03 Dec 2021
| 03 Dec 2021
The Project to Complete the Regional Topographic Geodatabase in Lombardy, Italy
Piera Belotti
Direzione Generale Territorio e Protezione Civile, Regione Lombardia, Milano, Italy
Fabio Conzi
Direzione Generale Territorio e Protezione Civile, Regione Lombardia, Milano, Italy
Chiara Dell’Orto
free lancer
Maurizio Federici
Direzione Generale Territorio e Protezione Civile, Regione Lombardia, Milano, Italy
Luigi Fregonese
Dipartimento di Architettura, dell’Ambiente Costruito e dell’Ingegneria delle Costruzioni (DABC), Politecnico di Milano, Italy
Gabriele Garnero
Dipartimento Interateneo di Scienze, Progetto e Politiche del Territorio, Università degli Studi di Torino, Italy
Emilio Guastamacchia
Dipartimento di Architettura e di Studi Urbani (DAStU), Politecnico di Milano, Italy
Franco Guzzetti
Dipartimento di Architettura, dell’Ambiente Costruito e dell’Ingegneria delle Costruzioni (DABC), Politecnico di Milano, Italy
Livio Pinto
Dipartimento di Ingegneria Civile e Ambientale (DICA), Politecnico di Milano, Italy
Marco Scaioni
Dipartimento di Architettura, dell’Ambiente Costruito e dell’Ingegneria delle Costruzioni (DABC), Politecnico di Milano, Italy
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Menglian Xia, Rongxing Li, Marco Scaioni, Lu An, Zhenshi Li, and Gang Qiao
EGUsphere, https://doi.org/10.5194/egusphere-2025-175, https://doi.org/10.5194/egusphere-2025-175, 2025
This preprint is open for discussion and under review for The Cryosphere (TC).
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.
Ahmad Elalailyi, Paweł Trybała, Luca Morelli, Francesco Fassi, Fabio Remondino, and Luigi Fregonese
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-2-W8-2024, 147–154, https://doi.org/10.5194/isprs-archives-XLVIII-2-W8-2024-147-2024, https://doi.org/10.5194/isprs-archives-XLVIII-2-W8-2024-147-2024, 2024
Daniele Treccani, Andrea Adami, and Luigi Fregonese
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-2-W8-2024, 431–438, https://doi.org/10.5194/isprs-archives-XLVIII-2-W8-2024-431-2024, https://doi.org/10.5194/isprs-archives-XLVIII-2-W8-2024-431-2024, 2024
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
Federica Gaspari, Francesco Ioli, Federico Barbieri, Samuele Bonora, Rebecca Fascia, Livio Pinto, and Federica Migliaccio
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4-W12-2024, 59–66, https://doi.org/10.5194/isprs-archives-XLVIII-4-W12-2024-59-2024, https://doi.org/10.5194/isprs-archives-XLVIII-4-W12-2024-59-2024, 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
R. Fascia, F. Barbieri, F. Gaspari, F. Ioli, and L. Pinto
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-2-W4-2024, 205–212, https://doi.org/10.5194/isprs-archives-XLVIII-2-W4-2024-205-2024, https://doi.org/10.5194/isprs-archives-XLVIII-2-W4-2024-205-2024, 2024
B. Fazion, D. Treccani, L. Fregonese, and N. Lombardini
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-2-W4-2024, 213–219, https://doi.org/10.5194/isprs-archives-XLVIII-2-W4-2024-213-2024, https://doi.org/10.5194/isprs-archives-XLVIII-2-W4-2024-213-2024, 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
F. Gaspari, F. Barbieri, J. P. Duque, R. Fascia, F. Ioli, G. Zani, D. Carrion, and L. Pinto
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-W2-2023, 299–306, https://doi.org/10.5194/isprs-archives-XLVIII-1-W2-2023-299-2023, https://doi.org/10.5194/isprs-archives-XLVIII-1-W2-2023-299-2023, 2023
F. Ioli, F. Barbieri, F. Gaspari, F. Nex, and L. Pinto
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-W2-2023, 1037–1044, https://doi.org/10.5194/isprs-archives-XLVIII-1-W2-2023-1037-2023, https://doi.org/10.5194/isprs-archives-XLVIII-1-W2-2023-1037-2023, 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
A. Adami, D. Treccani, and L. Fregonese
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-M-2-2023, 19–25, https://doi.org/10.5194/isprs-archives-XLVIII-M-2-2023-19-2023, https://doi.org/10.5194/isprs-archives-XLVIII-M-2-2023-19-2023, 2023
F. Biolo, F. Guzzetti, and K. L. N. Anyabolu
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-M-2-2023, 219–226, https://doi.org/10.5194/isprs-archives-XLVIII-M-2-2023-219-2023, https://doi.org/10.5194/isprs-archives-XLVIII-M-2-2023-219-2023, 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
F. Gaspari, F. Ioli, F. Barbieri, C. Rivieri, M. Dondi, and L. Pinto
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-M-2-2023, 661–668, https://doi.org/10.5194/isprs-archives-XLVIII-M-2-2023-661-2023, https://doi.org/10.5194/isprs-archives-XLVIII-M-2-2023-661-2023, 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
F. Guzzetti, K. L. N. Anyabolu, F. Biolo, and L. D’Ambrosio
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., X-M-1-2023, 101–108, https://doi.org/10.5194/isprs-annals-X-M-1-2023-101-2023, https://doi.org/10.5194/isprs-annals-X-M-1-2023-101-2023, 2023
F. Gaspari, F. Barbieri, I. Demnati, F. Ioli, L. Pinto, and V. Toscani
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4-W7-2023, 61–66, https://doi.org/10.5194/isprs-archives-XLVIII-4-W7-2023-61-2023, https://doi.org/10.5194/isprs-archives-XLVIII-4-W7-2023-61-2023, 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
F. Ioli, E. Bruno, D. Calzolari, M. Galbiati, A. Mannocchi, P. Manzoni, M. Martini, A. Bianchi, A. Cina, C. De Michele, and L. Pinto
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-M-1-2023, 137–144, https://doi.org/10.5194/isprs-archives-XLVIII-M-1-2023-137-2023, https://doi.org/10.5194/isprs-archives-XLVIII-M-1-2023-137-2023, 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
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
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
A. Adami, L. Fregonese, J. Helder, O. Rosignoli, L. Taffurelli, and D. Treccani
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2022, 745–752, https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-745-2022, https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-745-2022, 2022
F. Gaspari, F. Ioli, F. Barbieri, E. Belcore, and L. Pinto
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2022, 995–1002, https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-995-2022, https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-995-2022, 2022
F. Ioli, A. Pinto, and L. Pinto
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2022, 1025–1032, https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-1025-2022, https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-1025-2022, 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
L. Fregonese, M. Gallo, M. Pulcrano, S. Scandurra, and F. Del Vecchio
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-2-W1-2022, 223–229, https://doi.org/10.5194/isprs-archives-XLVI-2-W1-2022-223-2022, https://doi.org/10.5194/isprs-archives-XLVI-2-W1-2022-223-2022, 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
F. Guzzetti, K. L. N. Anyabolu, F. Biolo, and R. Dell’Orto
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-5-W1-2022, 115–122, https://doi.org/10.5194/isprs-archives-XLVI-5-W1-2022-115-2022, https://doi.org/10.5194/isprs-archives-XLVI-5-W1-2022-115-2022, 2022
F. Ioli, L. Pinto, and F. Ferrario
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2021, 25–32, https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-25-2021, https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-25-2021, 2021
L. Rossi, F. Ioli, E. Capizzi, L. Pinto, and M. Reguzzoni
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2021, 61–68, https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-61-2021, https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-61-2021, 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
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
A. Adami and L. Fregonese
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B5-2020, 9–14, https://doi.org/10.5194/isprs-archives-XLIII-B5-2020-9-2020, https://doi.org/10.5194/isprs-archives-XLIII-B5-2020-9-2020, 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
L. Pinto, F. Bianchini, V. Nova, and D. Passoni
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2020, 1145–1150, https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-1145-2020, https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-1145-2020, 2020
F. Ioli, L. Pinto, D. Passoni, V. Nova, and M. Detert
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2020, 597–604, https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-597-2020, https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-597-2020, 2020
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. Adami, L. Fregonese, M. Gallo, J. Helder, M. Pepe, and D. Treccani
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W17, 15–21, https://doi.org/10.5194/isprs-archives-XLII-2-W17-15-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W17-15-2019, 2019
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
L. Fregonese, N. Giordani, A. Adami, G. Bachinsky, L. Taffurelli, O. Rosignoli, and J. Helder
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W15, 481–487, https://doi.org/10.5194/isprs-archives-XLII-2-W15-481-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W15-481-2019, 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
F. Guzzetti, K. L. N. Anyabolu, L. D’Ambrosio, and G. Marchetti
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W11, 595–600, https://doi.org/10.5194/isprs-archives-XLII-2-W11-595-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W11-595-2019, 2019
C. Cappelletti, M. Boniardi, A. Casaroli, C. I. De Gaetani, D. Passoni, and L. Pinto
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W9, 227–234, https://doi.org/10.5194/isprs-archives-XLII-2-W9-227-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W9-227-2019, 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
D. Pagliari and L. Pinto
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2, 813–820, https://doi.org/10.5194/isprs-archives-XLII-2-813-2018, https://doi.org/10.5194/isprs-archives-XLII-2-813-2018, 2018
L. Rossi, C. I. De Gaetani, D. Pagliari, E. Realini, M. Reguzzoni, and L. Pinto
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2, 991–998, https://doi.org/10.5194/isprs-archives-XLII-2-991-2018, https://doi.org/10.5194/isprs-archives-XLII-2-991-2018, 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
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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
S. Gagliolo, R. Fagandini, B. Federici, I. Ferrando, D. Passoni, D. Pagliari, L. Pinto, and D. Sguerso
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-5-W1, 81–88, https://doi.org/10.5194/isprs-archives-XLII-5-W1-81-2017, https://doi.org/10.5194/isprs-archives-XLII-5-W1-81-2017, 2017
Francesco Avanzi, Alberto Bianchi, Alberto Cina, Carlo De Michele, Paolo Maschio, Diana Pagliari, Daniele Passoni, Livio Pinto, Marco Piras, and Lorenzo Rossi
The Cryosphere Discuss., https://doi.org/10.5194/tc-2017-57, https://doi.org/10.5194/tc-2017-57, 2017
Revised manuscript not accepted
Short summary
Short summary
We compare three different instruments used to collect snow depth, i.e., photogrammetric surveys using Unmanned Aerial Systems (UAS), a 3D laser scanning, and manual probing. The relatively high density of manual data (135 pt over 6700 m2, i.e., 2 pt/100 m2) enables to assess the performance of UAS in capturing the marked spatial variability of snow. Results suggest that UAS represent a competitive choice among existing techniques for high-precision, high-resolution remote sensing of snow.
A. Pasquinelli and F. Guzzetti
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-4-W1, 11–18, https://doi.org/10.5194/isprs-annals-IV-4-W1-11-2016, https://doi.org/10.5194/isprs-annals-IV-4-W1-11-2016, 2016
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
Carlo De Michele, Francesco Avanzi, Daniele Passoni, Riccardo Barzaghi, Livio Pinto, Paolo Dosso, Antonio Ghezzi, Roberto Gianatti, and Giacomo Della Vedova
The Cryosphere, 10, 511–522, https://doi.org/10.5194/tc-10-511-2016, https://doi.org/10.5194/tc-10-511-2016, 2016
Short summary
Short summary
We investigate snow depth distribution at peak accumulation over a small Alpine area using photogrammetry-based surveys with a fixed wing unmanned aerial system. Results reveal that UAS estimations of point snow depth present an average difference with reference to manual measurements equal to -0.073 m. Moreover, in this case study snow depth standard deviation (hence coefficient of variation) increases with decreasing cell size, but it stabilizes for resolutions smaller than 1 m.
