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The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Articles | Volume XLVIII-M-1-2023
https://doi.org/10.5194/isprs-archives-XLVIII-M-1-2023-137-2023
© 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-M-1-2023-137-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
21 Apr 2023
| 21 Apr 2023
A REPLICABLE OPEN-SOURCE MULTI-CAMERA SYSTEM FOR LOW-COST 4D GLACIER MONITORING
Politecnico di Milano, Department of Civil and Environmental Engineering, Milan, Italy
E. Bruno
Politecnico di Torino, Department of Mechanical and Aerospace Engineering, Torino, Italy
D. Calzolari
CERN, Geneva, Switzerland
M. Galbiati
Politecnico di Milano, Department of Energy, Milan, Italy
A. Mannocchi
Politecnico di Milano, Department of Aerospace Science and Technology, Milan, Italy
P. Manzoni
Politecnico di Milano, Department of Mathematics, Milan, Italy
M. Martini
Politecnico di Torino, Department of Electronics and Telecommunications, Torino, Italy
A. Bianchi
Politecnico di Milano, Department of Civil and Environmental Engineering, Milan, Italy
A. Cina
Politecnico di Torino, Department of Environment, Land and Infrastructure Engineering, Torino, Italy
C. De Michele
Politecnico di Milano, Department of Civil and Environmental Engineering, Milan, Italy
L. Pinto
Politecnico di Milano, Department of Civil and Environmental Engineering, Milan, Italy
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Climate hazards may be caused by events which have multiple drivers. Here we present a method to break down climate model biases in hazard indicators down to the bias caused by each driving variable. Using simplified fire and heat stress indicators driven by temperature and relative humidity as examples, we show how multivariate indicators may have complex biases and that the relationship between driving variables is a source of bias that must be considered in climate model bias corrections.
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Short summary
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Fabiola Banfi and Carlo De Michele
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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
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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
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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
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Hydrol. Earth Syst. Sci., 18, 4579–4600, https://doi.org/10.5194/hess-18-4579-2014, https://doi.org/10.5194/hess-18-4579-2014, 2014
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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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