- Article
(2338 KB) - Metadata XML
- April 08, 2024
- |
- Home
- |
- Sitemap
- |
- The ISPRS Foundation
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Articles | Volume XLII-2/W13
https://doi.org/10.5194/isprs-archives-XLII-2-W13-1803-2019
© Author(s) 2019. 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-XLII-2-W13-1803-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
05 Jun 2019
| 05 Jun 2019
MONITORING ALPINE GLACIERS FROM CLOSE-RANGE TO SATELLITE SENSORS
V. Yordanov
Dept. of Civil and Environment Engineering (DICA), Politecnico di Milano, piazza L. da Vinci 32, 20133 Milano, Italy
D. Fugazza
Dept. of Environmental Science and Policy (DESP), Università degli studi di Milano, via Mangiagalli 34, 20133 Milano, Italy
R. S. Azzoni
Dept. of Environmental Science and Policy (DESP), Università degli studi di Milano, via Mangiagalli 34, 20133 Milano, Italy
M. Cernuschi
Agricola 2000 S.C.P.A., 20067 Tribiano (MI), Italy
M. Scaioni
Dept. of Architecture, Built Environment and Construction Engineering (DABC), Politecnico di Milano, via Ponzio 31, 20133 Milano, Italy
G. A. Diolaiuti
Dept. of Environmental Science and Policy (DESP), Università degli studi di Milano, via Mangiagalli 34, 20133 Milano, Italy
Related authors
V. Yordanov, X. Q. Truong, M. Corti, L. Longoni, and M. A. Brovelli
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-W2-2023, 1089–1096, https://doi.org/10.5194/isprs-archives-XLVIII-1-W2-2023-1089-2023, https://doi.org/10.5194/isprs-archives-XLVIII-1-W2-2023-1089-2023, 2023
L. Amici, V. Yordanov, D. Oxoli, X. Q. Truong, and M. A. Brovelli
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4-W1-2022, 27–34, https://doi.org/10.5194/isprs-archives-XLVIII-4-W1-2022-27-2022, https://doi.org/10.5194/isprs-archives-XLVIII-4-W1-2022-27-2022, 2022
V. Yordanov, L. Biagi, X. Q. Truong, and M. A. Brovelli
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2022, 493–499, https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-493-2022, https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-493-2022, 2022
V. A. Tran, X. Q. Truong, D. A. Nguyen, L. Longoni, and V. Yordanov
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-4-W2-2021, 197–203, https://doi.org/10.5194/isprs-archives-XLVI-4-W2-2021-197-2021, https://doi.org/10.5194/isprs-archives-XLVI-4-W2-2021-197-2021, 2021
V. Yordanov, L. Biagi, X. Q. Truong, V. A. Tran, and M. A. Brovelli
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-4-W2-2021, 205–212, https://doi.org/10.5194/isprs-archives-XLVI-4-W2-2021-205-2021, https://doi.org/10.5194/isprs-archives-XLVI-4-W2-2021-205-2021, 2021
V. Yordanov and M. A. Brovelli
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2021, 865–872, https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-865-2021, https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-865-2021, 2021
V. Yordanov, M. A. Brovelli, D. Carrion, L. Barazzetti, L. J. A. Francisco, H. R. Comia, and M. I. Caravela
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIV-3-W1-2020, 151–158, https://doi.org/10.5194/isprs-archives-XLIV-3-W1-2020-151-2020, https://doi.org/10.5194/isprs-archives-XLIV-3-W1-2020-151-2020, 2020
V. Yordanov and M. A. Brovelli
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2020, 1277–1284, https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-1277-2020, https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-1277-2020, 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, 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
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
V. Yordanov, X. Q. Truong, M. Corti, L. Longoni, and M. A. Brovelli
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-W2-2023, 1089–1096, https://doi.org/10.5194/isprs-archives-XLVIII-1-W2-2023-1089-2023, https://doi.org/10.5194/isprs-archives-XLVIII-1-W2-2023-1089-2023, 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
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
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
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
L. Amici, V. Yordanov, D. Oxoli, X. Q. Truong, and M. A. Brovelli
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4-W1-2022, 27–34, https://doi.org/10.5194/isprs-archives-XLVIII-4-W1-2022-27-2022, https://doi.org/10.5194/isprs-archives-XLVIII-4-W1-2022-27-2022, 2022
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
V. Yordanov, L. Biagi, X. Q. Truong, and M. A. Brovelli
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2022, 493–499, https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-493-2022, https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-493-2022, 2022
Y. Cao and M. Scaioni
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2022, 219–226, https://doi.org/10.5194/isprs-annals-V-2-2022-219-2022, https://doi.org/10.5194/isprs-annals-V-2-2022-219-2022, 2022
M. Garramone, E. Tonelli, and M. Scaioni
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
Piera Belotti, Fabio Conzi, Chiara Dell’Orto, Maurizio Federici, Luigi Fregonese, Gabriele Garnero, Emilio Guastamacchia, Franco Guzzetti, Livio Pinto, and Marco Scaioni
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
V. A. Tran, X. Q. Truong, D. A. Nguyen, L. Longoni, and V. Yordanov
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-4-W2-2021, 197–203, https://doi.org/10.5194/isprs-archives-XLVI-4-W2-2021-197-2021, https://doi.org/10.5194/isprs-archives-XLVI-4-W2-2021-197-2021, 2021
V. Yordanov, L. Biagi, X. Q. Truong, V. A. Tran, and M. A. Brovelli
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-4-W2-2021, 205–212, https://doi.org/10.5194/isprs-archives-XLVI-4-W2-2021-205-2021, https://doi.org/10.5194/isprs-archives-XLVI-4-W2-2021-205-2021, 2021
V. Yordanov and M. A. Brovelli
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2021, 865–872, https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-865-2021, https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-865-2021, 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
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
V. Yordanov, M. A. Brovelli, D. Carrion, L. Barazzetti, L. J. A. Francisco, H. R. Comia, and M. I. Caravela
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIV-3-W1-2020, 151–158, https://doi.org/10.5194/isprs-archives-XLIV-3-W1-2020-151-2020, https://doi.org/10.5194/isprs-archives-XLIV-3-W1-2020-151-2020, 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
V. Yordanov and M. A. Brovelli
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2020, 1277–1284, https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-1277-2020, https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-1277-2020, 2020
Frank Paul, Philipp Rastner, Roberto Sergio Azzoni, Guglielmina Diolaiuti, Davide Fugazza, Raymond Le Bris, Johanna Nemec, Antoine Rabatel, Mélanie Ramusovic, Gabriele Schwaizer, and Claudio Smiraglia
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
Short summary
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
Giovanni Baccolo, Edyta Łokas, Paweł Gaca, Dario Massabò, Roberto Ambrosini, Roberto S. Azzoni, Caroline Clason, Biagio Di Mauro, Andrea Franzetti, Massimiliano Nastasi, Michele Prata, Paolo Prati, Ezio Previtali, Barbara Delmonte, and Valter Maggi
The Cryosphere, 14, 657–672, https://doi.org/10.5194/tc-14-657-2020, https://doi.org/10.5194/tc-14-657-2020, 2020
Short summary
Short summary
Cryoconite is the sediment found on the surface of glaciers. The paper presents cryoconite as an environmental matrix able to accumulate natural and artificial radioactivity with unprecedented efficiency. Only samples from sites where nuclear accidents and explosions occurred present a stronger radioactive contamination. The peculiarities of glacial environments are responsible for this extreme feature, making cryoconite a useful tool tool for the monitoring of environmental radioactivity.
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, 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
Antonella Senese, Maurizio Maugeri, Eraldo Meraldi, Gian Pietro Verza, Roberto Sergio Azzoni, Chiara Compostella, and Guglielmina Diolaiuti
The Cryosphere, 12, 1293–1306, https://doi.org/10.5194/tc-12-1293-2018, https://doi.org/10.5194/tc-12-1293-2018, 2018
Short summary
Short summary
We present and compare 11 years of snow data measured by an automatic weather station and corroborated by data from field campaigns on the Forni Glacier in Italy. The methodology we present is interesting for remote locations such as glaciers or high alpine regions, as it makes it possible to estimate the total snow water equivalent (SWE) using a relatively inexpensive, low-power, low-maintenance, and reliable instrument such as the sonic ranger.
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
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
Roberto Sergio Azzoni, Antonella Senese, Andrea Zerboni, Maurizio Maugeri, Claudio Smiraglia, and Guglielmina Adele Diolaiuti
The Cryosphere, 10, 665–679, https://doi.org/10.5194/tc-10-665-2016, https://doi.org/10.5194/tc-10-665-2016, 2016
Short summary
Short summary
In spite of quite abundant literature focusing on fine debris deposition over snow of glacier accumulation areas, less attention has been paid to the ice of the glacier melting surface. Accordingly, we developed a method for estimating ice albedo from fine debris cover quantified by a semi-automatic method. Our procedure was tested on the surface of the Forni Glacier (Italian Alps), acquiring parallel data sets of in situ measurements of ice albedo and high-resolution images.
C. L. Fyffe, B. W. Brock, M. P. Kirkbride, D. W. F. Mair, N. S. Arnold, C. Smiraglia, G. Diolaiuti, and F. Diotri
The Cryosphere Discuss., https://doi.org/10.5194/tcd-9-5373-2015, https://doi.org/10.5194/tcd-9-5373-2015, 2015
Revised manuscript not accepted
Short summary
Short summary
Dye-tracing of a debris-covered glacier revealed that its hydrological system was not similar to that of a debris-free glacier. Beneath the thick debris covering the lower glacier the drainage system was mainly inefficient, probably due lower sub-debris melt rates causing a lack of the large inputs required to open efficient channels. However, efficient channels opened by the large melt inputs from the debris-free areas did route water from the moulins above the thick debris.
A. Senese, M. Maugeri, E. Vuillermoz, C. Smiraglia, and G. Diolaiuti
The Cryosphere, 8, 1921–1933, https://doi.org/10.5194/tc-8-1921-2014, https://doi.org/10.5194/tc-8-1921-2014, 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