- Article
(1536 KB) - Metadata XML
- July 01, 2025
- |
- Home
- |
- Sitemap
- |
- The ISPRS Foundation
- |
- 𝕏
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Articles | Volume X-M-1-2023
https://doi.org/10.5194/isprs-annals-X-M-1-2023-285-2023
© Author(s) 2023. 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-M-1-2023-285-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
23 Jun 2023
| 23 Jun 2023
TRACKING THE URBAN CHAMELEON – TOWARDS A HYBRID CHANGE DETECTION OF GRAFFITI
Research Unit Photogrammetry – TU Wien, Vienna , Austria
G. Verhoeven
Ludwig Boltzmann Gesellschaft – LBI ArchPro (Austria), Vienna, Austria
N. Pfeifer
Research Unit Photogrammetry – TU Wien, Vienna , Austria
Related authors
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
Benjamin Wild, Irene Teubner, Leander Moesinger, Ruxandra-Maria Zotta, Matthias Forkel, Robin van der Schalie, Stephen Sitch, and Wouter Dorigo
Earth Syst. Sci. Data, 14, 1063–1085, https://doi.org/10.5194/essd-14-1063-2022, https://doi.org/10.5194/essd-14-1063-2022, 2022
Short summary
Short summary
Gross primary production (GPP) describes the conversion of CO2 to carbohydrates and can be seen as a filter for our atmosphere of the primary greenhouse gas CO2. We developed VODCA2GPP, a GPP dataset that is based on vegetation optical depth from microwave remote sensing and temperature. Thus, it is mostly independent from existing GPP datasets and also available in regions with frequent cloud coverage. Analysis showed that VODCA2GPP is able to complement existing state-of-the-art GPP datasets.
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
Irene E. Teubner, Matthias Forkel, Benjamin Wild, Leander Mösinger, and Wouter Dorigo
Biogeosciences, 18, 3285–3308, https://doi.org/10.5194/bg-18-3285-2021, https://doi.org/10.5194/bg-18-3285-2021, 2021
Short summary
Short summary
Vegetation optical depth (VOD), which contains information on vegetation water content and biomass, has been previously shown to be related to gross primary production (GPP). In this study, we analyzed the impact of adding temperature as model input and investigated if this can reduce the previously observed overestimation of VOD-derived GPP. In addition, we could show that the relationship between VOD and GPP largely holds true along a gradient of dry or wet conditions.
Florian Pöppl, Andrea Spitzer, Andreas Ullrich, and Norbert Pfeifer
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-W4-2025, 109–114, https://doi.org/10.5194/isprs-archives-XLVIII-1-W4-2025-109-2025, https://doi.org/10.5194/isprs-archives-XLVIII-1-W4-2025-109-2025, 2025
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
Bernhard Hynek, Daniel Binder, Michele Citterio, Signe Hillerup Larsen, Jakob Abermann, Geert Verhoeven, Elke Ludewig, and Wolfgang Schöner
The Cryosphere, 18, 5481–5494, https://doi.org/10.5194/tc-18-5481-2024, https://doi.org/10.5194/tc-18-5481-2024, 2024
Short summary
Short summary
An avalanche event in February 2018 caused thick snow deposits on Freya Glacier, a peripheral mountain glacier in northeastern Greenland. The avalanche deposits contributed significantly to the mass balance, leaving a strong imprint in the elevation changes in 2013–2021. The 8-year geodetic mass balance (2013–2021) of the glacier is positive, whereas previous estimates by direct measurements were negative and now turned out to have a negative bias.
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.
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
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
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
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
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
Benjamin Wild, Irene Teubner, Leander Moesinger, Ruxandra-Maria Zotta, Matthias Forkel, Robin van der Schalie, Stephen Sitch, and Wouter Dorigo
Earth Syst. Sci. Data, 14, 1063–1085, https://doi.org/10.5194/essd-14-1063-2022, https://doi.org/10.5194/essd-14-1063-2022, 2022
Short summary
Short summary
Gross primary production (GPP) describes the conversion of CO2 to carbohydrates and can be seen as a filter for our atmosphere of the primary greenhouse gas CO2. We developed VODCA2GPP, a GPP dataset that is based on vegetation optical depth from microwave remote sensing and temperature. Thus, it is mostly independent from existing GPP datasets and also available in regions with frequent cloud coverage. Analysis showed that VODCA2GPP is able to complement existing state-of-the-art GPP datasets.
E. Nocerino, F. Menna, and G. J. Verhoeven
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-2-W1-2022, 395–400, https://doi.org/10.5194/isprs-archives-XLVI-2-W1-2022-395-2022, https://doi.org/10.5194/isprs-archives-XLVI-2-W1-2022-395-2022, 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.
G. J. Verhoeven, M. Santner, and I. Trinks
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., VIII-M-1-2021, 171–178, https://doi.org/10.5194/isprs-annals-VIII-M-1-2021-171-2021, https://doi.org/10.5194/isprs-annals-VIII-M-1-2021-171-2021, 2021
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
Irene E. Teubner, Matthias Forkel, Benjamin Wild, Leander Mösinger, and Wouter Dorigo
Biogeosciences, 18, 3285–3308, https://doi.org/10.5194/bg-18-3285-2021, https://doi.org/10.5194/bg-18-3285-2021, 2021
Short summary
Short summary
Vegetation optical depth (VOD), which contains information on vegetation water content and biomass, has been previously shown to be related to gross primary production (GPP). In this study, we analyzed the impact of adding temperature as model input and investigated if this can reduce the previously observed overestimation of VOD-derived GPP. In addition, we could show that the relationship between VOD and GPP largely holds true along a gradient of dry or wet conditions.
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
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
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
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
S. Štuhec, G. Verhoeven, and I. Štuhec
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W9, 691–698, https://doi.org/10.5194/isprs-archives-XLII-2-W9-691-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W9-691-2019, 2019
G. J. Verhoeven
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2, 1149–1156, https://doi.org/10.5194/isprs-archives-XLII-2-1149-2018, https://doi.org/10.5194/isprs-archives-XLII-2-1149-2018, 2018
N. Li, N. Pfeifer, and C. Liu
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2-W4, 107–114, https://doi.org/10.5194/isprs-annals-IV-2-W4-107-2017, https://doi.org/10.5194/isprs-annals-IV-2-W4-107-2017, 2017
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
G. J. Verhoeven
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2-W2, 295–302, https://doi.org/10.5194/isprs-annals-IV-2-W2-295-2017, https://doi.org/10.5194/isprs-annals-IV-2-W2-295-2017, 2017
G. J. Verhoeven and S. J. Missinne
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2-W2, 303–310, https://doi.org/10.5194/isprs-annals-IV-2-W2-303-2017, https://doi.org/10.5194/isprs-annals-IV-2-W2-303-2017, 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
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