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The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Articles | Volume XLVIII-M-1-2023
https://doi.org/10.5194/isprs-archives-XLVIII-M-1-2023-293-2023
© 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-M-1-2023-293-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
21 Apr 2023
| 21 Apr 2023
TECHNIQUES FOR COMPARING MULTI-TEMPORAL ARCHIVE AERIAL IMAGERY FOR GLACIER MONITORING WITH POOR GROUND CONTROL
M. Scaioni
Politecnico di Milano, Dept. of Architecture, Built Environment and Construction Engineering (DABC) via Ponzio 31, 20133 Milano, Italy
A. Malekian
Politecnico di Milano, Lecco Campus, via G. Previati 1/c, 23900 Lecco, Italy
D. Fugazza
Università degli Studi di Milano, Department of Environmental Science and Policy (DESP), Via Celoria 2, 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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Y. Cao and M. Scaioni
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Short summary
Short summary
Glacier albedo determines how much solar radiation is absorbed by the glacier surface and is a key driver of glacier melt. Alpine glaciers are losing their snow and firn cover, and the underlying darker ice is becoming exposed. This means that more solar radiation is absorbed by the ice, which leads to increased melt. To quantify these processes, we explore data from a high-elevation, on-ice weather station that measures albedo and combine this information with satellite imagery.
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Short summary
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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.
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
Rasoul Eskandari and Marco Scaioni
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., X-3-2024, 131–138, https://doi.org/10.5194/isprs-annals-X-3-2024-131-2024, https://doi.org/10.5194/isprs-annals-X-3-2024-131-2024, 2024
Jianzhuo Xu, Manuel Garramone, and Marco Scaioni
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4-W11-2024, 161–166, https://doi.org/10.5194/isprs-archives-XLVIII-4-W11-2024-161-2024, https://doi.org/10.5194/isprs-archives-XLVIII-4-W11-2024-161-2024, 2024
Nicola Genzano, Davide Fugazza, Rasoul Eskandari, and Marco Scaioni
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-2-2024, 99–106, https://doi.org/10.5194/isprs-archives-XLVIII-2-2024-99-2024, https://doi.org/10.5194/isprs-archives-XLVIII-2-2024-99-2024, 2024
Y. Cao and M. Scaioni
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-W2-2023, 147–153, https://doi.org/10.5194/isprs-archives-XLVIII-1-W2-2023-147-2023, https://doi.org/10.5194/isprs-archives-XLVIII-1-W2-2023-147-2023, 2023
R. Eskandari and M. Scaioni
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-W2-2023, 1235–1241, https://doi.org/10.5194/isprs-archives-XLVIII-1-W2-2023-1235-2023, https://doi.org/10.5194/isprs-archives-XLVIII-1-W2-2023-1235-2023, 2023
Y. Cao and M. Scaioni
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-W3-2023, 31–37, https://doi.org/10.5194/isprs-archives-XLVIII-1-W3-2023-31-2023, https://doi.org/10.5194/isprs-archives-XLVIII-1-W3-2023-31-2023, 2023
J. Xu, M. Garramone, Y. Wang, and M. Scaioni
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-M-2-2023, 1645–1652, https://doi.org/10.5194/isprs-archives-XLVIII-M-2-2023-1645-2023, https://doi.org/10.5194/isprs-archives-XLVIII-M-2-2023-1645-2023, 2023
M. Garramone, D. Jovanovic, D. Oreni, L. Barazzetti, M. Previtali, F. Roncoroni, A. Mandelli, and M. Scaioni
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-M-2-2023, 653–660, https://doi.org/10.5194/isprs-archives-XLVIII-M-2-2023-653-2023, https://doi.org/10.5194/isprs-archives-XLVIII-M-2-2023-653-2023, 2023
R. Eskandari and M. Scaioni
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., X-M-1-2023, 79–86, https://doi.org/10.5194/isprs-annals-X-M-1-2023-79-2023, https://doi.org/10.5194/isprs-annals-X-M-1-2023-79-2023, 2023
M. Garramone and M. Scaioni
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-5-W2-2023, 37–42, https://doi.org/10.5194/isprs-archives-XLVIII-5-W2-2023-37-2023, https://doi.org/10.5194/isprs-archives-XLVIII-5-W2-2023-37-2023, 2023
J. Xu and M. Scaioni
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-5-W2-2023, 117–124, https://doi.org/10.5194/isprs-archives-XLVIII-5-W2-2023-117-2023, https://doi.org/10.5194/isprs-archives-XLVIII-5-W2-2023-117-2023, 2023
M. Previtali, L. Barazzetti, F. Roncoroni, Y. Cao, and M. Scaioni
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
Giacomo Traversa, Davide Fugazza, and Massimo Frezzotti
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
Short summary
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.
A. Malekian, D. Fugazza, and M. Scaioni
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., X-4-W1-2022, 459–466, https://doi.org/10.5194/isprs-annals-X-4-W1-2022-459-2023, https://doi.org/10.5194/isprs-annals-X-4-W1-2022-459-2023, 2023
R. Eskandari and M. Scaioni
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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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M. Garramone, E. Tonelli, and M. Scaioni
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Piera Belotti, Fabio Conzi, Chiara Dell’Orto, Maurizio Federici, Luigi Fregonese, Gabriele Garnero, Emilio Guastamacchia, Franco Guzzetti, Livio Pinto, and Marco Scaioni
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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
M. Scaioni, L. Longoni, L. Zanzi, V. Ivanov, and M. Papini
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
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