- Article
(4552 KB) - Metadata XML
- April 12, 2024
- |
- Home
- |
- Sitemap
- |
- The ISPRS Foundation
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Articles | Volume IV-2
https://doi.org/10.5194/isprs-annals-IV-2-193-2018
© 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-annals-IV-2-193-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
28 May 2018
| 28 May 2018
SUB-PIXEL ACCURACY CRACK WIDTH DETERMINATION ON CONCRETE BEAMS IN LOAD TESTS BY TRIANGLE MESH GEOMETRY ANALYSIS
F. Liebold
Institute of Photogrammetry and Remote Sensing, Technische Universit¨at Dresden, Germany
H.-G. Maas
Institute of Photogrammetry and Remote Sensing, Technische Universit¨at Dresden, Germany
Related authors
F. Liebold, R. Lorenzoni, I. Curosu, F. Léonard, V. Mechtcherine, S. Paciornik, and H.-G. Maas
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2021, 533–539, https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-533-2021, https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-533-2021, 2021
F. Liebold, H.-G. Maas, and A. A. Heravi
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W18, 107–113, https://doi.org/10.5194/isprs-archives-XLII-2-W18-107-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W18-107-2019, 2019
F. Wagner and H.-G. Maas
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-W2-2023, 1667–1676, https://doi.org/10.5194/isprs-archives-XLVIII-1-W2-2023-1667-2023, https://doi.org/10.5194/isprs-archives-XLVIII-1-W2-2023-1667-2023, 2023
F. Liebold and H.-G. Maas
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-2-W2-2022, 61–68, https://doi.org/10.5194/isprs-archives-XLVIII-2-W2-2022-61-2022, https://doi.org/10.5194/isprs-archives-XLVIII-2-W2-2022-61-2022, 2022
S. Isfort, F. Maiwald, C. Mulsow, and H.-G. Maas
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B1-2022, 113–119, https://doi.org/10.5194/isprs-archives-XLIII-B1-2022-113-2022, https://doi.org/10.5194/isprs-archives-XLIII-B1-2022-113-2022, 2022
M. Jarzabek-Rychard and H.-G. Maas
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2022, 395–400, https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-395-2022, https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-395-2022, 2022
K. Richter, D. Mader, P. Westfeld, and H.-G. Maas
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2022, 945–951, https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-945-2022, https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-945-2022, 2022
M. Jarząbek-Rychard and H-G. Maas
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., VIII-5-W1-2022, 1–7, https://doi.org/10.5194/isprs-annals-VIII-5-W1-2022-1-2022, https://doi.org/10.5194/isprs-annals-VIII-5-W1-2022-1-2022, 2022
F. Liebold, R. Lorenzoni, I. Curosu, F. Léonard, V. Mechtcherine, S. Paciornik, and H.-G. Maas
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2021, 533–539, https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-533-2021, https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-533-2021, 2021
K. Richter, D. Mader, P. Westfeld, and H.-G. Maas
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2021, 681–688, https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-681-2021, https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-681-2021, 2021
H. Sardemann, C. Mulsow, and H.-G. Maas
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2021, 689–692, https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-689-2021, https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-689-2021, 2021
E. Johnson, D. Floricioiu, E. Schwalbe, R. Koschitzki, H.-G. Maas, C. Cardenas, and G. Casassa
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-3-W2-2020, 125–127, https://doi.org/10.5194/isprs-annals-IV-3-W2-2020-125-2020, https://doi.org/10.5194/isprs-annals-IV-3-W2-2020-125-2020, 2020
E. Schwalbe, R. Koschitzki, E. Johnson, D. F. Mojica Moncada, B. Schröter, C. Cardenas, G. Casassa, and H.-G. Maas
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-3-W2-2020, 129–131, https://doi.org/10.5194/isprs-annals-IV-3-W2-2020-129-2020, https://doi.org/10.5194/isprs-annals-IV-3-W2-2020-129-2020, 2020
M. Elias and H.-G. Maas
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-1-2020, 181–187, https://doi.org/10.5194/isprs-annals-V-1-2020-181-2020, https://doi.org/10.5194/isprs-annals-V-1-2020-181-2020, 2020
C. Mulsow, G. Mandlburger, and H.-G. Maas
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2020, 671–677, https://doi.org/10.5194/isprs-annals-V-2-2020-671-2020, https://doi.org/10.5194/isprs-annals-V-2-2020-671-2020, 2020
F. Liebold, H.-G. Maas, and A. A. Heravi
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W18, 107–113, https://doi.org/10.5194/isprs-archives-XLII-2-W18-107-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W18-107-2019, 2019
T. Kaiser, C. Clemen, and H.-G. Maas
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-5-W2, 35–39, https://doi.org/10.5194/isprs-archives-XLII-5-W2-35-2019, https://doi.org/10.5194/isprs-archives-XLII-5-W2-35-2019, 2019
D. Mader, K. Richter, P. Westfeld, R. Weiß, and H.-G. Maas
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 1053–1059, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1053-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1053-2019, 2019
D. Lin, Z. Dong, X. Zhang, and H.-G. Maas
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2-W5, 45–51, https://doi.org/10.5194/isprs-annals-IV-2-W5-45-2019, https://doi.org/10.5194/isprs-annals-IV-2-W5-45-2019, 2019
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
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
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.
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.
Useful Links
Useful External Links
Our Contact
c/o
Leibniz University Hannover
Institute of Photogrammetry and GeoInformation
Nienburger Str. 1
D-30167 Hannover
GERMANY
Email: isprs-sg@isprs.org