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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-W6-289-2017
© 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-W6-289-2017
© 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
UAV PHOTOGRAMMETRIC SOLUTION USING A RASPBERRY PI CAMERA MODULE AND SMART DEVICES: TEST AND RESULTS
Politecnico di Torino, Dip. di Ingegneria dell'Ambiente, del Territorio e delle Infrastrutture, Corso Duca degli Abruzzi 24, 10129 Torino, Italy
N. Grasso
Politecnico di Torino, Dip. di Ingegneria dell'Ambiente, del Territorio e delle Infrastrutture, Corso Duca degli Abruzzi 24, 10129 Torino, Italy
A. Abdul Jabbar
Politecnico di Torino, Dip. di Ingegneria dell'Ambiente, del Territorio e delle Infrastrutture, Corso Duca degli Abruzzi 24, 10129 Torino, 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
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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.
I. Aicardi, F. Chiabrando, N. Grasso, A. M. Lingua, F. Noardo, and A. Spanò
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B1, 835–842, https://doi.org/10.5194/isprs-archives-XLI-B1-835-2016, https://doi.org/10.5194/isprs-archives-XLI-B1-835-2016, 2016
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