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Articles | Volume XLVIII-2-2024
https://doi.org/10.5194/isprs-archives-XLVIII-2-2024-99-2024
© Author(s) 2024. 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-2-2024-99-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
11 Jun 2024
| 11 Jun 2024
Multitemporal Structure-from-Motion: A Flexible Tool to Cope with Aerial Blocks in Changing Mountain Environment
Nicola Genzano
Department of Architecture, Built Environment and Construction Engineering (DABC), Politecnico Milano, Milano, Italy
Davide Fugazza
Department of Environmental Science and Policy (DESP), Università degli Studi di Milano, Milano, Italy
Rasoul Eskandari
Department of Architecture, Built Environment and Construction Engineering (DABC), Politecnico Milano, Milano, Italy
Marco Scaioni
Department of Architecture, Built Environment and Construction Engineering (DABC), Politecnico Milano, Milano, Italy
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Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-3-2024, 147–154, https://doi.org/10.5194/isprs-archives-XLVIII-3-2024-147-2024, https://doi.org/10.5194/isprs-archives-XLVIII-3-2024-147-2024, 2024
Nicola Genzano, José Armando Saballos, Wendel Gutierrez, and Francesco Marchese
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M. Parrot, V. Tramutoli, Tiger J. Y. Liu, S. Pulinets, D. Ouzounov, N. Genzano, M. Lisi, K. Hattori, and A. Namgaladze
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2016-172, https://doi.org/10.5194/nhess-2016-172, 2016
Revised manuscript not accepted
Short summary
Short summary
Since tens of years perturbations have been observed in the ionosphere prior to earthquakes (between a few hours and a few days before). But the mechanism to understand how the earthquake preparation in a seismic area can induce a change in the ionosphere is the subject of intense debate. In this paper we present various atmospheric and ionospheric perturbations observed prior to large earthquakes in order to support a model of coupling between the lithosphere, the atmosphere, and the ionosphere.
Rasoul Eskandari, Nicola Genzano, Davide Fugazza, and Marco Scaioni
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-3-2024, 147–154, https://doi.org/10.5194/isprs-archives-XLVIII-3-2024-147-2024, https://doi.org/10.5194/isprs-archives-XLVIII-3-2024-147-2024, 2024
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J. Xu, M. Garramone, Y. Wang, and M. Scaioni
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J. Xu and M. Scaioni
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Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-W1-2023, 411–416, https://doi.org/10.5194/isprs-archives-XLVIII-1-W1-2023-411-2023, https://doi.org/10.5194/isprs-archives-XLVIII-1-W1-2023-411-2023, 2023
M. Scaioni, A. Malekian, and D. Fugazza
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-M-1-2023, 293–300, https://doi.org/10.5194/isprs-archives-XLVIII-M-1-2023-293-2023, https://doi.org/10.5194/isprs-archives-XLVIII-M-1-2023-293-2023, 2023
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The Cryosphere, 17, 427–444, https://doi.org/10.5194/tc-17-427-2023, https://doi.org/10.5194/tc-17-427-2023, 2023
Short summary
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Megadunes are fields of huge snow dunes present in Antarctica and on other planets, important as they present mass loss on the leeward side (glazed snow), on a continent characterized by mass gain. Here, we studied megadunes using remote data and measurements acquired during past field expeditions. We quantified their physical properties and migration and demonstrated that they migrate against slope and wind. We further proposed automatic detections of the glazed snow on their leeward side.
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R. Eskandari and M. Scaioni
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4-W2-2022, 31–38, https://doi.org/10.5194/isprs-archives-XLVIII-4-W2-2022-31-2023, https://doi.org/10.5194/isprs-archives-XLVIII-4-W2-2022-31-2023, 2023
M. Garramone and M. Scaioni
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B4-2022, 39–45, https://doi.org/10.5194/isprs-archives-XLIII-B4-2022-39-2022, https://doi.org/10.5194/isprs-archives-XLIII-B4-2022-39-2022, 2022
V. Belloni, D. Fugazza, and M. Di Rita
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B1-2022, 367–373, https://doi.org/10.5194/isprs-archives-XLIII-B1-2022-367-2022, https://doi.org/10.5194/isprs-archives-XLIII-B1-2022-367-2022, 2022
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Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-5-W1-2022, 95–102, https://doi.org/10.5194/isprs-archives-XLVI-5-W1-2022-95-2022, https://doi.org/10.5194/isprs-archives-XLVI-5-W1-2022-95-2022, 2022
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Proc. Int. Cartogr. Assoc., 4, 12, https://doi.org/10.5194/ica-proc-4-12-2021, https://doi.org/10.5194/ica-proc-4-12-2021, 2021
Y. Cao and M. Scaioni
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2021, 449–456, https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-449-2021, https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-449-2021, 2021
M. Previtali, M. Garramone, and M. Scaioni
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2021, 229–235, https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-229-2021, https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-229-2021, 2021
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Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIV-3-W1-2020, 131–138, https://doi.org/10.5194/isprs-archives-XLIV-3-W1-2020-131-2020, https://doi.org/10.5194/isprs-archives-XLIV-3-W1-2020-131-2020, 2020
M. Garramone, N. Moretti, M. Scaioni, C. Ellul, F. Re Cecconi, and M. C. Dejaco
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., VI-4-W1-2020, 77–84, https://doi.org/10.5194/isprs-annals-VI-4-W1-2020-77-2020, https://doi.org/10.5194/isprs-annals-VI-4-W1-2020-77-2020, 2020
M. Rutzinger, K. Anders, M. Bremer, B. Höfle, R. Lindenbergh, S. Oude Elberink, F. Pirotti, M. Scaioni, and T. Zieher
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B5-2020, 243–250, https://doi.org/10.5194/isprs-archives-XLIII-B5-2020-243-2020, https://doi.org/10.5194/isprs-archives-XLIII-B5-2020-243-2020, 2020
M. Previtali, L. Barazzetti, and M. Scaioni
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2020, 533–539, https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-533-2020, https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-533-2020, 2020
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Earth Syst. Sci. Data, 12, 1805–1821, https://doi.org/10.5194/essd-12-1805-2020, https://doi.org/10.5194/essd-12-1805-2020, 2020
Short summary
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We have used Sentinel-2 satellite data from 2015 and 2016 to create a new glacier inventory for the European Alps. Outlines from earlier national inventories were used to guide manual corrections (e.g. ice in shadow or under debris cover) of the automatically mapped clean ice. We mapped 4395 glaciers, covering 1806 km2, an area loss of about 14 % (or −1.2 % per year) compared to the last inventory of 2003. We conclude that glacier shrinkage in the Alps has continued unabated since the mid-1980s.
Y. Cao, M. Previtali, and M. Scaioni
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2020, 651–657, https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-651-2020, https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-651-2020, 2020
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
Davide Fugazza, Marco Scaioni, Manuel Corti, Carlo D'Agata, Roberto Sergio Azzoni, Massimo Cernuschi, Claudio Smiraglia, and Guglielmina Adele Diolaiuti
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
M. Parrot, V. Tramutoli, Tiger J. Y. Liu, S. Pulinets, D. Ouzounov, N. Genzano, M. Lisi, K. Hattori, and A. Namgaladze
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2016-172, https://doi.org/10.5194/nhess-2016-172, 2016
Revised manuscript not accepted
Short summary
Short summary
Since tens of years perturbations have been observed in the ionosphere prior to earthquakes (between a few hours and a few days before). But the mechanism to understand how the earthquake preparation in a seismic area can induce a change in the ionosphere is the subject of intense debate. In this paper we present various atmospheric and ionospheric perturbations observed prior to large earthquakes in order to support a model of coupling between the lithosphere, the atmosphere, and the ionosphere.
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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