, 2016
Anette Eltner, Andreas Kaiser, Carlos Castillo, Gilles Rock, Fabian Neugirg, and Antonio Abellán
Earth Surf. Dynam., 4, 359–389, https://doi.org/10.5194/esurf-4-359-2016, https://doi.org/10.5194/esurf-4-359-2016, 2016
Short summary
Short summary
Three-dimensional reconstruction of earth surfaces from overlapping images is a promising tool for geoscientists. The method is very flexible, cost-efficient and easy to use, leading to a high variability in applications at different scales. Performance evaluation reveals that good accuracies are achievable but depend on the requirements of the individual case study. Future applications and developments (i.e. big data) will consolidate this essential tool for digital surface mapping.
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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