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The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Articles | Volume XLIII-B1-2020
https://doi.org/10.5194/isprs-archives-XLIII-B1-2020-227-2020
© Author(s) 2020. 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-XLIII-B1-2020-227-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
06 Aug 2020
| 06 Aug 2020
CHARACTERIZATION OF A MOBILE MAPPING SYSTEM FOR SEAMLESS NAVIGATION
V. Di Pietra
Department of Environment Land and Infrastructure Engineering (DIATI) - Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy
PIC4SeR, Politecnico di Torino Interdepartmental Centre for Service Robotics, Torino, Italy
N. Grasso
Department of Environment Land and Infrastructure Engineering (DIATI) - Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy
Department of Environment Land and Infrastructure Engineering (DIATI) - Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy
PIC4SeR, Politecnico di Torino Interdepartmental Centre for Service Robotics, Torino, Italy
P. Dabove
Department of Environment Land and Infrastructure Engineering (DIATI) - Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy
PIC4SeR, Politecnico di Torino Interdepartmental Centre for Service Robotics, Torino, Italy
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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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