- Article
(2952 KB) - Metadata XML
- July 11, 2026
- |
- Home
- |
- Sitemap
- |
- The ISPRS Foundation
- |
- 𝕏
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Articles | Volume XLVIII-2/W2-2022
https://doi.org/10.5194/isprs-archives-XLVIII-2-W2-2022-53-2022
© Author(s) 2022. 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-archives-XLVIII-2-W2-2022-53-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
08 Dec 2022
| 08 Dec 2022
CHARACTERIZATION OF MORPHOLOGICAL SURFACE ACTIVITIES DERIVED FROM NEAR-CONTINUOUS TERRESTRIAL LIDAR TIME SERIES
D. Hulskemper
Dept. of Geoscience and Remote Sensing, Faculty of Civil Engineering and Geoscience, Delft University of Technology, The Netherlands
3DGeo Research Group, Institute of Geography, Heidelberg University, Germany
K. Anders
3DGeo Research Group, Institute of Geography, Heidelberg University, Germany
J. A. Á. Antolínez
Dept. of Hydraulic Engineering, Faculty of Civil Engineering and Geoscience, Delft University of Technology, The Netherlands
M. Kuschnerus
Dept. of Geoscience and Remote Sensing, Faculty of Civil Engineering and Geoscience, Delft University of Technology, The Netherlands
3DGeo Research Group, Institute of Geography, Heidelberg University, Germany
R. Lindenbergh
Dept. of Geoscience and Remote Sensing, Faculty of Civil Engineering and Geoscience, Delft University of Technology, The Netherlands
Related authors
No articles found.
Mahmoud H. Ahmed, Roderik Lindenbergh, Massimo Menenti, and Joris Timmermans
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., XI-3-2026, 695–704, https://doi.org/10.5194/isprs-annals-XI-3-2026-695-2026, https://doi.org/10.5194/isprs-annals-XI-3-2026-695-2026, 2026
Felix Dahle, Roderik Lindenbergh, and Bert Wouters
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., XI-3-2026, 671–678, https://doi.org/10.5194/isprs-annals-XI-3-2026-671-2026, https://doi.org/10.5194/isprs-annals-XI-3-2026-671-2026, 2026
Xiaoyu Huang, Mathilde Letard, Dimitri Lague, Bernhard Höfle, Ronald Tabernig, Paul Leroy, and Katharina Anders
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., XI-2-2026, 623–630, https://doi.org/10.5194/isprs-annals-XI-2-2026-623-2026, https://doi.org/10.5194/isprs-annals-XI-2-2026-623-2026, 2026
Jiapan Wang, Xiaoyu Huang, Pim Maydhisudhiwongs, Mathilde Letard, Balthasar Teuscher, Prabin Gyawali, Martin Werner, and Katharina Anders
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., XI-2-2026, 545–552, https://doi.org/10.5194/isprs-annals-XI-2-2026-545-2026, https://doi.org/10.5194/isprs-annals-XI-2-2026-545-2026, 2026
Mathilde Letard, Peter Naylor, and Katharina Anders
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., XI-2-2026, 527–534, https://doi.org/10.5194/isprs-annals-XI-2-2026-527-2026, https://doi.org/10.5194/isprs-annals-XI-2-2026-527-2026, 2026
Ronald Tabernig and Bernhard Höfle
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., XI-2-2026, 155–162, https://doi.org/10.5194/isprs-annals-XI-2-2026-155-2026, https://doi.org/10.5194/isprs-annals-XI-2-2026-155-2026, 2026
Daan Hulskemper, Hannah Weiser, Ronald Tabernig, Bernhard Höfle, Thomas de Jong, and Roderik Lindenbergh
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., XI-1-2026, 91–99, https://doi.org/10.5194/isprs-annals-XI-1-2026-91-2026, https://doi.org/10.5194/isprs-annals-XI-1-2026-91-2026, 2026
Daan Hulskemper, José A. Á. Antolínez, Roderik Lindenbergh, and Katharina Anders
Earth Surf. Dynam., 14, 329–359, https://doi.org/10.5194/esurf-14-329-2026, https://doi.org/10.5194/esurf-14-329-2026, 2026
Short summary
Short summary
We developed a new method to automatically detect and group short-term topographic changes on sandy beaches using hourly 3D laser scans collected over three years. By distinguishing variations in patterns of sand deposition and erosion, the approach allows scientists to study how beaches change at different moments in time and link these changes to environmental conditions like winds, waves or bulldozers, improving understanding and prediction of dynamics of sandy beaches.
Lotte de Vugt, Edoardo Carraro, Ayoub Fatihi, Enrico Mattea, Eleanor Myall, Daniel Czerwonka-Schröder, and Katharina Anders
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-G-2025, 359–365, https://doi.org/10.5194/isprs-archives-XLVIII-G-2025-359-2025, https://doi.org/10.5194/isprs-archives-XLVIII-G-2025-359-2025, 2025
Jiapan Wang and Katharina Anders
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., X-G-2025, 929–936, https://doi.org/10.5194/isprs-annals-X-G-2025-929-2025, https://doi.org/10.5194/isprs-annals-X-G-2025-929-2025, 2025
Jannik S. Meyer, Ronald Tabernig, and Bernhard Höfle
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., X-G-2025, 583–590, https://doi.org/10.5194/isprs-annals-X-G-2025-583-2025, https://doi.org/10.5194/isprs-annals-X-G-2025-583-2025, 2025
William Albert, Hannah Weiser, Ronald Tabernig, and Bernhard Höfle
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., X-G-2025, 25–32, https://doi.org/10.5194/isprs-annals-X-G-2025-25-2025, https://doi.org/10.5194/isprs-annals-X-G-2025-25-2025, 2025
Yushan Liu, Alireza Amiri-Simkooei, Roderik Lindenbergh, and Mirjam Snellen
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-2-W10-2025, 169–176, https://doi.org/10.5194/isprs-archives-XLVIII-2-W10-2025-169-2025, https://doi.org/10.5194/isprs-archives-XLVIII-2-W10-2025-169-2025, 2025
Lucas Terlinden-Ruhl, Anaïs Couasnon, Dirk Eilander, Gijs G. Hendrickx, Patricia Mares-Nasarre, and José A. Á. Antolínez
Nat. Hazards Earth Syst. Sci., 25, 1353–1375, https://doi.org/10.5194/nhess-25-1353-2025, https://doi.org/10.5194/nhess-25-1353-2025, 2025
Short summary
Short summary
This study develops a conceptual framework that uses active learning to accelerate compound flood risk assessments. A case study of Charleston County shows that the framework achieves faster and more accurate risk quantification compared to the state-of-the-art. This win–win allows for an increase in the number of flooding parameters, which results in an 11.6 % difference in the expected annual damages. Therefore, this framework allows for more comprehensive compound flood risk assessments.
Robert McCall, Curt Storlazzi, Floortje Roelvink, Stuart G. Pearson, Roel de Goede, and José A. Á. Antolínez
Nat. Hazards Earth Syst. Sci., 24, 3597–3625, https://doi.org/10.5194/nhess-24-3597-2024, https://doi.org/10.5194/nhess-24-3597-2024, 2024
Short summary
Short summary
Accurate predictions of wave-driven flooding are essential to manage risk on low-lying, reef-lined coasts. Models to provide this information are, however, computationally expensive. We present and validate a modeling system that simulates flood drivers on diverse and complex reef-lined coasts as competently as a full-physics model but at a fraction of the computational cost to run. This development paves the way for application in large-scale early-warning systems and flood risk assessments.
Kees Nederhoff, Maarten van Ormondt, Jay Veeramony, Ap van Dongeren, José Antonio Álvarez Antolínez, Tim Leijnse, and Dano Roelvink
Geosci. Model Dev., 17, 1789–1811, https://doi.org/10.5194/gmd-17-1789-2024, https://doi.org/10.5194/gmd-17-1789-2024, 2024
Short summary
Short summary
Forecasting tropical cyclones and their flooding impact is challenging. Our research introduces the Tropical Cyclone Forecasting Framework (TC-FF), enhancing cyclone predictions despite uncertainties. TC-FF generates global wind and flood scenarios, valuable even in data-limited regions. Applied to cases like Cyclone Idai, it showcases potential in bettering disaster preparation, marking progress in handling cyclone threats.
M. Potůčková, J. Albrechtová, K. Anders, L. Červená, J. Dvořák, K. Gryguc, B. Höfle, L. Hunt, Z. Lhotáková, A. Marcinkowska-Ochtyra, A. Mayr, E. Neuwirthová, A. Ochtyra, M. Rutzinger, A. Šedová, A. Šrollerů, and L. Kupková
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-W2-2023, 989–996, https://doi.org/10.5194/isprs-archives-XLVIII-1-W2-2023-989-2023, https://doi.org/10.5194/isprs-archives-XLVIII-1-W2-2023-989-2023, 2023
Adriaan L. van Natijne, Thom A. Bogaard, Thomas Zieher, Jan Pfeiffer, and Roderik C. Lindenbergh
Nat. Hazards Earth Syst. Sci., 23, 3723–3745, https://doi.org/10.5194/nhess-23-3723-2023, https://doi.org/10.5194/nhess-23-3723-2023, 2023
Short summary
Short summary
Landslides are one of the major weather-related geohazards. To assess their potential impact and design mitigation solutions, a detailed understanding of the slope is required. We tested if the use of machine learning, combined with satellite remote sensing data, would allow us to forecast deformation. Our results on the Vögelsberg landslide, a deep-seated landslide near Innsbruck, Austria, show that the formulation of such a machine learning system is not as straightforward as often hoped for.
Lukas Winiwarter, Katharina Anders, Daniel Czerwonka-Schröder, and Bernhard Höfle
Earth Surf. Dynam., 11, 593–613, https://doi.org/10.5194/esurf-11-593-2023, https://doi.org/10.5194/esurf-11-593-2023, 2023
Short summary
Short summary
We present a method to extract surface change information from 4D time series of topographic point clouds recorded with a terrestrial laser scanner. The method uses sensor information to spatially and temporally smooth the data, reducing uncertainties. The Kalman filter used for the temporal smoothing also allows us to interpolate over data gaps or extrapolate into the future. Clustering areas where change histories are similar allows us to identify processes that may have the same causes.
Lea Hartl, Thomas Zieher, Magnus Bremer, Martin Stocker-Waldhuber, Vivien Zahs, Bernhard Höfle, Christoph Klug, and Alessandro Cicoira
Earth Surf. Dynam., 11, 117–147, https://doi.org/10.5194/esurf-11-117-2023, https://doi.org/10.5194/esurf-11-117-2023, 2023
Short summary
Short summary
The rock glacier in Äußeres Hochebenkar (Austria) moved faster in 2021–2022 than it has in about 70 years of monitoring. It is currently destabilizing. Using a combination of different data types and methods, we show that there have been two cycles of destabilization at Hochebenkar and provide a detailed analysis of velocity and surface changes. Because our time series are very long and show repeated destabilization, this helps us better understand the processes of rock glacier destabilization.
J. P. Meinderts, R. Lindenbergh, D. H. van der Heide, A. Amiri-Simkooei, and L. Truong-Hong
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-2-W2-2022, 69–76, https://doi.org/10.5194/isprs-archives-XLVIII-2-W2-2022-69-2022, https://doi.org/10.5194/isprs-archives-XLVIII-2-W2-2022-69-2022, 2022
Panagiotis Athanasiou, Ap van Dongeren, Alessio Giardino, Michalis Vousdoukas, Jose A. A. Antolinez, and Roshanka Ranasinghe
Nat. Hazards Earth Syst. Sci., 22, 3897–3915, https://doi.org/10.5194/nhess-22-3897-2022, https://doi.org/10.5194/nhess-22-3897-2022, 2022
Short summary
Short summary
Sandy dunes protect the hinterland from coastal flooding during storms. Thus, models that can efficiently predict dune erosion are critical for coastal zone management and early warning systems. Here we develop such a model for the Dutch coast based on machine learning techniques, allowing for dune erosion estimations in a matter of seconds relative to available computationally expensive models. Validation of the model against benchmark data and observations shows good agreement.
L. Truong-Hong, R. C. Lindenbergh, and M. J. Vermeij
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4-W4-2022, 161–168, https://doi.org/10.5194/isprs-archives-XLVIII-4-W4-2022-161-2022, https://doi.org/10.5194/isprs-archives-XLVIII-4-W4-2022-161-2022, 2022
Hannah Weiser, Jannika Schäfer, Lukas Winiwarter, Nina Krašovec, Fabian E. Fassnacht, and Bernhard Höfle
Earth Syst. Sci. Data, 14, 2989–3012, https://doi.org/10.5194/essd-14-2989-2022, https://doi.org/10.5194/essd-14-2989-2022, 2022
Short summary
Short summary
3D point clouds, acquired by laser scanning, allow us to retrieve information about forest structure and individual tree properties. We conducted airborne, UAV-borne and terrestrial laser scanning in German mixed forests, resulting in overlapping point clouds with different characteristics. From these, we generated a comprehensive database of individual tree point clouds and corresponding tree metrics. Our dataset may serve as a benchmark dataset for algorithms in forestry research.
K. Anders, L. Winiwarter, D. Schröder, and B. Höfle
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2022, 973–980, https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-973-2022, https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-973-2022, 2022
A. Nurunnabi, F. N. Teferle, R. C. Lindenbergh, J. Li, and S. Zlatanova
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B1-2022, 59–66, https://doi.org/10.5194/isprs-archives-XLIII-B1-2022-59-2022, https://doi.org/10.5194/isprs-archives-XLIII-B1-2022-59-2022, 2022
H. S. Kathmann, A. L. van Natijne, and R. C. Lindenbergh
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2022, 1033–1040, https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-1033-2022, https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-1033-2022, 2022
M. Kuschnerus, R. Lindenbergh, Q. Lodder, E. Brand, and S. Vos
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2022, 1055–1061, https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-1055-2022, https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-1055-2022, 2022
V. Zahs, L. Winiwarter, K. Anders, M. Bremer, M. Rutzinger, M. Potůčková, and B. Höfle
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2022, 1109–1116, https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-1109-2022, https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-1109-2022, 2022
F. Dahle, J. Tanke, B. Wouters, and R. Lindenbergh
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2022, 237–244, https://doi.org/10.5194/isprs-annals-V-2-2022-237-2022, https://doi.org/10.5194/isprs-annals-V-2-2022-237-2022, 2022
L. Winiwarter, K. Anders, D. Schröder, and B. Höfle
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2022, 79–86, https://doi.org/10.5194/isprs-annals-V-2-2022-79-2022, https://doi.org/10.5194/isprs-annals-V-2-2022-79-2022, 2022
A. Nurunnabi, F. N. Teferle, D. F. Laefer, R. C. Lindenbergh, and A. Hunegnaw
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-2-W1-2022, 401–408, https://doi.org/10.5194/isprs-archives-XLVI-2-W1-2022-401-2022, https://doi.org/10.5194/isprs-archives-XLVI-2-W1-2022-401-2022, 2022
A. Nurunnabi, F. N. Teferle, J. Li, R. C. Lindenbergh, and S. Parvaz
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-4-W5-2021, 397–404, https://doi.org/10.5194/isprs-archives-XLVI-4-W5-2021-397-2021, https://doi.org/10.5194/isprs-archives-XLVI-4-W5-2021-397-2021, 2021
L. Truong-Hong, N. Nguyen, R. Lindenbergh, P. Fisk, and T. Huynh
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-4-W4-2021, 119–124, https://doi.org/10.5194/isprs-archives-XLVI-4-W4-2021-119-2021, https://doi.org/10.5194/isprs-archives-XLVI-4-W4-2021-119-2021, 2021
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