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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-W2-2023-1037-2023
© 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-W2-2023-1037-2023
© 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
ICEPY4D: A PYTHON TOOLKIT FOR ADVANCED MULTI-EPOCH GLACIER MONITORING WITH DEEP-LEARNING PHOTOGRAMMETRY
Politecnico di Milano, Dept. of Civil and Environmental Engineering, Milan, Italy
F. Barbieri
Politecnico di Milano, Dept. of Civil and Environmental Engineering, Milan, Italy
F. Gaspari
Politecnico di Milano, Dept. of Civil and Environmental Engineering, Milan, Italy
Dept. of Earth Observation Science (EOS), Faculty ITC, University of Twente, Enschede, The Netherlands
L. Pinto
Politecnico di Milano, Dept. of Civil and Environmental Engineering, Milan, Italy
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Short summary
Short summary
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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
D. Duarte, F. Nex, N. Kerle, and G. Vosselman
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2, 89–96, https://doi.org/10.5194/isprs-annals-IV-2-89-2018, https://doi.org/10.5194/isprs-annals-IV-2-89-2018, 2018
Y. Lin, F. Nex, and M. Y. Yang
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2, 209–216, https://doi.org/10.5194/isprs-annals-IV-2-209-2018, https://doi.org/10.5194/isprs-annals-IV-2-209-2018, 2018
Daniele Giordan, Yuichi Hayakawa, Francesco Nex, Fabio Remondino, and Paolo Tarolli
Nat. Hazards Earth Syst. Sci., 18, 1079–1096, https://doi.org/10.5194/nhess-18-1079-2018, https://doi.org/10.5194/nhess-18-1079-2018, 2018
Short summary
Short summary
Remotely piloted aerial systems can acquire on-demand ultra-high-resolution images that can be used for the identification of active processes like landslides or volcanic activities but also for the definition of effects of earthquakes, wildfires and floods. In this paper, we present a review of published literature that describes experimental methodologies developed for the study and monitoring of natural hazards.
C. Stöcker, F. Nex, M. Koeva, and M. Gerke
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W6, 355–361, https://doi.org/10.5194/isprs-archives-XLII-2-W6-355-2017, https://doi.org/10.5194/isprs-archives-XLII-2-W6-355-2017, 2017
P. Jende, F. Nex, M. Gerke, and G. Vosselman
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-1-W1, 317–323, https://doi.org/10.5194/isprs-archives-XLII-1-W1-317-2017, https://doi.org/10.5194/isprs-archives-XLII-1-W1-317-2017, 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.
M. Gerke, F. Nex, and P. Jende
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-3-W4, 11–18, https://doi.org/10.5194/isprs-archives-XL-3-W4-11-2016, https://doi.org/10.5194/isprs-archives-XL-3-W4-11-2016, 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.
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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