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The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Articles | Volume XLII-2/W8
https://doi.org/10.5194/isprs-archives-XLII-2-W8-75-2017
© 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-W8-75-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
13 Nov 2017
| 13 Nov 2017
A TOOL FOR CROWDSOURCED BUILDING INFORMATION MODELING THROUGH LOW-COST RANGE CAMERA: PRELIMINARY DEMONSTRATION AND POTENTIAL
F. Capocchiano
Geodesy and Geomatics Division, DICEA - University of Rome “La Sapienza”, Rome, Italy
Sapienza School for Advanced Studies, Rome, Italy
R. Ravanelli
Geodesy and Geomatics Division, DICEA - University of Rome “La Sapienza”, Rome, Italy
M. Crespi
Geodesy and Geomatics Division, DICEA - University of Rome “La Sapienza”, Rome, Italy
Sapienza School for Advanced Studies, Rome, Italy
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Short summary
Short summary
The estimation of precipitable water vapour (W) content is of great interest in both meteorological and climatological studies. Sun photometers allowed the development of W automatic estimations with high temporal resolution. A new methodology, based on the hypothesis that the calibration parameters characterizing the atmospheric transmittance are dependent on vertical profiles of temperature, air pressure and moisture typical of each measurement site, has been presented providing good results.
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R. Ravanelli, A. Nascetti, M. Di Rita, V. Belloni, D. Mattei, N. Nisticó, and M. Crespi
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4-W2, 139–145, https://doi.org/10.5194/isprs-archives-XLII-4-W2-139-2017, https://doi.org/10.5194/isprs-archives-XLII-4-W2-139-2017, 2017
A. Nascetti, M. Di Rita, R. Ravanelli, M. Amicuzi, S. Esposito, and M. Crespi
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-1-W1, 627–633, https://doi.org/10.5194/isprs-archives-XLII-1-W1-627-2017, https://doi.org/10.5194/isprs-archives-XLII-1-W1-627-2017, 2017
M. Di Rita, A. Nascetti, and M. Crespi
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-1-W1, 635–638, https://doi.org/10.5194/isprs-archives-XLII-1-W1-635-2017, https://doi.org/10.5194/isprs-archives-XLII-1-W1-635-2017, 2017
R. Ravanelli, A. Nascetti, M. Di Rita, L. Nigro, D. Montanari, F. Spagnoli, and M. Crespi
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-5-W1, 589–592, https://doi.org/10.5194/isprs-archives-XLII-5-W1-589-2017, https://doi.org/10.5194/isprs-archives-XLII-5-W1-589-2017, 2017
A. Nascetti, F. Nocchi, A. Camplani, C. Di Rico, and M. Crespi
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B7, 783–788, https://doi.org/10.5194/isprs-archives-XLI-B7-783-2016, https://doi.org/10.5194/isprs-archives-XLI-B7-783-2016, 2016
F. Fratarcangeli, A. Nascetti, P. Capaldo, A. Mazzoni, and M. Crespi
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B7, 815–820, https://doi.org/10.5194/isprs-archives-XLI-B7-815-2016, https://doi.org/10.5194/isprs-archives-XLI-B7-815-2016, 2016
M. Di Rita, A. Nascetti, F. Fratarcangeli, and M. Crespi
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B7, 821–825, https://doi.org/10.5194/isprs-archives-XLI-B7-821-2016, https://doi.org/10.5194/isprs-archives-XLI-B7-821-2016, 2016
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