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ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Articles | Volume IV-2/W4
https://doi.org/10.5194/isprs-annals-IV-2-W4-107-2017
© Author(s) 2017. 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-W4-107-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
13 Sep 2017
| 13 Sep 2017
AIRBORNE LIDAR POINTS CLASSIFICATION BASED ON TENSOR SPARSE REPRESENTATION
N. Li
College of Survey and Geoinformation, Tongji University, 200092, Shanghai, China
Deptartment of Geodesy and Geoinformation, Technische Universität Wien, 1040 Vienna, Austria
N. Pfeifer
Deptartment of Geodesy and Geoinformation, Technische Universität Wien, 1040 Vienna, Austria
C. Liu
College of Survey and Geoinformation, Tongji University, 200092, Shanghai, China
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Alpine rivers have experienced strong changes over the last century. In the present study, we explore the potential of historical multi-temporal elevation models, combined with recent topographic data, to quantify 66 years (from 1953 to 2019) of river changes in the glacier forefield of an Alpine catchment. Thereby, we quantify the changes in the river form as well as the related sediment erosion and deposition.
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A. Walicka, N. Pfeifer, G. Jóźków, and A. Borkowski
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 1149–1154, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1149-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1149-2019, 2019
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Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 469–473, https://doi.org/10.5194/isprs-archives-XLII-2-W13-469-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W13-469-2019, 2019
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P. Glira, N. Pfeifer, and G. Mandlburger
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2-W5, 567–574, https://doi.org/10.5194/isprs-annals-IV-2-W5-567-2019, https://doi.org/10.5194/isprs-annals-IV-2-W5-567-2019, 2019
P. Yu, H. Wu, C. Liu, and Z. Xu
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 2167–2171, https://doi.org/10.5194/isprs-archives-XLII-3-2167-2018, https://doi.org/10.5194/isprs-archives-XLII-3-2167-2018, 2018
G. Mandlburger, N. Pfeifer, and U. Soergel
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A. Roncat, N. Pfeifer, and C. Briese
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2-W4, 131–137, https://doi.org/10.5194/isprs-annals-IV-2-W4-131-2017, https://doi.org/10.5194/isprs-annals-IV-2-W4-131-2017, 2017
D. Wang, M. Hollaus, and N. Pfeifer
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2-W4, 157–164, https://doi.org/10.5194/isprs-annals-IV-2-W4-157-2017, https://doi.org/10.5194/isprs-annals-IV-2-W4-157-2017, 2017
G. Mandlburger, K. Wenzel, A. Spitzer, N. Haala, P. Glira, and N. Pfeifer
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2-W4, 259–266, https://doi.org/10.5194/isprs-annals-IV-2-W4-259-2017, https://doi.org/10.5194/isprs-annals-IV-2-W4-259-2017, 2017
M. Pöchtrager, G. Styhler-Aydın, M. Döring-Williams, and N. Pfeifer
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2-W2, 195–202, https://doi.org/10.5194/isprs-annals-IV-2-W2-195-2017, https://doi.org/10.5194/isprs-annals-IV-2-W2-195-2017, 2017
A. Zlinszky, B. Deák, A. Kania, A. Schroiff, and N. Pfeifer
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B8, 1293–1299, https://doi.org/10.5194/isprs-archives-XLI-B8-1293-2016, https://doi.org/10.5194/isprs-archives-XLI-B8-1293-2016, 2016
W. Y. Li, C. Liu, and J. Gao
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B8, 105–107, https://doi.org/10.5194/isprs-archives-XLI-B8-105-2016, https://doi.org/10.5194/isprs-archives-XLI-B8-105-2016, 2016
T. Qu, P. Lu, C. Liu, and H. Wan
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B1, 89–91, https://doi.org/10.5194/isprs-archives-XLI-B1-89-2016, https://doi.org/10.5194/isprs-archives-XLI-B1-89-2016, 2016
Livia Piermattei, Luca Carturan, Fabrizio de Blasi, Paolo Tarolli, Giancarlo Dalla Fontana, Antonio Vettore, and Norbert Pfeifer
Earth Surf. Dynam., 4, 425–443, https://doi.org/10.5194/esurf-4-425-2016, https://doi.org/10.5194/esurf-4-425-2016, 2016
Short summary
Short summary
We investigated the applicability of the SfM–MVS approach for calculating the geodetic mass balance of a glacier and for the detection of the surface displacement rate of an active rock glacier located in the eastern Italian Alps. The results demonstrate that it is possible to reliably quantify the investigated glacial and periglacial processes by means of a quick ground-based photogrammetric survey that was conducted using a consumer grade SRL camera and natural targets as ground control points.
Mathias Harzhauser, Ana Djuricic, Oleg Mandic, Thomas A. Neubauer, Martin Zuschin, and Norbert Pfeifer
Biogeosciences, 13, 1223–1235, https://doi.org/10.5194/bg-13-1223-2016, https://doi.org/10.5194/bg-13-1223-2016, 2016
Short summary
Short summary
We present the first analysis of population structure and cohort distribution in a fossil oyster reef. Data are derived from Terrestrial Laser Scanning of a Miocene shell bed covering 459 m². A growth model was calculated, revealing this species as the giant oyster Crassostrea gryphoides was the fastest growing oyster known so far. The shell half-lives range around few years, indicating that oyster reefs were geologically short-lived structures, which were degraded on a decadal scale.
A. Zlinszky, G. Timár, R. Weber, B. Székely, C. Briese, C. Ressl, and N. Pfeifer
Solid Earth, 5, 355–369, https://doi.org/10.5194/se-5-355-2014, https://doi.org/10.5194/se-5-355-2014, 2014
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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