- Article
(2446 KB) - Metadata XML
- December 22, 2024
- |
- Home
- |
- Sitemap
- |
- The ISPRS Foundation
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
Related authors
No articles found.
Martin Wieser, Geert Verhoeven, Benjamin Wild, and Norbert Pfeifer
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-2-W8-2024, 463–470, https://doi.org/10.5194/isprs-archives-XLVIII-2-W8-2024-463-2024, https://doi.org/10.5194/isprs-archives-XLVIII-2-W8-2024-463-2024, 2024
Thirawat Bannakulpiphat, Wilfried Karel, Camillo Ressl, and Norbert Pfeifer
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-2-W7-2024, 17–24, https://doi.org/10.5194/isprs-archives-XLVIII-2-W7-2024-17-2024, https://doi.org/10.5194/isprs-archives-XLVIII-2-W7-2024-17-2024, 2024
Günter Blöschl, Andreas Buttinger-Kreuzhuber, Daniel Cornel, Julia Eisl, Michael Hofer, Markus Hollaus, Zsolt Horváth, Jürgen Komma, Artem Konev, Juraj Parajka, Norbert Pfeifer, Andreas Reithofer, José Salinas, Peter Valent, Roman Výleta, Jürgen Waser, Michael H. Wimmer, and Heinz Stiefelmeyer
Nat. Hazards Earth Syst. Sci., 24, 2071–2091, https://doi.org/10.5194/nhess-24-2071-2024, https://doi.org/10.5194/nhess-24-2071-2024, 2024
Short summary
Short summary
A methodology of regional flood hazard mapping is proposed, based on data in Austria, which combines automatic methods with manual interventions to maximise efficiency and to obtain estimation accuracy similar to that of local studies. Flood discharge records from 781 stations are used to estimate flood hazard patterns of a given return period at a resolution of 2 m over a total stream length of 38 000 km. The hazard maps are used for civil protection, risk awareness and insurance purposes.
S. Zhang, W. Zhang, and C. Liu
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-W2-2023, 1923–1928, https://doi.org/10.5194/isprs-archives-XLVIII-1-W2-2023-1923-2023, https://doi.org/10.5194/isprs-archives-XLVIII-1-W2-2023-1923-2023, 2023
C. Liu, Y. Li, J. Gu, Y. Lou, and T. Shen
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., X-1-W1-2023, 319–328, https://doi.org/10.5194/isprs-annals-X-1-W1-2023-319-2023, https://doi.org/10.5194/isprs-annals-X-1-W1-2023-319-2023, 2023
F. Pöppl, G. Mandlburger, and N. Pfeifer
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-W3-2023, 161–166, https://doi.org/10.5194/isprs-archives-XLVIII-1-W3-2023-161-2023, https://doi.org/10.5194/isprs-archives-XLVIII-1-W3-2023-161-2023, 2023
B. Wild, G. Verhoeven, and N. Pfeifer
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., X-M-1-2023, 285–292, https://doi.org/10.5194/isprs-annals-X-M-1-2023-285-2023, https://doi.org/10.5194/isprs-annals-X-M-1-2023-285-2023, 2023
I. Cortesi, A. Masiero, N. Pfeifer, and G. Tucci
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-W1-2023, 101–106, https://doi.org/10.5194/isprs-archives-XLVIII-1-W1-2023-101-2023, https://doi.org/10.5194/isprs-archives-XLVIII-1-W1-2023-101-2023, 2023
F. Pöppl, H. Teufelsbauer, A. Ullrich, and N. Pfeifer
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-W1-2023, 403–410, https://doi.org/10.5194/isprs-archives-XLVIII-1-W1-2023-403-2023, https://doi.org/10.5194/isprs-archives-XLVIII-1-W1-2023-403-2023, 2023
S. Zhao, C. Liu, and J. Zhang
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-2-W3-2023, 269–274, https://doi.org/10.5194/isprs-archives-XLVIII-2-W3-2023-269-2023, https://doi.org/10.5194/isprs-archives-XLVIII-2-W3-2023-269-2023, 2023
Livia Piermattei, Tobias Heckmann, Sarah Betz-Nutz, Moritz Altmann, Jakob Rom, Fabian Fleischer, Manuel Stark, Florian Haas, Camillo Ressl, Michael H. Wimmer, Norbert Pfeifer, and Michael Becht
Earth Surf. Dynam., 11, 383–403, https://doi.org/10.5194/esurf-11-383-2023, https://doi.org/10.5194/esurf-11-383-2023, 2023
Short summary
Short summary
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.
N. Homainejad, S. Zlatanova, S. M. E. Sepasgozar, and N. Pfeifer
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., X-4-W2-2022, 113–119, https://doi.org/10.5194/isprs-annals-X-4-W2-2022-113-2022, https://doi.org/10.5194/isprs-annals-X-4-W2-2022-113-2022, 2022
C. Liu and S. Wang
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-1-2022, 25–32, https://doi.org/10.5194/isprs-annals-V-1-2022-25-2022, https://doi.org/10.5194/isprs-annals-V-1-2022-25-2022, 2022
R. Arav, F. Pöppl, and N. Pfeifer
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2022, 95–102, https://doi.org/10.5194/isprs-annals-V-2-2022-95-2022, https://doi.org/10.5194/isprs-annals-V-2-2022-95-2022, 2022
C. Liu and Y. Qi
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2022, 375–382, https://doi.org/10.5194/isprs-annals-V-2-2022-375-2022, https://doi.org/10.5194/isprs-annals-V-2-2022-375-2022, 2022
N. Homainejad, S. Zlatanova, and N. Pfeifer
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2022, 697–704, https://doi.org/10.5194/isprs-annals-V-3-2022-697-2022, https://doi.org/10.5194/isprs-annals-V-3-2022-697-2022, 2022
G. Verhoeven, B. Wild, J. Schlegel, M. Wieser, N. Pfeifer, S. Wogrin, L. Eysn, M. Carloni, B. Koschiček-Krombholz, A. Molada-Tebar, J. Otepka-Schremmer, C. Ressl, M. Trognitz, and A. Watzinger
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-2-W1-2022, 513–520, https://doi.org/10.5194/isprs-archives-XLVI-2-W1-2022-513-2022, https://doi.org/10.5194/isprs-archives-XLVI-2-W1-2022-513-2022, 2022
Fabian Fleischer, Florian Haas, Livia Piermattei, Madlene Pfeiffer, Tobias Heckmann, Moritz Altmann, Jakob Rom, Manuel Stark, Michael H. Wimmer, Norbert Pfeifer, and Michael Becht
The Cryosphere, 15, 5345–5369, https://doi.org/10.5194/tc-15-5345-2021, https://doi.org/10.5194/tc-15-5345-2021, 2021
Short summary
Short summary
We investigate the long-term (1953–2017) morphodynamic changes in rock glaciers in Kaunertal valley, Austria. Using a combination of historical aerial photographs and laser scanning data, we derive information on flow velocities and surface elevation changes. We observe a loss of volume and an acceleration from the late 1990s onwards. We explain this by changes in the meteorological forcing. Individual rock glaciers react to these changes to varying degrees.
A. Iglseder, M. Bruggisser, A. Dostálová, N. Pfeifer, S. Schlaffer, W. Wagner, and M. Hollaus
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2021, 567–574, https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-567-2021, https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-567-2021, 2021
J. Otepka, G. Mandlburger, W. Karel, B. Wöhrer, C. Ressl, and N. Pfeifer
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2021, 35–42, https://doi.org/10.5194/isprs-annals-V-2-2021-35-2021, https://doi.org/10.5194/isprs-annals-V-2-2021-35-2021, 2021
C. Liu, X. Zhou, Y. Zhou, and A. Akbar
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2020, 1469–1475, https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-1469-2020, https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-1469-2020, 2020
J. Na, G. Tang, K. Wang, and N. Pfeifer
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2020, 1485–1490, https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-1485-2020, https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-1485-2020, 2020
M. Ai, C. Liu, H. Shen, and F. Cheng
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2020, 177–182, https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-177-2020, https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-177-2020, 2020
J. Otepka, G. Mandlburger, M. Schütz, N. Pfeifer, and M. Wimmer
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2020, 293–300, https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-293-2020, https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-293-2020, 2020
F. Cheng, C. Liu, H. Wu, and M. Ai
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2020, 757–763, https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-757-2020, https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-757-2020, 2020
S. Zhang, C. Liu, and N. Haala
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-1-2020, 325–331, https://doi.org/10.5194/isprs-annals-V-1-2020-325-2020, https://doi.org/10.5194/isprs-annals-V-1-2020-325-2020, 2020
A-M. Loghin, N. Pfeifer, and J. Otepka-Schremmer
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2020, 525–532, https://doi.org/10.5194/isprs-annals-V-2-2020-525-2020, https://doi.org/10.5194/isprs-annals-V-2-2020-525-2020, 2020
S. Flöry, C. Ressl, M. Hollaus, G. Pürcher, L. Piermattei, and N. Pfeifer
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2020, 695–701, https://doi.org/10.5194/isprs-annals-V-2-2020-695-2020, https://doi.org/10.5194/isprs-annals-V-2-2020-695-2020, 2020
N. Li and N. Pfeifer
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 1033–1037, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1033-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1033-2019, 2019
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
T. Qu, Q. Xu, C. Liu, Z. Li, B. Chen, and K. Dai
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 1939–1943, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1939-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1939-2019, 2019
J. Na, X. Yang, X. Fang, G. Tang, and N. Pfeifer
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
M. Bruggisser, M. Hollaus, D. Kükenbrink, and N. Pfeifer
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2-W5, 325–332, https://doi.org/10.5194/isprs-annals-IV-2-W5-325-2019, https://doi.org/10.5194/isprs-annals-IV-2-W5-325-2019, 2019
G. Mandlburger, H. Lehner, and N. Pfeifer
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2-W5, 397–404, https://doi.org/10.5194/isprs-annals-IV-2-W5-397-2019, https://doi.org/10.5194/isprs-annals-IV-2-W5-397-2019, 2019
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
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2-W4, 123–130, https://doi.org/10.5194/isprs-annals-IV-2-W4-123-2017, https://doi.org/10.5194/isprs-annals-IV-2-W4-123-2017, 2017
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.
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