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The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Articles | Volume XLVIII-1/W2-2023
https://doi.org/10.5194/isprs-archives-XLVIII-1-W2-2023-1235-2023
© 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-archives-XLVIII-1-W2-2023-1235-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
13 Dec 2023
| 13 Dec 2023
EUROPEAN GROUND MOTION SERVICE FOR BRIDGE MONITORING: TEMPORAL AND THERMAL DEFORMATION CROSS-CHECK USING COSMO-SKYMED INSAR
R. Eskandari
Dept. of Architecture, Built Environment and Construction Engineering, Politecnico di Milano via Ponzio 31, 20133 Milano, Italy
M. Scaioni
Dept. of Architecture, Built Environment and Construction Engineering, Politecnico di Milano via Ponzio 31, 20133 Milano, Italy
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Short summary
Short summary
We propose an innovative multi-satellite DEM adjustment model (MDAM) that removes biases in elevation between sub-DEMs across ice shelves. Our results reveal quantitative 3D structural and mélange features of a ~50 km long rift. For first time, we found that while the mélange elevation decreased from 2014–2021, the mélange inside the rift experienced a rapid expansion, attributing to newly calved shelf ice from rift walls, associated rift widening, and other rift-mélange interaction factors.
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M. Rutzinger, K. Anders, M. Bremer, B. Höfle, R. Lindenbergh, S. Oude Elberink, F. Pirotti, M. Scaioni, and T. Zieher
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D. Backes, M. Smigaj, M. Schimka, V. Zahs, A. Grznárová, and M. Scaioni
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2020, 1017–1024, https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-1017-2020, https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-1017-2020, 2020
M. Di Rita, D. Fugazza, V. Belloni, G. Diolaiuti, M. Scaioni, and M. Crespi
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2020, 1041–1048, https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-1041-2020, https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-1041-2020, 2020
J. Wang, H. B. Zheng, and M. Scaioni
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W10, 235–243, https://doi.org/10.5194/isprs-archives-XLII-3-W10-235-2020, https://doi.org/10.5194/isprs-archives-XLII-3-W10-235-2020, 2020
A. Mostafavi, M. Scaioni, and V. Yordanov
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4-W18, 765–772, https://doi.org/10.5194/isprs-archives-XLII-4-W18-765-2019, https://doi.org/10.5194/isprs-archives-XLII-4-W18-765-2019, 2019
V. Yordanov, D. Fugazza, R. S. Azzoni, M. Cernuschi, M. Scaioni, and G. A. Diolaiuti
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 1803–1810, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1803-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1803-2019, 2019
V. Yordanov, A. Mostafavi, and M. Scaioni
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W11, 1165–1172, https://doi.org/10.5194/isprs-archives-XLII-2-W11-1165-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W11-1165-2019, 2019
R. Brumana, V. Pracchi, F. Rinaudo, A. Grimoldi, M. Scaioni, L. Cantini, and M. Previtali
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W11, 1–2, https://doi.org/10.5194/isprs-archives-XLII-2-W11-1-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W11-1-2019, 2019
L. Díaz-Vilariño, E. Frías, M. Previtali, M. Scaioni, and J. Balado
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W11, 489–494, https://doi.org/10.5194/isprs-archives-XLII-2-W11-489-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W11-489-2019, 2019
D. Wujanz, L. Barazzetti, M. Previtali, and M. Scaioni
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W9, 779–786, https://doi.org/10.5194/isprs-archives-XLII-2-W9-779-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W9-779-2019, 2019
M. Previtali, L. Díaz-Vilariño, and M. Scaioni
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4, 507–514, https://doi.org/10.5194/isprs-archives-XLII-4-507-2018, https://doi.org/10.5194/isprs-archives-XLII-4-507-2018, 2018
M. Scaioni, J. Crippa, M. Corti, L. Barazzetti, D. Fugazza, R. Azzoni, M. Cernuschi, and G. A. Diolaiuti
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2, 1029–1036, https://doi.org/10.5194/isprs-archives-XLII-2-1029-2018, https://doi.org/10.5194/isprs-archives-XLII-2-1029-2018, 2018
S. R. Hosseini, M. Scaioni, and M. Marani
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 527–532, https://doi.org/10.5194/isprs-archives-XLII-3-527-2018, https://doi.org/10.5194/isprs-archives-XLII-3-527-2018, 2018
M. Scaioni, B. Höfle, A. P. Baungarten Kersting, L. Barazzetti, M. Previtali, and D. Wujanz
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 1503–1510, https://doi.org/10.5194/isprs-archives-XLII-3-1503-2018, https://doi.org/10.5194/isprs-archives-XLII-3-1503-2018, 2018
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Nat. Hazards Earth Syst. Sci., 18, 1055–1071, https://doi.org/10.5194/nhess-18-1055-2018, https://doi.org/10.5194/nhess-18-1055-2018, 2018
Short summary
Short summary
This paper describes the surveys we performed in 2014 and 2016 by means of UAVs and terrestrial photogrammetry to monitor the Forni Glacier, one of the largest glaciers in the Italian Alps. We investigated the hazards related to the glacier collapse, which have been increasing recently due to the high ice melting rate. Our approach is feasible and low cost and we will repeatedly monitor the glacier to provide rapid hazard detection services to help the tourism sector.
M. Scaioni, L. Barazzetti, M. Corti, J. Crippa, R. S. Azzoni, D. Fugazza, M. Cernuschi, and G. A. Diolaiuti
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W4, 445–452, https://doi.org/10.5194/isprs-archives-XLII-3-W4-445-2018, https://doi.org/10.5194/isprs-archives-XLII-3-W4-445-2018, 2018
M. Scaioni, J. Crippa, V. Yordanov, L. Longoni, V. I. Ivanov, and M. Papini
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W4, 453–460, https://doi.org/10.5194/isprs-archives-XLII-3-W4-453-2018, https://doi.org/10.5194/isprs-archives-XLII-3-W4-453-2018, 2018
M. Cogliati, E. Tonelli, D. Battaglia, and M. Scaioni
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-5-W1, 9–16, https://doi.org/10.5194/isprs-annals-IV-5-W1-9-2017, https://doi.org/10.5194/isprs-annals-IV-5-W1-9-2017, 2017
G. López-Pazos, J. Balado, L. Díaz-Vilariño, P. Arias, and M. Scaioni
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-5-W1, 35–41, https://doi.org/10.5194/isprs-annals-IV-5-W1-35-2017, https://doi.org/10.5194/isprs-annals-IV-5-W1-35-2017, 2017
M. Scaioni, J. Crippa, L. Longoni, M. Papini, and L. Zanzi
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-5-W1, 63–70, https://doi.org/10.5194/isprs-annals-IV-5-W1-63-2017, https://doi.org/10.5194/isprs-annals-IV-5-W1-63-2017, 2017
M. Scaioni, M. Corti, G. Diolaiuti, D. Fugazza, and M. Cernuschi
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W7, 1547–1554, https://doi.org/10.5194/isprs-archives-XLII-2-W7-1547-2017, https://doi.org/10.5194/isprs-archives-XLII-2-W7-1547-2017, 2017
M. Scaioni, E. Rosina, A. L’Erario, and L. Dìaz-Vilariño
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-5-W1, 153–160, https://doi.org/10.5194/isprs-archives-XLII-5-W1-153-2017, https://doi.org/10.5194/isprs-archives-XLII-5-W1-153-2017, 2017
V. Yordanov, M. Scaioni, M. T. Brunetti, M. T. Melis, A. Zinzi, and P. Giommi
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B6, 17–24, https://doi.org/10.5194/isprs-archives-XLI-B6-17-2016, https://doi.org/10.5194/isprs-archives-XLI-B6-17-2016, 2016
M. Scaioni, P. Giommi, M. T. Brunetti, C. Carli, P. Cerroni, G. Cremonese, G. Forlani, P. Gamba, M. Lavagna, M. T. Melis, M. Massironi, G. Ori, F. Salese, A. Zinzi, G. Xie, Z. Kang, R. Shi, Y. Sun, and Y. Wu
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B6, 71–78, https://doi.org/10.5194/isprs-archives-XLI-B6-71-2016, https://doi.org/10.5194/isprs-archives-XLI-B6-71-2016, 2016
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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