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The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Articles | Volume XLII-2/W6
https://doi.org/10.5194/isprs-archives-XLII-2-W6-281-2017
© Author(s) 2017. 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-W6-281-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
24 Aug 2017
| 24 Aug 2017
3D MODELING OF INDUSTRIAL HERITAGE BUILDING USING COTSs SYSTEM: TEST, LIMITS AND PERFORMANCES
Department of Environmental, Land and Infrastructure Engineering (DIATI), Polytechnic of Torino corso Duca degli Abruzzi 24, 10129 Torino, Italy
V. Di Pietra
Department of Environmental, Land and Infrastructure Engineering (DIATI), Polytechnic of Torino corso Duca degli Abruzzi 24, 10129 Torino, Italy
D. Visintini
Polytechnic Department of Engineering and Architecture (DPIA), University of Udine via delle Scienze 206, 33100 Udine, Italy
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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.
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V. Di Pietra, N. Grasso, M. Piras, and P. Dabove
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B1-2020, 227–234, https://doi.org/10.5194/isprs-archives-XLIII-B1-2020-227-2020, https://doi.org/10.5194/isprs-archives-XLIII-B1-2020-227-2020, 2020
D. De Luca, M. Del Giudice, N. Grasso, F. Matrone, A. Osello, and M. Piras
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W15, 381–388, https://doi.org/10.5194/isprs-archives-XLII-2-W15-381-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W15-381-2019, 2019
G. P. C. Bronzino, N. Grasso, F. Matrone, A. Osello, and M. Piras
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W15, 215–222, https://doi.org/10.5194/isprs-archives-XLII-2-W15-215-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W15-215-2019, 2019
E. Belcore, M. Piras, A. Pezzoli, G. Massazza, and M. Rosso
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 207–214, https://doi.org/10.5194/isprs-archives-XLII-2-W13-207-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W13-207-2019, 2019
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I. Selvaggi, M. Dellapasqua, F. Franci, A. Spangher, D. Visintini, and G. Bitelli
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2, 1061–1066, https://doi.org/10.5194/isprs-archives-XLII-2-1061-2018, https://doi.org/10.5194/isprs-archives-XLII-2-1061-2018, 2018
N. Grasso, E. Verbree, S. Zlatanova, and M. Piras
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M. Piras, N. Grasso, and A. Abdul Jabbar
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A. Abdul Jabbar, I. Aicardi, N. Grasso, and M. Piras
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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.
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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