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ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Articles | Volume V-2-2022
https://doi.org/10.5194/isprs-annals-V-2-2022-7-2022
© Author(s) 2022. 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-annals-V-2-2022-7-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
17 May 2022
| 17 May 2022
PREFACE: TECHNICAL COMMISSION II
A. Yilmaz
Dept. of Civil, Environmental and Geodetic Engineering, The Ohio State University, Columbus, Ohio, USA
J. D. Wegner
EcoVision Lab, Photogrammetry and Remote Sensing, ETH Zurich, 8093 Zurich, Switzerland
Institute for Computational Science, University of Zurich, 8057 Zurich, Switzerland
R. Qin
Dept. of Civil, Environmental and Geodetic Engineering, The Ohio State University, Columbus, Ohio, USA
F. Remondino
3D Optical Metrology (3DOM) unit, Bruno Kessler Foundation (FBK), Trento, Italy
T. Fuse
Dept. of Civil Engineering, University of Tokyo, Hongo 7-3-1, Bunkyo-ku, Tokyo, 113-8656, Japan
I. Toschi
3D Optical Metrology (3DOM) unit, Bruno Kessler Foundation (FBK), Trento, Italy
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Short summary
Short summary
Oftentimes when objective measurements are not possible, human estimates are used instead. In our study, we investigate the reproducibility of human judgement for size estimates, the mappings of avalanches from oblique photographs and remotely sensed imagery. The variability that we found in those estimates is worth considering as it may influence results and should be kept in mind for several applications.
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Short summary
Short summary
Knowing where avalanches occur is very important information for several disciplines, for example avalanche warning, hazard zonation and risk management. Satellite imagery can provide such data systematically over large regions. In our work we propose a machine learning model to automate the time-consuming manual mapping. Additionally, we investigate expert agreement for manual avalanche mapping, showing that our network is equally as good as the experts in identifying avalanches.
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Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2022, 695–702, https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-695-2022, https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-695-2022, 2022
F. Menna, E. Nocerino, S. Malek, F. Remondino, and S. Schiaparelli
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2022, 935–943, https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-935-2022, https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-935-2022, 2022
E. M. Farella, L. Morelli, F. Remondino, J. P. Mills, N. Haala, and J. Crompvoets
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2022, 1175–1182, https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-1175-2022, https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-1175-2022, 2022
M. V. Peppa, L. Morelli, J. P. Mills, N. T. Penna, and F. Remondino
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2022, 1183–1190, https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-1183-2022, https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-1183-2022, 2022
D. Huang, M. Elhashash, and R. Qin
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2022, 17–22, https://doi.org/10.5194/isprs-annals-V-2-2022-17-2022, https://doi.org/10.5194/isprs-annals-V-2-2022-17-2022, 2022
S. Song and R. Qin
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2022, 23–30, https://doi.org/10.5194/isprs-annals-V-2-2022-23-2022, https://doi.org/10.5194/isprs-annals-V-2-2022-23-2022, 2022
H. Albanwan and R. Qin
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2022, 39–46, https://doi.org/10.5194/isprs-annals-V-2-2022-39-2022, https://doi.org/10.5194/isprs-annals-V-2-2022-39-2022, 2022
M. Elhashash and R. Qin
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2022, 47–52, https://doi.org/10.5194/isprs-annals-V-2-2022-47-2022, https://doi.org/10.5194/isprs-annals-V-2-2022-47-2022, 2022
F. Bellavia, L. Morelli, F. Menna, and F. Remondino
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-2-W1-2022, 73–80, https://doi.org/10.5194/isprs-archives-XLVI-2-W1-2022-73-2022, https://doi.org/10.5194/isprs-archives-XLVI-2-W1-2022-73-2022, 2022
E. M. Farella, L. Morelli, E. Grilli, S. Rigon, and F. Remondino
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-2-W1-2022, 215–222, https://doi.org/10.5194/isprs-archives-XLVI-2-W1-2022-215-2022, https://doi.org/10.5194/isprs-archives-XLVI-2-W1-2022-215-2022, 2022
S. Kyriakaki-Grammatikaki, E. K. Stathopoulou, E. Grilli, F. Remondino, and A. Georgopoulos
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-2-W1-2022, 291–298, https://doi.org/10.5194/isprs-archives-XLVI-2-W1-2022-291-2022, https://doi.org/10.5194/isprs-archives-XLVI-2-W1-2022-291-2022, 2022
G. Mazzacca, E. Grilli, G. P. Cirigliano, F. Remondino, and S. Campana
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-2-W1-2022, 365–372, https://doi.org/10.5194/isprs-archives-XLVI-2-W1-2022-365-2022, https://doi.org/10.5194/isprs-archives-XLVI-2-W1-2022-365-2022, 2022
A. Torresani, S. Rigon, E. M. Farella, F. Menna, and F. Remondino
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-M-1-2021, 761–768, https://doi.org/10.5194/isprs-archives-XLVI-M-1-2021-761-2021, https://doi.org/10.5194/isprs-archives-XLVI-M-1-2021-761-2021, 2021
S. Teruggi, E. Grilli, F. Fassi, and F. Remondino
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., VIII-M-1-2021, 155–162, https://doi.org/10.5194/isprs-annals-VIII-M-1-2021-155-2021, https://doi.org/10.5194/isprs-annals-VIII-M-1-2021-155-2021, 2021
A. Yilmaz, J. D. Wegner, F. Remondino, T. Fuse, and I. Toschi
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2021, 7–7, https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-7-2021, https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-7-2021, 2021
E. Maset, E. Rupnik, M. Pierrot-Deseilligny, F. Remondino, and A. Fusiello
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2021, 33–38, https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-33-2021, https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-33-2021, 2021
V. Mousavi, M. Varshosaz, and F. Remondino
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2021, 39–46, https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-39-2021, https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-39-2021, 2021
T. Fuse and T. Yamano
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2021, 163–169, https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-163-2021, https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-163-2021, 2021
H. Albanwan and R. Qin
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2021, 283–288, https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-283-2021, https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-283-2021, 2021
E. K. Stathopoulou, S. Rigon, R. Battisti, and F. Remondino
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2021, 391–398, https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-391-2021, https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-391-2021, 2021
E. Grilli, F. Poux, and F. Remondino
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2021, 471–478, https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-471-2021, https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-471-2021, 2021
A. Karami, F. Menna, and F. Remondino
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2021, 519–526, https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-519-2021, https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-519-2021, 2021
F. Remondino, F. Menna, and L. Morelli
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2021, 549–556, https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-549-2021, https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-549-2021, 2021
J. Wei, J. Jiang, and A. Yilmaz
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2021, 557–564, https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-557-2021, https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-557-2021, 2021
F. Menna, E. Nocerino, B. Chemisky, F. Remondino, and P. Drap
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2021, 667–672, https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-667-2021, https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-667-2021, 2021
A. Yilmaz, J. D. Wegner, F. Remondino, T. Fuse, and I. Toschi
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2021, 7–7, https://doi.org/10.5194/isprs-annals-V-2-2021-7-2021, https://doi.org/10.5194/isprs-annals-V-2-2021-7-2021, 2021
Nico Lang, Andrea Irniger, Agnieszka Rozniak, Roni Hunziker, Jan Dirk Wegner, and Konrad Schindler
Hydrol. Earth Syst. Sci., 25, 2567–2597, https://doi.org/10.5194/hess-25-2567-2021, https://doi.org/10.5194/hess-25-2567-2021, 2021
Short summary
Short summary
Grain size analysis is the key to understanding the sediment dynamics of river systems and is an important indicator for mitigating flood risk and preserving biodiversity in aquatic habitats. We propose GRAINet, a data-driven approach based on deep learning, to regress grain size distributions from georeferenced UAV images. This allows for a holistic analysis of entire gravel bars, resulting in robust grading curves and high-resolution maps of spatial grain size distribution at large scale.
D. González-Aguilera, E. Ruiz de Oña, L. López-Fernandez, E. M. Farella, E. K. Stathopoulou, I. Toschi, F. Remondino, P. Rodríguez-Gonzálvez, D. Hernández-López, A. Fusiello, and F. Nex
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B5-2020, 213–219, https://doi.org/10.5194/isprs-archives-XLIII-B5-2020-213-2020, https://doi.org/10.5194/isprs-archives-XLIII-B5-2020-213-2020, 2020
F. Matrone, A. Lingua, R. Pierdicca, E. S. Malinverni, M. Paolanti, E. Grilli, F. Remondino, A. Murtiyoso, and T. Landes
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2020, 1419–1426, https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-1419-2020, https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-1419-2020, 2020
F. Remondino, T. Fuse, and I. Toschi
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2020, 7–7, https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-7-2020, https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-7-2020, 2020
R. Qin, S. Song, and X. Huang
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2020, 157–162, https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-157-2020, https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-157-2020, 2020
V. V. Kniaz, S. Y. Zheltov, F. Remondino, V. A. Knyaz, A. Bordodymov, and A. Gruen
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2020, 435–441, https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-435-2020, https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-435-2020, 2020
O. Lanz, F. Sottsas, M. Conni, M. Boschetti, E. Nocerino, F. Menna, and F. Remondino
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2020, 785–790, https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-785-2020, https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-785-2020, 2020
F. Remondino, T. Fuse, and I. Toschi
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2020, 7–7, https://doi.org/10.5194/isprs-annals-V-2-2020-7-2020, https://doi.org/10.5194/isprs-annals-V-2-2020-7-2020, 2020
E. Maset, L. Magri, I. Toschi, and A. Fusiello
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2020, 49–55, https://doi.org/10.5194/isprs-annals-V-2-2020-49-2020, https://doi.org/10.5194/isprs-annals-V-2-2020-49-2020, 2020
S. Song and R. Qin
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2020, 403–409, https://doi.org/10.5194/isprs-annals-V-2-2020-403-2020, https://doi.org/10.5194/isprs-annals-V-2-2020-403-2020, 2020
T. Fuse and Y. Kajihara
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2020, 633–640, https://doi.org/10.5194/isprs-annals-V-2-2020-633-2020, https://doi.org/10.5194/isprs-annals-V-2-2020-633-2020, 2020
H. Albanwan and R. Qin
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2020, 227–232, https://doi.org/10.5194/isprs-annals-V-3-2020-227-2020, https://doi.org/10.5194/isprs-annals-V-3-2020-227-2020, 2020
E.-K. Stathopoulou, M. Welponer, and F. Remondino
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W17, 331–338, https://doi.org/10.5194/isprs-archives-XLII-2-W17-331-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W17-331-2019, 2019
T. Fuse and H. Ikezawa
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W18, 47–52, https://doi.org/10.5194/isprs-archives-XLII-2-W18-47-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W18-47-2019, 2019
E. Grilli, E. Özdemir, and F. Remondino
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4-W18, 447–454, https://doi.org/10.5194/isprs-archives-XLII-4-W18-447-2019, https://doi.org/10.5194/isprs-archives-XLII-4-W18-447-2019, 2019
E. Özdemir, F. Remondino, and A. Golkar
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4-W18, 843–849, https://doi.org/10.5194/isprs-archives-XLII-4-W18-843-2019, https://doi.org/10.5194/isprs-archives-XLII-4-W18-843-2019, 2019
A. Gruen, S. Schubiger, R. Qin, G. Schrotter, B. Xiong, J. Li, X. Ling, C. Xiao, S. Yao, and F. Nuesch
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4-W15, 11–18, https://doi.org/10.5194/isprs-archives-XLII-4-W15-11-2019, https://doi.org/10.5194/isprs-archives-XLII-4-W15-11-2019, 2019
K. Bakuła, J. P. Mills, and F. Remondino
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-1-W2, 1–8, https://doi.org/10.5194/isprs-archives-XLII-1-W2-1-2019, https://doi.org/10.5194/isprs-archives-XLII-1-W2-1-2019, 2019
E. Özdemir, I. Toschi, and F. Remondino
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-1-W2, 53–60, https://doi.org/10.5194/isprs-archives-XLII-1-W2-53-2019, https://doi.org/10.5194/isprs-archives-XLII-1-W2-53-2019, 2019
E.-K. Stathopoulou and F. Remondino
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W15, 1135–1140, https://doi.org/10.5194/isprs-archives-XLII-2-W15-1135-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W15-1135-2019, 2019
A. Torresani and F. Remondino
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W15, 1157–1162, https://doi.org/10.5194/isprs-archives-XLII-2-W15-1157-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W15-1157-2019, 2019
E. Nocerino, F. Menna, E. Farella, and F. Remondino
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W15, 857–864, https://doi.org/10.5194/isprs-archives-XLII-2-W15-857-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W15-857-2019, 2019
E. M. Farella, A. Torresani, and F. Remondino
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W15, 465–472, https://doi.org/10.5194/isprs-archives-XLII-2-W15-465-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W15-465-2019, 2019
E. Grilli, E. M. Farella, A. Torresani, and F. Remondino
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W15, 541–548, https://doi.org/10.5194/isprs-archives-XLII-2-W15-541-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W15-541-2019, 2019
C. Bernard, J. P. Mills, J. Talaya, and F. Remondino
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 927–934, https://doi.org/10.5194/isprs-archives-XLII-2-W13-927-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W13-927-2019, 2019
E. Özdemir and F. Remondino
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 103–110, https://doi.org/10.5194/isprs-archives-XLII-2-W13-103-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W13-103-2019, 2019
I. Toschi, D. Morabito, E. Grilli, F. Remondino, C. Carlevaro, A. Cappellotto, G. Tamagni, and M. Maffeis
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 119–126, https://doi.org/10.5194/isprs-archives-XLII-2-W13-119-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W13-119-2019, 2019
F. Menna, A. Torresani, E. Nocerino, M. M. Nawaf, J. Seinturier, F. Remondino, P. Drap, and B. Chemisky
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W10, 127–134, https://doi.org/10.5194/isprs-archives-XLII-2-W10-127-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W10-127-2019, 2019
E. M. Farella, A. Torresani, and F. Remondino
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W9, 339–346, https://doi.org/10.5194/isprs-archives-XLII-2-W9-339-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W9-339-2019, 2019
V. V. Kniaz, F. Remondino, and V. A. Knyaz
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W9, 403–408, https://doi.org/10.5194/isprs-archives-XLII-2-W9-403-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W9-403-2019, 2019
E.-K. Stathopoulou and F. Remondino
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W9, 685–690, https://doi.org/10.5194/isprs-archives-XLII-2-W9-685-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W9-685-2019, 2019
X. Huang, R. Qin, and M. Chen
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-1, 77–84, https://doi.org/10.5194/isprs-annals-IV-1-77-2018, https://doi.org/10.5194/isprs-annals-IV-1-77-2018, 2018
C. Xiao, R. Qin, X. Huang, and J. Li
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-1, 163–169, https://doi.org/10.5194/isprs-annals-IV-1-163-2018, https://doi.org/10.5194/isprs-annals-IV-1-163-2018, 2018
I. Toschi, F. Remondino, R. Rothe, and K. Klimek
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-1, 437–444, https://doi.org/10.5194/isprs-archives-XLII-1-437-2018, https://doi.org/10.5194/isprs-archives-XLII-1-437-2018, 2018
A. Nowacka and F. Remondino
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4, 467–474, https://doi.org/10.5194/isprs-archives-XLII-4-467-2018, https://doi.org/10.5194/isprs-archives-XLII-4-467-2018, 2018
E. Özdemir and F. Remondino
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4-W10, 135–142, https://doi.org/10.5194/isprs-archives-XLII-4-W10-135-2018, https://doi.org/10.5194/isprs-archives-XLII-4-W10-135-2018, 2018
D. Abate, I. Toschi, C. Sturdy-Colls, and F. Remondino
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2, 1–8, https://doi.org/10.5194/isprs-archives-XLII-2-1-2018, https://doi.org/10.5194/isprs-archives-XLII-2-1-2018, 2018
A. Dhanda, F. Remondino, and M. Santana Quintero
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2, 297–302, https://doi.org/10.5194/isprs-archives-XLII-2-297-2018, https://doi.org/10.5194/isprs-archives-XLII-2-297-2018, 2018
E. Grilli, D. Dininno, G. Petrucci, and F. Remondino
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2, 399–406, https://doi.org/10.5194/isprs-archives-XLII-2-399-2018, https://doi.org/10.5194/isprs-archives-XLII-2-399-2018, 2018
F. Menna, E. Nocerino, P. Drap, F. Remondino, A. Murtiyoso, P. Grussenmeyer, and N. Börlin
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2, 699–705, https://doi.org/10.5194/isprs-archives-XLII-2-699-2018, https://doi.org/10.5194/isprs-archives-XLII-2-699-2018, 2018
E. Nocerino, D. H. Rieke-Zapp, E. Trinkl, R. Rosenbauer, E. M. Farella, D. Morabito, and F. Remondino
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2, 773–780, https://doi.org/10.5194/isprs-archives-XLII-2-773-2018, https://doi.org/10.5194/isprs-archives-XLII-2-773-2018, 2018
Y. Tefera, F. Poiesi, D. Morabito, F. Remondino, E. Nocerino, and P. Chippendale
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2, 1097–1103, https://doi.org/10.5194/isprs-archives-XLII-2-1097-2018, https://doi.org/10.5194/isprs-archives-XLII-2-1097-2018, 2018
T. Zieher, I. Toschi, F. Remondino, M. Rutzinger, Ch. Kofler, A. Mejia-Aguilar, and R. Schlögel
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2, 1243–1250, https://doi.org/10.5194/isprs-archives-XLII-2-1243-2018, https://doi.org/10.5194/isprs-archives-XLII-2-1243-2018, 2018
Daniele Giordan, Yuichi Hayakawa, Francesco Nex, Fabio Remondino, and Paolo Tarolli
Nat. Hazards Earth Syst. Sci., 18, 1079–1096, https://doi.org/10.5194/nhess-18-1079-2018, https://doi.org/10.5194/nhess-18-1079-2018, 2018
Short summary
Short summary
Remotely piloted aerial systems can acquire on-demand ultra-high-resolution images that can be used for the identification of active processes like landslides or volcanic activities but also for the definition of effects of earthquakes, wildfires and floods. In this paper, we present a review of published literature that describes experimental methodologies developed for the study and monitoring of natural hazards.
I. Toschi, M. Allocca, and F. Remondino
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W4, 505–512, https://doi.org/10.5194/isprs-archives-XLII-3-W4-505-2018, https://doi.org/10.5194/isprs-archives-XLII-3-W4-505-2018, 2018
E. Nocerino, F. Poiesi, A. Locher, Y. T. Tefera, F. Remondino, P. Chippendale, and L. Van Gool
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W8, 187–194, https://doi.org/10.5194/isprs-archives-XLII-2-W8-187-2017, https://doi.org/10.5194/isprs-archives-XLII-2-W8-187-2017, 2017
D. Abate, I. Toschi, C. Sturdy-Colls, and F. Remondino
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W8, 1–8, https://doi.org/10.5194/isprs-archives-XLII-2-W8-1-2017, https://doi.org/10.5194/isprs-archives-XLII-2-W8-1-2017, 2017
F. Menna, E. Nocerino, D. Morabito, E. M. Farella, M. Perini, and F. Remondino
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W8, 155–162, https://doi.org/10.5194/isprs-archives-XLII-2-W8-155-2017, https://doi.org/10.5194/isprs-archives-XLII-2-W8-155-2017, 2017
E. Nocerino, M. Dubbini, F. Menna, F. Remondino, M. Gattelli, and D. Covi
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W3, 149–156, https://doi.org/10.5194/isprs-archives-XLII-3-W3-149-2017, https://doi.org/10.5194/isprs-archives-XLII-3-W3-149-2017, 2017
F. Remondino, E. Nocerino, I. Toschi, and F. Menna
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W5, 591–599, https://doi.org/10.5194/isprs-archives-XLII-2-W5-591-2017, https://doi.org/10.5194/isprs-archives-XLII-2-W5-591-2017, 2017
E. Nocerino, F. Menna, D. Morabito, F. Remondino, I. Toschi, D. Abate, D. Ebolese, E. Farella, F. Fiorillo, S. Minto, P. Rodríguez-Gonzálvez, C. Slongo, and M. G. Speraj
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2-W2, 179–186, https://doi.org/10.5194/isprs-annals-IV-2-W2-179-2017, https://doi.org/10.5194/isprs-annals-IV-2-W2-179-2017, 2017
D. Poli, K. Moe, K. Legat, I. Toschi, F. Lago, and F. Remondino
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-1-W1, 493–498, https://doi.org/10.5194/isprs-archives-XLII-1-W1-493-2017, https://doi.org/10.5194/isprs-archives-XLII-1-W1-493-2017, 2017
I. Toschi, E. Nocerino, F. Remondino, A. Revolti, G. Soria, and S. Piffer
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-1-W1, 527–534, https://doi.org/10.5194/isprs-archives-XLII-1-W1-527-2017, https://doi.org/10.5194/isprs-archives-XLII-1-W1-527-2017, 2017
E. Grilli, F. Menna, and F. Remondino
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W3, 339–344, https://doi.org/10.5194/isprs-archives-XLII-2-W3-339-2017, https://doi.org/10.5194/isprs-archives-XLII-2-W3-339-2017, 2017
K. Kamiya, T. Fuse, and M. Takahashi
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B7, 229–234, https://doi.org/10.5194/isprs-archives-XLI-B7-229-2016, https://doi.org/10.5194/isprs-archives-XLI-B7-229-2016, 2016
D. González-Aguilera, L. López-Fernández, P. Rodriguez-Gonzalvez, D. Guerrero, D. Hernandez-Lopez, F. Remondino, F. Menna, E. Nocerino, I. Toschi, A. Ballabeni, and M. Gaiani
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B6, 31–38, https://doi.org/10.5194/isprs-archives-XLI-B6-31-2016, https://doi.org/10.5194/isprs-archives-XLI-B6-31-2016, 2016
T. Fuse and R. Harada
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B5, 641–646, https://doi.org/10.5194/isprs-archives-XLI-B5-641-2016, https://doi.org/10.5194/isprs-archives-XLI-B5-641-2016, 2016
E. Farella, F. Menna, E. Nocerino, D. Morabito, F. Remondino, and M. Campi
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B5, 255–262, https://doi.org/10.5194/isprs-archives-XLI-B5-255-2016, https://doi.org/10.5194/isprs-archives-XLI-B5-255-2016, 2016
F. Remondino, I. Toschi, M. Gerke, F. Nex, D. Holland, A. McGill, J. Talaya Lopez, and A. Magarinos
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B4, 639–645, https://doi.org/10.5194/isprs-archives-XLI-B4-639-2016, https://doi.org/10.5194/isprs-archives-XLI-B4-639-2016, 2016
R. Qin
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., III-1, 77–82, https://doi.org/10.5194/isprs-annals-III-1-77-2016, https://doi.org/10.5194/isprs-annals-III-1-77-2016, 2016
E. Nocerino, F. Menna, F. Fassi, and F. Remondino
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-3-W4, 127–134, https://doi.org/10.5194/isprs-archives-XL-3-W4-127-2016, https://doi.org/10.5194/isprs-archives-XL-3-W4-127-2016, 2016
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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