Articles | Volume 18, issue 4
https://doi.org/10.5194/nhess-18-1079-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-18-1079-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Review article
| 
06 Apr 2018
Review article |
| 06 Apr 2018
| 06 Apr 2018
Review article: the use of remotely piloted aircraft systems (RPASs) for natural hazards monitoring and management
Daniele Giordan
CORRESPONDING AUTHOR
Istituto di Ricerca per la Protezione Idrogeologica, Consiglio Nazionale delle
Ricerche,
Torino, Italy
Yuichi Hayakawa
Center for Spatial Information Science, The University of Tokyo, Tokyo, Japan
Francesco Nex
University of Twente, Faculty of Geo-Information Science and Earth Observation (ITC), Enschede, the Netherlands
Fabio Remondino
3D Optical Metrology (3DOM) Unit, Bruno Kessler Foundation (FBK), Trento, Italy
Paolo Tarolli
Department of Land, Environment, Agriculture and Forestry, University of Padova, Legnaro, Italy
Related authors
Fabrizio Troilo, Niccolò Dematteis, Francesco Zucca, Martin Funk, and Daniele Giordan
EGUsphere, https://doi.org/10.5194/egusphere-2023-2771, https://doi.org/10.5194/egusphere-2023-2771, 2023
Short summary
Short summary
One of the main features of glaciers is their movement along slopes. The study of this process is relevant in many aspects of glaciology. In the present study, optical satellite images of Mont Blanc were processed, obtaining surface velocities of 30 glaciers between 2016–2022. The study highlighted different behaviours and velocity variations that have relationships with the glacier morphology. An unexpected accelerating trend was observed, but its origin needs to be further investigated.
This article is included in the Encyclopedia of Geosciences
Davide Notti, Martina Cignetti, Danilo Godone, and Daniele Giordan
Nat. Hazards Earth Syst. Sci., 23, 2625–2648, https://doi.org/10.5194/nhess-23-2625-2023, https://doi.org/10.5194/nhess-23-2625-2023, 2023
Short summary
Short summary
We developed a cost-effective and user-friendly approach to map shallow landslides using free satellite data. Our methodology involves analysing the pre- and post-event NDVI variation to semi-automatically detect areas potentially affected by shallow landslides (PLs). Additionally, we have created Google Earth Engine scripts to rapidly compute NDVI differences and time series of affected areas. Datasets and codes are stored in an open data repository for improvement by the scientific community.
This article is included in the Encyclopedia of Geosciences
D. Stroppiana, M. Pepe, M. Boschetti, A. Crema, G. Candiani, D. Giordan, M. Baldo, P. Allasia, and L. Monopoli
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 619–624, https://doi.org/10.5194/isprs-archives-XLII-2-W13-619-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W13-619-2019, 2019
Michele Santangelo, Massimiliano Alvioli, Marco Baldo, Mauro Cardinali, Daniele Giordan, Fausto Guzzetti, Ivan Marchesini, and Paola Reichenbach
Nat. Hazards Earth Syst. Sci., 19, 325–335, https://doi.org/10.5194/nhess-19-325-2019, https://doi.org/10.5194/nhess-19-325-2019, 2019
Short summary
Short summary
The paper discusses the use of rockfall modelling software and photogrammetry applied to images acquired by RPAS to provide support to civil protection agencies during emergency response. The paper focuses on a procedure that was applied to define the residual rockfall risk for a road that was hit by an earthquake-triggered rockfall that occurred during the seismic sequence that hit central Italy on 24 August 2016. Road reopening conditions were decided based on the results of this study.
This article is included in the Encyclopedia of Geosciences
Daniele Giordan, Yuichi S. Hayakawa, Francesco Nex, and Paolo Tarolli
Nat. Hazards Earth Syst. Sci., 18, 3085–3087, https://doi.org/10.5194/nhess-18-3085-2018, https://doi.org/10.5194/nhess-18-3085-2018, 2018
Short summary
Short summary
In the special issue
This article is included in the Encyclopedia of Geosciences
The use of remotely piloted aircraft systems (RPAS) in monitoring applications and management of natural hazardswe propose a collection of papers that provide a critical description of the state of the art in the use of RPAS for different scenarios. In particular, the sequence of papers can be considered an exhaustive representation of the state of the art of the methodologies and approaches applied to the study and management of natural hazards.
Daniele Giordan, Davide Notti, Alfredo Villa, Francesco Zucca, Fabiana Calò, Antonio Pepe, Furio Dutto, Paolo Pari, Marco Baldo, and Paolo Allasia
Nat. Hazards Earth Syst. Sci., 18, 1493–1516, https://doi.org/10.5194/nhess-18-1493-2018, https://doi.org/10.5194/nhess-18-1493-2018, 2018
Short summary
Short summary
We present a multiscale and multi-sensor methodology for flood mapping using free or low-cost data. We first mapped flooded areas at basin scale using free satellite data using both SAR and multispectral sensors. At local scale we refine mapping using very high-resolution images from Remotely Piloted Aerial System and terrestrial car camera, then we used these data to create 3-D model with structure from motion (SfM). All these data allowed creating accurate flooded area and water depth maps.
This article is included in the Encyclopedia of Geosciences
Federica Fiorucci, Daniele Giordan, Michele Santangelo, Furio Dutto, Mauro Rossi, and Fausto Guzzetti
Nat. Hazards Earth Syst. Sci., 18, 405–417, https://doi.org/10.5194/nhess-18-405-2018, https://doi.org/10.5194/nhess-18-405-2018, 2018
Short summary
Short summary
This paper describes the criteria for the optimal selection of remote sensing images to map event landslides, discussing the ability of monoscopic and stereoscopic VHR satellite images and ultra-high-resolution UAV images to resolve the landslide photographical and morphological signatures. The findings can be useful to decide on the optimal imagery and technique to be used when planning the production of a landslide inventory map.
This article is included in the Encyclopedia of Geosciences
D. Giordan, A. Manconi, P. Allasia, and D. Bertolo
Nat. Hazards Earth Syst. Sci., 15, 2009–2017, https://doi.org/10.5194/nhess-15-2009-2015, https://doi.org/10.5194/nhess-15-2009-2015, 2015
Short summary
Short summary
Straightforward communication of monitoring results is of major importance in emergency scenarios relevant to large slope instabilities. Here we describe the communication strategy developed for the Mont de La Saxe case study, a large rockslide threatening La Palud and Entrèves hamlets in the Courmayeur municipality (Aosta Valley, Italy).
This article is included in the Encyclopedia of Geosciences
A. Manconi and D. Giordan
Nat. Hazards Earth Syst. Sci., 15, 1639–1644, https://doi.org/10.5194/nhess-15-1639-2015, https://doi.org/10.5194/nhess-15-1639-2015, 2015
D. Giordan, A. Manconi, A. Facello, M. Baldo, F. dell'Anese, P. Allasia, and F. Dutto
Nat. Hazards Earth Syst. Sci., 15, 163–169, https://doi.org/10.5194/nhess-15-163-2015, https://doi.org/10.5194/nhess-15-163-2015, 2015
Short summary
Short summary
In recent years, the use of unmanned aerial vehicles (UAVs) in civilian/commercial contexts is becoming increasingly common, also for the applications concerning the anthropic and natural disasters. In this paper, we present the first results of a research project aimed at defining a possible methodology for the use of micro-UAVs in emergency scenarios relevant to rockfall phenomena.
This article is included in the Encyclopedia of Geosciences
Onur Can Bayrak, Zhenyu Ma, Elisa Mariarosaria Farella, Fabio Remondino, and Melis Uzar
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-2-2024, 25–32, https://doi.org/10.5194/isprs-archives-XLVIII-2-2024-25-2024, https://doi.org/10.5194/isprs-archives-XLVIII-2-2024-25-2024, 2024
Marco Medici, Giulio Perda, Andrea Sterpin, Elisa Mariarosaria Farella, Stefano Settimo, and Fabio Remondino
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-2-2024, 249–256, https://doi.org/10.5194/isprs-archives-XLVIII-2-2024-249-2024, https://doi.org/10.5194/isprs-archives-XLVIII-2-2024-249-2024, 2024
Luca Morelli, Gabriele Mazzacca, Pawel Trybała, Federica Gaspari, Francesco Ioli, Zhenyu Ma, Fabio Remondino, Keith Challis, Andrew Poad, Alex Turner, and Jon P. Mills
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-2-2024, 281–288, https://doi.org/10.5194/isprs-archives-XLVIII-2-2024-281-2024, https://doi.org/10.5194/isprs-archives-XLVIII-2-2024-281-2024, 2024
Vandita Shukla, Luca Morelli, Fabio Remondino, Andrea Micheli, Devis Tuia, and Benjamin Risse
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-2-2024, 379–386, https://doi.org/10.5194/isprs-archives-XLVIII-2-2024-379-2024, https://doi.org/10.5194/isprs-archives-XLVIII-2-2024-379-2024, 2024
Shuang Song, Luca Morelli, Xinyi Wu, Rongjun Qin, Hessah Albanwan, and Fabio Remondino
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-2-2024, 393–400, https://doi.org/10.5194/isprs-archives-XLVIII-2-2024-393-2024, https://doi.org/10.5194/isprs-archives-XLVIII-2-2024-393-2024, 2024
Paweł Trybała, Simone Rigon, Fabio Remondino, Aleksandra Banasiewicz, Adam Wróblewski, Arkadiusz Macek, Paulina Kujawa, Kinga Romańczukiewicz, Carlos Redondo, and Fran Espada
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-2-2024, 427–434, https://doi.org/10.5194/isprs-archives-XLVIII-2-2024-427-2024, https://doi.org/10.5194/isprs-archives-XLVIII-2-2024-427-2024, 2024
M. Avena, G. Patrucco, F. Remondino, and A. Spanò
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-2-W4-2024, 25–31, https://doi.org/10.5194/isprs-archives-XLVIII-2-W4-2024-25-2024, https://doi.org/10.5194/isprs-archives-XLVIII-2-W4-2024-25-2024, 2024
M. Bassier, G. Mazzacca, R. Battisti, S. Malek, and F. Remondino
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-2-W4-2024, 49–56, https://doi.org/10.5194/isprs-archives-XLVIII-2-W4-2024-49-2024, https://doi.org/10.5194/isprs-archives-XLVIII-2-W4-2024-49-2024, 2024
M. Chizhova, J. Pan, T. Luhmann, A. Karami, F. Menna, F. Remondino, M. Hess, and T. Eißing
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-2-W4-2024, 103–110, https://doi.org/10.5194/isprs-archives-XLVIII-2-W4-2024-103-2024, https://doi.org/10.5194/isprs-archives-XLVIII-2-W4-2024-103-2024, 2024
M. Codiglione, G. Mazzacca, and F. Remondino
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-2-W4-2024, 119–125, https://doi.org/10.5194/isprs-archives-XLVIII-2-W4-2024-119-2024, https://doi.org/10.5194/isprs-archives-XLVIII-2-W4-2024-119-2024, 2024
A. Elalailyi, L. Perfetti, F. Fassi, and F. Remondino
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-2-W4-2024, 189–195, https://doi.org/10.5194/isprs-archives-XLVIII-2-W4-2024-189-2024, https://doi.org/10.5194/isprs-archives-XLVIII-2-W4-2024-189-2024, 2024
E. M. Farella, S. Rigon, F. Remondino, A. Stan, G. Ioannidis, S. Münster, M. Medici, F. Maietti, and A. Sánchez
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-2-W4-2024, 197–204, https://doi.org/10.5194/isprs-archives-XLVIII-2-W4-2024-197-2024, https://doi.org/10.5194/isprs-archives-XLVIII-2-W4-2024-197-2024, 2024
L. Morelli, F. Ioli, F. Maiwald, G. Mazzacca, F. Menna, and F. Remondino
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-2-W4-2024, 309–316, https://doi.org/10.5194/isprs-archives-XLVIII-2-W4-2024-309-2024, https://doi.org/10.5194/isprs-archives-XLVIII-2-W4-2024-309-2024, 2024
E. Oniga, B. Boroianu, L. Morelli, F. Remondino, and M. Macovei
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-2-W4-2024, 333–339, https://doi.org/10.5194/isprs-archives-XLVIII-2-W4-2024-333-2024, https://doi.org/10.5194/isprs-archives-XLVIII-2-W4-2024-333-2024, 2024
M. B. Trivi, G. Mazzacca, M. Griffo, S. Malek, R. Battisti, F. Remondino, C. Bianchini, and E. Chiavoni
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-2-W4-2024, 445–451, https://doi.org/10.5194/isprs-archives-XLVIII-2-W4-2024-445-2024, https://doi.org/10.5194/isprs-archives-XLVIII-2-W4-2024-445-2024, 2024
Y. Yadav, B. Alsadik, F. Nex, F. Remondino, and P. Glira
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-W2-2023, 633–640, https://doi.org/10.5194/isprs-archives-XLVIII-1-W2-2023-633-2023, https://doi.org/10.5194/isprs-archives-XLVIII-1-W2-2023-633-2023, 2023
F. Ioli, F. Barbieri, F. Gaspari, F. Nex, and L. Pinto
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-W2-2023, 1037–1044, https://doi.org/10.5194/isprs-archives-XLVIII-1-W2-2023-1037-2023, https://doi.org/10.5194/isprs-archives-XLVIII-1-W2-2023-1037-2023, 2023
A. Masiero, L. Morelli, C. Toth, and F. Remondino
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-W2-2023, 1127–1133, https://doi.org/10.5194/isprs-archives-XLVIII-1-W2-2023-1127-2023, https://doi.org/10.5194/isprs-archives-XLVIII-1-W2-2023-1127-2023, 2023
S. M. Tilon and F. Nex
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., X-1-W1-2023, 431–437, https://doi.org/10.5194/isprs-annals-X-1-W1-2023-431-2023, https://doi.org/10.5194/isprs-annals-X-1-W1-2023-431-2023, 2023
U. V. B. L. Udugama, G. Vosselman, and F. Nex
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., X-1-W1-2023, 439–445, https://doi.org/10.5194/isprs-annals-X-1-W1-2023-439-2023, https://doi.org/10.5194/isprs-annals-X-1-W1-2023-439-2023, 2023
J. R. Bergado and F. Nex
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., X-1-W1-2023, 1027–1032, https://doi.org/10.5194/isprs-annals-X-1-W1-2023-1027-2023, https://doi.org/10.5194/isprs-annals-X-1-W1-2023-1027-2023, 2023
Fabrizio Troilo, Niccolò Dematteis, Francesco Zucca, Martin Funk, and Daniele Giordan
EGUsphere, https://doi.org/10.5194/egusphere-2023-2771, https://doi.org/10.5194/egusphere-2023-2771, 2023
Short summary
Short summary
One of the main features of glaciers is their movement along slopes. The study of this process is relevant in many aspects of glaciology. In the present study, optical satellite images of Mont Blanc were processed, obtaining surface velocities of 30 glaciers between 2016–2022. The study highlighted different behaviours and velocity variations that have relationships with the glacier morphology. An unexpected accelerating trend was observed, but its origin needs to be further investigated.
This article is included in the Encyclopedia of Geosciences
O. C. Bayrak, F. Remondino, and M. Uzar
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-W3-2023, 1–8, https://doi.org/10.5194/isprs-archives-XLVIII-1-W3-2023-1-2023, https://doi.org/10.5194/isprs-archives-XLVIII-1-W3-2023-1-2023, 2023
R. Beber, G. Perda, N. Takhtkeshha, F. Remondino, T. Maffei, D. Poli, K. Moe, P. Cipriano, and M. Ciliberti
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-W3-2023, 9–16, https://doi.org/10.5194/isprs-archives-XLVIII-1-W3-2023-9-2023, https://doi.org/10.5194/isprs-archives-XLVIII-1-W3-2023-9-2023, 2023
E. M. Farella, F. Remondino, C. Cahalane, R. Qin, A. M. Loghin, M. Di Tullio, N. Haala, and J. Mills
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-W3-2023, 47–54, https://doi.org/10.5194/isprs-archives-XLVIII-1-W3-2023-47-2023, https://doi.org/10.5194/isprs-archives-XLVIII-1-W3-2023-47-2023, 2023
C. R. Fol, A. Murtiyoso, D. Kükenbrink, F. Remondino, and V. C. Griess
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-W3-2023, 55–61, https://doi.org/10.5194/isprs-archives-XLVIII-1-W3-2023-55-2023, https://doi.org/10.5194/isprs-archives-XLVIII-1-W3-2023-55-2023, 2023
F. Nex, N. Zhang, F. Remondino, E. M. Farella, R. Qin, and C. Zhang
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-W3-2023, 123–130, https://doi.org/10.5194/isprs-archives-XLVIII-1-W3-2023-123-2023, https://doi.org/10.5194/isprs-archives-XLVIII-1-W3-2023-123-2023, 2023
N. Padkan, P. Trybala, R. Battisti, F. Remondino, and C. Bergeret
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-W3-2023, 137–144, https://doi.org/10.5194/isprs-archives-XLVIII-1-W3-2023-137-2023, https://doi.org/10.5194/isprs-archives-XLVIII-1-W3-2023-137-2023, 2023
O. Roman, E. M. Farella, S. Rigon, F. Remondino, S. Ricciuti, and D. Viesi
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-W3-2023, 175–182, https://doi.org/10.5194/isprs-archives-XLVIII-1-W3-2023-175-2023, https://doi.org/10.5194/isprs-archives-XLVIII-1-W3-2023-175-2023, 2023
P. Trybała, P. Kujawa, K. Romańczukiewicz, A. Szrek, and F. Remondino
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-W3-2023, 191–198, https://doi.org/10.5194/isprs-archives-XLVIII-1-W3-2023-191-2023, https://doi.org/10.5194/isprs-archives-XLVIII-1-W3-2023-191-2023, 2023
Z. Yan, G. Mazzacca, S. Rigon, E. M. Farella, P. Trybala, and F. Remondino
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-W3-2023, 219–226, https://doi.org/10.5194/isprs-archives-XLVIII-1-W3-2023-219-2023, https://doi.org/10.5194/isprs-archives-XLVIII-1-W3-2023-219-2023, 2023
Davide Notti, Martina Cignetti, Danilo Godone, and Daniele Giordan
Nat. Hazards Earth Syst. Sci., 23, 2625–2648, https://doi.org/10.5194/nhess-23-2625-2023, https://doi.org/10.5194/nhess-23-2625-2023, 2023
Short summary
Short summary
We developed a cost-effective and user-friendly approach to map shallow landslides using free satellite data. Our methodology involves analysing the pre- and post-event NDVI variation to semi-automatically detect areas potentially affected by shallow landslides (PLs). Additionally, we have created Google Earth Engine scripts to rapidly compute NDVI differences and time series of affected areas. Datasets and codes are stored in an open data repository for improvement by the scientific community.
This article is included in the Encyclopedia of Geosciences
G. Mazzacca, A. Karami, S. Rigon, E. M. Farella, P. Trybala, and F. Remondino
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-M-2-2023, 1051–1058, https://doi.org/10.5194/isprs-archives-XLVIII-M-2-2023-1051-2023, https://doi.org/10.5194/isprs-archives-XLVIII-M-2-2023-1051-2023, 2023
O. Roman, M. Avena, E. M. Farella, F. Remondino, and A. Spanò
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-M-2-2023, 1345–1352, https://doi.org/10.5194/isprs-archives-XLVIII-M-2-2023-1345-2023, https://doi.org/10.5194/isprs-archives-XLVIII-M-2-2023-1345-2023, 2023
F. M. La Russa, E. Grilli, F. Remondino, C. Santagati, and M. Intelisano
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-M-2-2023, 903–910, https://doi.org/10.5194/isprs-archives-XLVIII-M-2-2023-903-2023, https://doi.org/10.5194/isprs-archives-XLVIII-M-2-2023-903-2023, 2023
F. Menna, R. Battisti, E. Nocerino, and F. Remondino
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-W1-2023, 295–302, https://doi.org/10.5194/isprs-archives-XLVIII-1-W1-2023-295-2023, https://doi.org/10.5194/isprs-archives-XLVIII-1-W1-2023-295-2023, 2023
L. Morelli, F. Ioli, R. Beber, F. Menna, F. Remondino, and A. Vitti
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-W1-2023, 317–324, https://doi.org/10.5194/isprs-archives-XLVIII-1-W1-2023-317-2023, https://doi.org/10.5194/isprs-archives-XLVIII-1-W1-2023-317-2023, 2023
V. E. Oniga, L. Morelli, M. Macovei, C. Chirila, A. I. Breaban, F. Remondino, and P. Sestraș
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-W1-2023, 345–352, https://doi.org/10.5194/isprs-archives-XLVIII-1-W1-2023-345-2023, https://doi.org/10.5194/isprs-archives-XLVIII-1-W1-2023-345-2023, 2023
N. Padkan, R. Battisti, F. Menna, and F. Remondino
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-W1-2023, 363–370, https://doi.org/10.5194/isprs-archives-XLVIII-1-W1-2023-363-2023, https://doi.org/10.5194/isprs-archives-XLVIII-1-W1-2023-363-2023, 2023
P. Trybała, D. Kasza, J. Wajs, and F. Remondino
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-W1-2023, 517–524, https://doi.org/10.5194/isprs-archives-XLVIII-1-W1-2023-517-2023, https://doi.org/10.5194/isprs-archives-XLVIII-1-W1-2023-517-2023, 2023
A. Karami, M. Varshosaz, F. Menna, F. Remondino, and T. Luhmann
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., X-4-W1-2022, 363–370, https://doi.org/10.5194/isprs-annals-X-4-W1-2022-363-2023, https://doi.org/10.5194/isprs-annals-X-4-W1-2022-363-2023, 2023
F. Menna, A. Torresani, R. Battisti, E. Nocerino, and F. Remondino
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-2-W1-2022, 153–162, https://doi.org/10.5194/isprs-archives-XLVIII-2-W1-2022-153-2022, https://doi.org/10.5194/isprs-archives-XLVIII-2-W1-2022-153-2022, 2022
L. Morelli, F. Bellavia, F. Menna, and F. Remondino
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-2-W1-2022, 163–170, https://doi.org/10.5194/isprs-archives-XLVIII-2-W1-2022-163-2022, https://doi.org/10.5194/isprs-archives-XLVIII-2-W1-2022-163-2022, 2022
L. Morelli, F. Menna, A. Vitti, and F. Remondino
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-2-W1-2022, 171–176, https://doi.org/10.5194/isprs-archives-XLVIII-2-W1-2022-171-2022, https://doi.org/10.5194/isprs-archives-XLVIII-2-W1-2022-171-2022, 2022
L. Morelli, A. Karami, F. Menna, and F. Remondino
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-2-W2-2022, 77–84, https://doi.org/10.5194/isprs-archives-XLVIII-2-W2-2022-77-2022, https://doi.org/10.5194/isprs-archives-XLVIII-2-W2-2022-77-2022, 2022
P. Trybała, J. Szrek, F. Remondino, J. Wodecki, and R. Zimroz
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-2-W2-2022, 135–142, https://doi.org/10.5194/isprs-archives-XLVIII-2-W2-2022-135-2022, https://doi.org/10.5194/isprs-archives-XLVIII-2-W2-2022-135-2022, 2022
A. Nurunnabi, F. N. Teferle, D. F. Laefer, F. Remondino, I. R. Karas, and J. Li
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4-W3-2022, 111–118, https://doi.org/10.5194/isprs-archives-XLVIII-4-W3-2022-111-2022, https://doi.org/10.5194/isprs-archives-XLVIII-4-W3-2022-111-2022, 2022
N. Zhang, F. Nex, G. Vosselman, and N. Kerle
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2022, 1189–1196, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-1189-2022, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-1189-2022, 2022
A. Yilmaz, J. D. Wegner, R. Qin, F. Remondino, T. Fuse, and I. Toschi
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2022, 7–7, https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-7-2022, https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-7-2022, 2022
A. Azimi, A. Hosseininaveh, and F. Remondino
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2022, 9–14, https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-9-2022, https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-9-2022, 2022
F. Remondino, L. Morelli, E. Stathopoulou, M. Elhashash, and R. Qin
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2022, 77–84, https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-77-2022, https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-77-2022, 2022
K. K. Mwangangi, P. O. Mc’Okeyo, S. J. Oude Elberink, and F. Nex
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2022, 433–440, https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-433-2022, https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-433-2022, 2022
M. Welponer, E. K. Stathopoulou, and F. Remondino
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2022, 469–476, https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-469-2022, https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-469-2022, 2022
A. Karami, R. Battisti, F. Menna, and F. Remondino
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
S. Karam, F. Nex, O. Karlsson, J. Rydell, E. Bilock, M. Tulldahl, M. Holmberg, and N. Kerle
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-1-2022, 203–210, https://doi.org/10.5194/isprs-annals-V-1-2022-203-2022, https://doi.org/10.5194/isprs-annals-V-1-2022-203-2022, 2022
A. Yilmaz, J. D. Wegner, R. Qin, F. Remondino, T. Fuse, and I. Toschi
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2022, 7–7, https://doi.org/10.5194/isprs-annals-V-2-2022-7-2022, https://doi.org/10.5194/isprs-annals-V-2-2022-7-2022, 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
Jonathan Rizzi, Ana M. Tarquis, Anne Gobin, Mikhail Semenov, Wenwu Zhao, and Paolo Tarolli
Nat. Hazards Earth Syst. Sci., 21, 3873–3877, https://doi.org/10.5194/nhess-21-3873-2021, https://doi.org/10.5194/nhess-21-3873-2021, 2021
Pengzhi Zhao, Daniel Joseph Fallu, Sara Cucchiaro, Paolo Tarolli, Clive Waddington, David Cockcroft, Lisa Snape, Andreas Lang, Sebastian Doetterl, Antony G. Brown, and Kristof Van Oost
Biogeosciences, 18, 6301–6312, https://doi.org/10.5194/bg-18-6301-2021, https://doi.org/10.5194/bg-18-6301-2021, 2021
Short summary
Short summary
We investigate the factors controlling the soil organic carbon (SOC) stability and temperature sensitivity of abandoned prehistoric agricultural terrace soils. Results suggest that the burial of former topsoil due to terracing provided an SOC stabilization mechanism. Both the soil C : N ratio and SOC mineral protection regulate soil SOC temperature sensitivity. However, which mechanism predominantly controls SOC temperature sensitivity depends on the age of the buried terrace soils.
This article is included in the Encyclopedia of Geosciences
Mihai Ciprian Mărgărint, Mihai Niculiță, Giulia Roder, and Paolo Tarolli
Nat. Hazards Earth Syst. Sci., 21, 3251–3283, https://doi.org/10.5194/nhess-21-3251-2021, https://doi.org/10.5194/nhess-21-3251-2021, 2021
Short summary
Short summary
Local stakeholders' knowledge plays a deciding role in emergencies, supporting rescue officers in natural hazard events; coordinating; and assisting, both physically and psychologically, the affected populations. Their risk perception was assessed using a questionnaire for an area in north-eastern Romania. The results show low preparedness and reveal substantial distinctions among stakeholders and different risks based on their cognitive and behavioral roles in their communities.
This article is included in the Encyclopedia of Geosciences
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. Masiero, P. Dabove, V. Di Pietra, M. Piragnolo, A. Vettore, S. Cucchiaro, A. Guarnieri, P. Tarolli, C. Toth, V. Gikas, H. Perakis, K.-W. Chiang, L. M. Ruotsalainen, S. Goel, and J. Gabela
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B1-2021, 111–116, https://doi.org/10.5194/isprs-archives-XLIII-B1-2021-111-2021, https://doi.org/10.5194/isprs-archives-XLIII-B1-2021-111-2021, 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
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
N. Zhang, F. Nex, N. Kerle, and G. Vosselman
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2021, 427–432, https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-427-2021, https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-427-2021, 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
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
Faith E. Taylor, Paolo Tarolli, and Bruce D. Malamud
Nat. Hazards Earth Syst. Sci., 20, 2585–2590, https://doi.org/10.5194/nhess-20-2585-2020, https://doi.org/10.5194/nhess-20-2585-2020, 2020
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
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
A. Masiero, G. Sofia, and P. Tarolli
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B1-2020, 259–264, https://doi.org/10.5194/isprs-archives-XLIII-B1-2020-259-2020, https://doi.org/10.5194/isprs-archives-XLIII-B1-2020-259-2020, 2020
P. O. Mc’Okeyo, F. Nex, C. Persello, and A. Vrieling
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-1-2020, 309–316, https://doi.org/10.5194/isprs-annals-V-1-2020-309-2020, https://doi.org/10.5194/isprs-annals-V-1-2020-309-2020, 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
L. Madhuanand, F. Nex, and M. Y. Yang
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2020, 451–458, https://doi.org/10.5194/isprs-annals-V-2-2020-451-2020, https://doi.org/10.5194/isprs-annals-V-2-2020-451-2020, 2020
S. M. Tilon, F. Nex, D. Duarte, N. Kerle, and G. Vosselman
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2020, 573–582, https://doi.org/10.5194/isprs-annals-V-2-2020-573-2020, https://doi.org/10.5194/isprs-annals-V-2-2020-573-2020, 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
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
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
N. Kerle, F. Nex, D. Duarte, and A. Vetrivel
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W8, 187–194, https://doi.org/10.5194/isprs-archives-XLII-3-W8-187-2019, https://doi.org/10.5194/isprs-archives-XLII-3-W8-187-2019, 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
P. Fanta-Jende, F. Nex, M. Gerke, J. Lijnen, and G. Vosselman
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 1649–1654, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1649-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1649-2019, 2019
S. Huang, F. Nex, Y. Lin, and M. Y. Yang
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 35–42, https://doi.org/10.5194/isprs-archives-XLII-2-W13-35-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W13-35-2019, 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. Nex
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 163–164, https://doi.org/10.5194/isprs-archives-XLII-2-W13-163-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W13-163-2019, 2019
H. K. Palanirajan, B. Alsadik, F. Nex, and S. Oude Elberink
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 495–502, https://doi.org/10.5194/isprs-archives-XLII-2-W13-495-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W13-495-2019, 2019
C. Stöcker, F. Nex, M. Koeva, and M. Gerke
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 613–617, https://doi.org/10.5194/isprs-archives-XLII-2-W13-613-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W13-613-2019, 2019
D. Stroppiana, M. Pepe, M. Boschetti, A. Crema, G. Candiani, D. Giordan, M. Baldo, P. Allasia, and L. Monopoli
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 619–624, https://doi.org/10.5194/isprs-archives-XLII-2-W13-619-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W13-619-2019, 2019
D. Duarte, F. Nex, N. Kerle, and G. Vosselman
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2-W5, 29–36, https://doi.org/10.5194/isprs-annals-IV-2-W5-29-2019, https://doi.org/10.5194/isprs-annals-IV-2-W5-29-2019, 2019
F. Nex
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2-W5, 85–86, https://doi.org/10.5194/isprs-annals-IV-2-W5-85-2019, https://doi.org/10.5194/isprs-annals-IV-2-W5-85-2019, 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
Michele Santangelo, Massimiliano Alvioli, Marco Baldo, Mauro Cardinali, Daniele Giordan, Fausto Guzzetti, Ivan Marchesini, and Paola Reichenbach
Nat. Hazards Earth Syst. Sci., 19, 325–335, https://doi.org/10.5194/nhess-19-325-2019, https://doi.org/10.5194/nhess-19-325-2019, 2019
Short summary
Short summary
The paper discusses the use of rockfall modelling software and photogrammetry applied to images acquired by RPAS to provide support to civil protection agencies during emergency response. The paper focuses on a procedure that was applied to define the residual rockfall risk for a road that was hit by an earthquake-triggered rockfall that occurred during the seismic sequence that hit central Italy on 24 August 2016. Road reopening conditions were decided based on the results of this study.
This article is included in the Encyclopedia of Geosciences
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
Daniele Giordan, Yuichi S. Hayakawa, Francesco Nex, and Paolo Tarolli
Nat. Hazards Earth Syst. Sci., 18, 3085–3087, https://doi.org/10.5194/nhess-18-3085-2018, https://doi.org/10.5194/nhess-18-3085-2018, 2018
Short summary
Short summary
In the special issue
This article is included in the Encyclopedia of Geosciences
The use of remotely piloted aircraft systems (RPAS) in monitoring applications and management of natural hazardswe propose a collection of papers that provide a critical description of the state of the art in the use of RPAS for different scenarios. In particular, the sequence of papers can be considered an exhaustive representation of the state of the art of the methodologies and approaches applied to the study and management of natural hazards.
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
Johnny Cusicanqui, Norman Kerle, and Francesco Nex
Nat. Hazards Earth Syst. Sci., 18, 1583–1598, https://doi.org/10.5194/nhess-18-1583-2018, https://doi.org/10.5194/nhess-18-1583-2018, 2018
Short summary
Short summary
Aerial multi-perspective images can be used for the effective assessment of post-disaster structural damage. Alternatively, rapidly available video data can be processed for the same purpose. However, video quality characteristics are different than those of images taken with still cameras. The use of video data in post-disaster damage assessment has not been demonstrated. Based on a comparative assessment, our findings support the application of video data in post-disaster damage assessment.
This article is included in the Encyclopedia of Geosciences
Daniele Giordan, Davide Notti, Alfredo Villa, Francesco Zucca, Fabiana Calò, Antonio Pepe, Furio Dutto, Paolo Pari, Marco Baldo, and Paolo Allasia
Nat. Hazards Earth Syst. Sci., 18, 1493–1516, https://doi.org/10.5194/nhess-18-1493-2018, https://doi.org/10.5194/nhess-18-1493-2018, 2018
Short summary
Short summary
We present a multiscale and multi-sensor methodology for flood mapping using free or low-cost data. We first mapped flooded areas at basin scale using free satellite data using both SAR and multispectral sensors. At local scale we refine mapping using very high-resolution images from Remotely Piloted Aerial System and terrestrial car camera, then we used these data to create 3-D model with structure from motion (SfM). All these data allowed creating accurate flooded area and water depth maps.
This article is included in the Encyclopedia of Geosciences
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
P. Jende, F. Nex, M. Gerke, and G. Vosselman
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2, 471–477, https://doi.org/10.5194/isprs-archives-XLII-2-471-2018, https://doi.org/10.5194/isprs-archives-XLII-2-471-2018, 2018
S. Makuti, F. Nex, and M. Y. Yang
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2, 651–658, https://doi.org/10.5194/isprs-archives-XLII-2-651-2018, https://doi.org/10.5194/isprs-archives-XLII-2-651-2018, 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
D. Duarte, F. Nex, N. Kerle, and G. Vosselman
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2, 89–96, https://doi.org/10.5194/isprs-annals-IV-2-89-2018, https://doi.org/10.5194/isprs-annals-IV-2-89-2018, 2018
Y. Lin, F. Nex, and M. Y. Yang
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2, 209–216, https://doi.org/10.5194/isprs-annals-IV-2-209-2018, https://doi.org/10.5194/isprs-annals-IV-2-209-2018, 2018
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
Yuichi S. Hayakawa, Hidetsugu Yoshida, Hiroyuki Obanawa, Ryutaro Naruhashi, Koji Okumura, Masumi Zaiki, and Ryoichi Kontani
Nat. Hazards Earth Syst. Sci., 18, 429–444, https://doi.org/10.5194/nhess-18-429-2018, https://doi.org/10.5194/nhess-18-429-2018, 2018
Short summary
Short summary
This study assesses the applicability of the RPAS-based photogrammetric approach for a high-definition geomorphometry of hummocks, i.e., characteristic morphological features in the surface of debris avalanche deposits caused by a gigantic sector collapse of a volcanic mountain body. Satellite-based topographic data were also utilized to estimate the source volume of the sector collapse. We provide new, detailed insights into the characteristics of the debris avalanche and potential hazards.
This article is included in the Encyclopedia of Geosciences
Federica Fiorucci, Daniele Giordan, Michele Santangelo, Furio Dutto, Mauro Rossi, and Fausto Guzzetti
Nat. Hazards Earth Syst. Sci., 18, 405–417, https://doi.org/10.5194/nhess-18-405-2018, https://doi.org/10.5194/nhess-18-405-2018, 2018
Short summary
Short summary
This paper describes the criteria for the optimal selection of remote sensing images to map event landslides, discussing the ability of monoscopic and stereoscopic VHR satellite images and ultra-high-resolution UAV images to resolve the landslide photographical and morphological signatures. The findings can be useful to decide on the optimal imagery and technique to be used when planning the production of a landslide inventory map.
This article is included in the Encyclopedia of Geosciences
Fumitoshi Imaizumi, Yuichi S. Hayakawa, Norifumi Hotta, Haruka Tsunetaka, Okihiro Ohsaka, and Satoshi Tsuchiya
Nat. Hazards Earth Syst. Sci., 17, 1923–1938, https://doi.org/10.5194/nhess-17-1923-2017, https://doi.org/10.5194/nhess-17-1923-2017, 2017
Short summary
Short summary
Debris flow characteristics in the initiation zones are poorly understood because of the difficulty in monitoring. We studied the relationship between the flow characteristics and the accumulation conditions of the storage in an initiation zone of debris flow. Our study clarified that both partly and fully saturated flows are important processes in the initiation zones of debris flow. The predominant type of flow varied temporally and was affected by the volume of storage and rainfall patterns.
This article is included in the Encyclopedia of Geosciences
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
C. Stöcker, F. Nex, M. Koeva, and M. Gerke
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W6, 355–361, https://doi.org/10.5194/isprs-archives-XLII-2-W6-355-2017, https://doi.org/10.5194/isprs-archives-XLII-2-W6-355-2017, 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
K. Pawłuszek, A. Borkowski, and P. Tarolli
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-1-W1, 83–90, https://doi.org/10.5194/isprs-archives-XLII-1-W1-83-2017, https://doi.org/10.5194/isprs-archives-XLII-1-W1-83-2017, 2017
P. Jende, F. Nex, M. Gerke, and G. Vosselman
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-1-W1, 317–323, https://doi.org/10.5194/isprs-archives-XLII-1-W1-317-2017, https://doi.org/10.5194/isprs-archives-XLII-1-W1-317-2017, 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
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
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
Livia Piermattei, Luca Carturan, Fabrizio de Blasi, Paolo Tarolli, Giancarlo Dalla Fontana, Antonio Vettore, and Norbert Pfeifer
Earth Surf. Dynam., 4, 425–443, https://doi.org/10.5194/esurf-4-425-2016, https://doi.org/10.5194/esurf-4-425-2016, 2016
Short summary
Short summary
We investigated the applicability of the SfM–MVS approach for calculating the geodetic mass balance of a glacier and for the detection of the surface displacement rate of an active rock glacier located in the eastern Italian Alps. The results demonstrate that it is possible to reliably quantify the investigated glacial and periglacial processes by means of a quick ground-based photogrammetric survey that was conducted using a consumer grade SRL camera and natural targets as ground control points.
This article is included in the Encyclopedia of Geosciences
M. Gerke, F. Nex, and P. Jende
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-3-W4, 11–18, https://doi.org/10.5194/isprs-archives-XL-3-W4-11-2016, https://doi.org/10.5194/isprs-archives-XL-3-W4-11-2016, 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
D. Giordan, A. Manconi, P. Allasia, and D. Bertolo
Nat. Hazards Earth Syst. Sci., 15, 2009–2017, https://doi.org/10.5194/nhess-15-2009-2015, https://doi.org/10.5194/nhess-15-2009-2015, 2015
Short summary
Short summary
Straightforward communication of monitoring results is of major importance in emergency scenarios relevant to large slope instabilities. Here we describe the communication strategy developed for the Mont de La Saxe case study, a large rockslide threatening La Palud and Entrèves hamlets in the Courmayeur municipality (Aosta Valley, Italy).
This article is included in the Encyclopedia of Geosciences
A. Manconi and D. Giordan
Nat. Hazards Earth Syst. Sci., 15, 1639–1644, https://doi.org/10.5194/nhess-15-1639-2015, https://doi.org/10.5194/nhess-15-1639-2015, 2015
D. Giordan, A. Manconi, A. Facello, M. Baldo, F. dell'Anese, P. Allasia, and F. Dutto
Nat. Hazards Earth Syst. Sci., 15, 163–169, https://doi.org/10.5194/nhess-15-163-2015, https://doi.org/10.5194/nhess-15-163-2015, 2015
Short summary
Short summary
In recent years, the use of unmanned aerial vehicles (UAVs) in civilian/commercial contexts is becoming increasingly common, also for the applications concerning the anthropic and natural disasters. In this paper, we present the first results of a research project aimed at defining a possible methodology for the use of micro-UAVs in emergency scenarios relevant to rockfall phenomena.
This article is included in the Encyclopedia of Geosciences
D. Penna, M. Borga, G. T. Aronica, G. Brigandì, and P. Tarolli
Hydrol. Earth Syst. Sci., 18, 2127–2139, https://doi.org/10.5194/hess-18-2127-2014, https://doi.org/10.5194/hess-18-2127-2014, 2014
Related subject area
Risk Assessment, Mitigation and Adaptation Strategies, Socioeconomic and Management Aspects
Risk reduction through managed retreat? Investigating enabling conditions and assessing resettlement effects on community resilience in Metro Manila
Brief communication: Lessons learned and experiences gained from building up a global survey on societal resilience to changing droughts
Regional seismic risk assessment based on ground conditions in Uzbekistan
Unveiling transboundary challenges in river flood risk management: learning from the Ciliwung River basin
Quantitative study of storm surge risk assessment in an undeveloped coastal area of China based on deep learning and geographic information system techniques: a case study of Double Moon Bay
Multisectoral analysis of drought impacts and management responses to the 2008–2015 record drought in the Colorado Basin, Texas
Simulating multi-hazard event sets for life cycle consequence analysis
Analysis of the effects of urban micro-scale vulnerabilities on tsunami evacuation using an agent-based model – case study in the city of Iquique, Chile
Factors of influence on flood risk perceptions related to Hurricane Dorian: an assessment of heuristics, time dynamics, and accuracy of risk perceptions
Anticipating a risky future: long short-term memory (LSTM) models for spatiotemporal extrapolation of population data in areas prone to earthquakes and tsunamis in Lima, Peru
A new regionally consistent exposure database for Central Asia: population and residential buildings
Always on My Mind: Indications of Post-Traumatic Stress Disorder Among Those Affected by the 2021 Flood Event in the Ahr Valley, Germany
Study on seismic risk assessment model of water supply systems in mainland China
Mapping current and future flood exposure using a 5 m flood model and climate change projections
Brief communication: On the environmental impacts of the 2023 floods in Emilia-Romagna (Italy)
A regional-scale approach to assessing non-residential building, transportation and cropland exposure in Central Asia
Towards a global impact-based forecasting model for tropical cyclones
Identifying vulnerable populations in urban society: a case study in a flood-prone district of Wuhan, China
An assessment of potential improvements in social capital, risk awareness, and preparedness from digital technologies
Spatial accessibility of emergency medical services under inclement weather: a case study in Beijing, China
Review article: Current approaches and critical issues in multi-risk recovery planning of urban areas exposed to natural hazards
Estimating emergency costs for earthquakes and floods in Central Asia based on modelled losses
An Impact Chain-based exploration of multi-hazard vulnerability dynamics. The multi-hazard of floods and the COVID-19 pandemic in Romania
Compound flood impacts from Hurricane Sandy on New York City in climate-driven storylines
Regional-scale landslide risk assessment in Central Asia
Cost estimation for the monitoring instrumentation of landslide early warning systems
The role of response efficacy and self-efficacy in disaster preparedness actions for vulnerable households
Scientists as storytellers: the explanatory power of stories told about environmental crises
Back analysis of a building collapse under snow and rain loads in a Mediterranean area
Assessment of building damage and risk under extreme flood scenarios in Shanghai
Brief communication: Storm Daniel Flood Impact in Greece 2023: Mapping Crop and Livestock Exposure from SAR
Micro business participation in collective flood adaptation. Lessons from scenario-based analysis in Ho Chi Minh City, Vietnam
Mangrove ecosystem properties regulate high water levels in a river delta
Analysis of flood warning and evacuation efficiency by comparing damage and life-loss estimates with real consequences related to the São Francisco tailings dam failure in Brazil
Criteria-based visualization design for hazard maps
Low-regret climate change adaptation in coastal megacities – evaluating large-scale flood protection and small-scale rainwater detention measures for Ho Chi Minh City, Vietnam
Modeling compound flood risk and risk reduction using a globally applicable framework: a pilot in the Sofala province of Mozambique
Scenario-based multi-risk assessment from existing single-hazard vulnerability models. An application to consecutive earthquakes and tsunamis in Lima, Peru
Earthquake insurance in Iran: Solvency of local insurers in light of the current market practice
Using machine learning algorithms to identify predictors of social vulnerability in the event of a hazard: Istanbul case study
Large-scale risk assessment on snow avalanche hazard in alpine regions
Probabilistic and machine learning methods for uncertainty quantification in power outage prediction due to extreme events
Public intention to participate in sustainable geohazard mitigation: an empirical study based on an extended theory of planned behavior
An assessment of short–medium-term interventions using CAESAR-Lisflood in a post-earthquake mountainous area
Review article: Design and evaluation of weather index insurance for multi-hazard resilience and food insecurity
Design and application of a multi-hazard risk rapid assessment questionnaire for hill communities in the Indian Himalayan region
Identifying the drivers of private flood precautionary measures in Ho Chi Minh City, Vietnam
Performance of the flood warning system in Germany in July 2021 – insights from affected residents
Differences in volcanic risk perception among Goma's population before the Nyiragongo eruption of May 2021, Virunga volcanic province (DR Congo)
Empirical tsunami fragility modelling for hierarchical damage levels
Hannes Lauer, Carmeli Marie C. Chaves, Evelyn Lorenzo, Sonia Islam, and Jörn Birkmann
Nat. Hazards Earth Syst. Sci., 24, 2243–2261, https://doi.org/10.5194/nhess-24-2243-2024, https://doi.org/10.5194/nhess-24-2243-2024, 2024
Short summary
Short summary
In many urban areas, people face high exposure to hazards. Resettling them to safer locations becomes a major strategy, not least because of climate change. This paper dives into the success factors of government-led resettlement in Manila and finds surprising results which challenge the usual narrative and fuel the conversation on resettlement as an adaptation strategy. Contrary to expectations, the location – whether urban or rural – of the new home is less important than safety from floods.
This article is included in the Encyclopedia of Geosciences
Marina Batalini de Macedo, Marcos Roberto Benso, Karina Simone Sass, Eduardo Mario Mendiondo, Greicelene Jesus da Silva, Pedro Gustavo Câmara da Silva, Elisabeth Shrimpton, Tanaya Sarmah, Da Huo, Michael Jacobson, Abdullah Konak, Nazmiye Balta-Ozkan, and Adelaide Cassia Nardocci
Nat. Hazards Earth Syst. Sci., 24, 2165–2173, https://doi.org/10.5194/nhess-24-2165-2024, https://doi.org/10.5194/nhess-24-2165-2024, 2024
Short summary
Short summary
With climate change, societies increasingly need to adapt to deal with more severe droughts and the impacts they can have on food production. To make better adaptation decisions, drought resilience indicators can be used. To build these indicators, surveys with experts can be done. However, designing surveys is a costly process that can influence how experts respond. In this communication, we aim to deal with the challenges encountered in the development of surveys to help further research.
This article is included in the Encyclopedia of Geosciences
Vakhitkhan Alikhanovich Ismailov, Sharofiddin Ismatullayevich Yodgorov, Akhror Sabriddinovich Khusomiddinov, Eldor Makhmadiyorovich Yadigarov, Bekzod Uktamovich Aktamov, and Shuhrat Bakhtiyorovich Avazov
Nat. Hazards Earth Syst. Sci., 24, 2133–2146, https://doi.org/10.5194/nhess-24-2133-2024, https://doi.org/10.5194/nhess-24-2133-2024, 2024
Short summary
Short summary
For the basis of seismic risk assessment, maps of seismic intensity increment and an improved map of seismic hazard have been developed, taking into account the engineering-geological conditions of the territory of Uzbekistan and the seismic characteristics of soils. For seismic risk map development, databases were created based on geographic information system platforms, allowing us to systematize and evaluate the regional distribution of information.
This article is included in the Encyclopedia of Geosciences
Harkunti Pertiwi Rahayu, Khonsa Indana Zulfa, Dewi Nurhasanah, Richard Haigh, Dilanthi Amaratunga, and In In Wahdiny
Nat. Hazards Earth Syst. Sci., 24, 2045–2064, https://doi.org/10.5194/nhess-24-2045-2024, https://doi.org/10.5194/nhess-24-2045-2024, 2024
Short summary
Short summary
Transboundary flood risk management in the Ciliwung River basin is placed in a broader context of disaster management, environmental science, and governance. This is particularly relevant for areas of research involving the management of shared water resources, the impact of regional development on flood risk, and strategies to reduce economic losses from flooding.
This article is included in the Encyclopedia of Geosciences
Lichen Yu, Hao Qin, Shining Huang, Wei Wei, Haoyu Jiang, and Lin Mu
Nat. Hazards Earth Syst. Sci., 24, 2003–2024, https://doi.org/10.5194/nhess-24-2003-2024, https://doi.org/10.5194/nhess-24-2003-2024, 2024
Short summary
Short summary
This paper proposes a quantitative storm surge risk assessment method for data-deficient regions. A coupled model is used to simulate five storm surge scenarios. Deep learning is used to extract building footprints. Economic losses are calculated by combining adjusted depth–damage functions with inundation simulation results. Zoning maps illustrate risk levels based on economic losses, aiding in disaster prevention measures to reduce losses in coastal areas.
This article is included in the Encyclopedia of Geosciences
Stephen B. Ferencz, Ning Sun, Sean W. D. Turner, Brian A. Smith, and Jennie S. Rice
Nat. Hazards Earth Syst. Sci., 24, 1871–1896, https://doi.org/10.5194/nhess-24-1871-2024, https://doi.org/10.5194/nhess-24-1871-2024, 2024
Short summary
Short summary
Drought has long posed an existential threat to society. Population growth, economic development, and the potential for more extreme and prolonged droughts due to climate change pose significant water security challenges. Better understanding the impacts and adaptive responses resulting from extreme drought can aid adaptive planning. The 2008–2015 record drought in the Colorado Basin, Texas, United States, is used as a case study to assess impacts and responses to severe drought.
This article is included in the Encyclopedia of Geosciences
Leandro Iannacone, Kenneth Otárola, Roberto Gentile, and Carmine Galasso
Nat. Hazards Earth Syst. Sci., 24, 1721–1740, https://doi.org/10.5194/nhess-24-1721-2024, https://doi.org/10.5194/nhess-24-1721-2024, 2024
Short summary
Short summary
The paper presents a review of the available classifications for hazard interactions in a multi-hazard context, and it incorporates such classifications from a modeling perspective. The outcome is a sequential Monte Carlo approach enabling efficient simulation of multi-hazard event sets (i.e., sequences of events throughout the life cycle). These event sets can then be integrated into frameworks for the quantification of consequences for the purposes of life cycle consequence (LCCon) analysis.
This article is included in the Encyclopedia of Geosciences
Rodrigo Cienfuegos, Gonzalo Álvarez, Jorge León, Alejandro Urrutia, and Sebastián Castro
Nat. Hazards Earth Syst. Sci., 24, 1485–1500, https://doi.org/10.5194/nhess-24-1485-2024, https://doi.org/10.5194/nhess-24-1485-2024, 2024
Short summary
Short summary
This study carries out a detailed analysis of possible tsunami evacuation scenarios in the city of Iquique in Chile. Evacuation modeling and tsunami modeling are integrated, allowing for an estimation of the potential number of people that the inundation may reach under different scenarios by emulating the dynamics and behavior of the population and their decision-making regarding the starting time of the evacuation.
This article is included in the Encyclopedia of Geosciences
Laurine A. de Wolf, Peter J. Robinson, W. J. Wouter Botzen, Toon Haer, Jantsje M. Mol, and Jeffrey Czajkowski
Nat. Hazards Earth Syst. Sci., 24, 1303–1318, https://doi.org/10.5194/nhess-24-1303-2024, https://doi.org/10.5194/nhess-24-1303-2024, 2024
Short summary
Short summary
An understanding of flood risk perceptions may aid in improving flood risk communication. We conducted a survey among 871 coastal residents in Florida who were threatened to be flooded by Hurricane Dorian. Part of the original sample was resurveyed after Dorian failed to make landfall to investigate changes in risk perception. We find a strong influence of previous flood experience and social norms on flood risk perceptions. Furthermore, flood risk perceptions declined after the near-miss event.
This article is included in the Encyclopedia of Geosciences
Christian Geiß, Jana Maier, Emily So, Elisabeth Schoepfer, Sven Harig, Juan Camilo Gómez Zapata, and Yue Zhu
Nat. Hazards Earth Syst. Sci., 24, 1051–1064, https://doi.org/10.5194/nhess-24-1051-2024, https://doi.org/10.5194/nhess-24-1051-2024, 2024
Short summary
Short summary
We establish a model of future geospatial population distributions to quantify the number of people living in earthquake-prone and tsunami-prone areas of Lima and Callao, Peru, for the year 2035. Areas of high earthquake intensity will experience a population growth of almost 30 %. The population in the tsunami inundation area is estimated to grow by more than 60 %. Uncovering those relations can help urban planners and policymakers to develop effective risk mitigation strategies.
This article is included in the Encyclopedia of Geosciences
Chiara Scaini, Alberto Tamaro, Baurzhan Adilkhan, Satbek Sarzhanov, Vakhitkhan Ismailov, Ruslan Umaraliev, Mustafo Safarov, Vladimir Belikov, Japar Karayev, and Ettore Faga
Nat. Hazards Earth Syst. Sci., 24, 929–945, https://doi.org/10.5194/nhess-24-929-2024, https://doi.org/10.5194/nhess-24-929-2024, 2024
Short summary
Short summary
Central Asia is highly exposed to multiple hazards, including earthquakes, floods and landslides, for which risk reduction strategies are currently under development. We provide a regional-scale database of assets at risk, including population and residential buildings, based on existing information and recent data collected for each Central Asian country. The population and number of buildings are also estimated for the year 2080 to support the definition of disaster risk reduction strategies.
This article is included in the Encyclopedia of Geosciences
Marie-Luise Zenker, Philip Bubeck, and Annegret H. Thieken
EGUsphere, https://doi.org/10.5194/egusphere-2024-725, https://doi.org/10.5194/egusphere-2024-725, 2024
Short summary
Short summary
Despite the visible flood damage, mental health impacts are a growing concern. Yet, there is limited data in Germany. A survey in a heavily affected region revealed 28 % showing signs of posttraumatic stress disorder one year later. Risk factors Include gender, serious injury or illness due to flooding, and feeling left alone to cope with impacts. The study highlights the need for tailored mental health support for flood-affected populations.
This article is included in the Encyclopedia of Geosciences
Tianyang Yu, Banghua Lu, Hui Jiang, and Zhi Liu
Nat. Hazards Earth Syst. Sci., 24, 803–822, https://doi.org/10.5194/nhess-24-803-2024, https://doi.org/10.5194/nhess-24-803-2024, 2024
Short summary
Short summary
A basic database for seismic risk assessment of 720 urban water supply systems in mainland China is established. The parameters of the seismic risk curves of 720 cities are calculated. The seismic fragility curves of various facilities in the water supply system are given based on the logarithmic normal distribution model. The expected seismic loss and the expected loss rate index of 720 urban water supply systems in mainland China in the medium and long term are given.
This article is included in the Encyclopedia of Geosciences
Connor Darlington, Jonathan Raikes, Daniel Henstra, Jason Thistlethwaite, and Emma K. Raven
Nat. Hazards Earth Syst. Sci., 24, 699–714, https://doi.org/10.5194/nhess-24-699-2024, https://doi.org/10.5194/nhess-24-699-2024, 2024
Short summary
Short summary
The impacts of climate change on local floods require precise maps that clearly demarcate changes to flood exposure; however, most maps lack important considerations that reduce their utility in policy and decision-making. This article presents a new approach to identifying current and projected flood exposure using a 5 m model. The results highlight advancements in the mapping of flood exposure with implications for flood risk management.
This article is included in the Encyclopedia of Geosciences
Chiara Arrighi and Alessio Domeneghetti
Nat. Hazards Earth Syst. Sci., 24, 673–679, https://doi.org/10.5194/nhess-24-673-2024, https://doi.org/10.5194/nhess-24-673-2024, 2024
Short summary
Short summary
In this communication, we reflect on environmental flood impacts by analysing the reported environmental consequences of the 2023 Emilia-Romagna floods. The most frequently reported damage involves water resources and water-related ecosystems. Indirect effects in time and space, intrinsic recovery capacity, cascade impacts on socio-economic systems, and the lack of established monitoring activities appear to be the most challenging aspects for future research.
This article is included in the Encyclopedia of Geosciences
Chiara Scaini, Alberto Tamaro, Baurzhan Adilkhan, Satbek Sarzhanov, Zukhritdin Ergashev, Ruslan Umaraliev, Mustafo Safarov, Vladimir Belikov, Japar Karayev, and Ettore Fagà
Nat. Hazards Earth Syst. Sci., 24, 355–373, https://doi.org/10.5194/nhess-24-355-2024, https://doi.org/10.5194/nhess-24-355-2024, 2024
Short summary
Short summary
Central Asia is prone to multiple hazards such as floods, landslides and earthquakes, which can affect a wide range of assets at risk. We develop the first regionally consistent database of assets at risk for non-residential buildings, transportation and croplands in Central Asia. The database combines global and regional data sources and country-based information and supports the development of regional-scale disaster risk reduction strategies for the Central Asia region.
This article is included in the Encyclopedia of Geosciences
Mersedeh Kooshki Forooshani, Marc van den Homberg, Kyriaki Kalimeri, Andreas Kaltenbrunner, Yelena Mejova, Leonardo Milano, Pauline Ndirangu, Daniela Paolotti, Aklilu Teklesadik, and Monica L. Turner
Nat. Hazards Earth Syst. Sci., 24, 309–329, https://doi.org/10.5194/nhess-24-309-2024, https://doi.org/10.5194/nhess-24-309-2024, 2024
Short summary
Short summary
We improve an existing impact forecasting model for the Philippines by transforming the target variable (percentage of damaged houses) to a fine grid, using only features which are globally available. We show that our two-stage model conserves the performance of the original and even has the potential to introduce savings in anticipatory action resources. Such model generalizability is important in increasing the applicability of such tools around the world.
This article is included in the Encyclopedia of Geosciences
Jia Xu, Makoto Takahashi, and Weifu Li
Nat. Hazards Earth Syst. Sci., 24, 179–197, https://doi.org/10.5194/nhess-24-179-2024, https://doi.org/10.5194/nhess-24-179-2024, 2024
Short summary
Short summary
Through the development of micro-individual social vulnerability indicators and cluster analysis, this study assessed the level of social vulnerability of 599 residents from 11 communities in the Hongshan District of Wuhan. The findings reveal three levels of social vulnerability: high, medium, and low. Quantitative assessments offer specific comparisons between distinct units, and the results indicate that different types of communities have significant differences in social vulnerability.
This article is included in the Encyclopedia of Geosciences
Tommaso Piseddu, Mathilda Englund, and Karina Barquet
Nat. Hazards Earth Syst. Sci., 24, 145–161, https://doi.org/10.5194/nhess-24-145-2024, https://doi.org/10.5194/nhess-24-145-2024, 2024
Short summary
Short summary
Contributions to social capital, risk awareness, and preparedness constitute the parameters to test applications in disaster risk management. We propose an evaluation of four of these: mobile positioning data, social media crowdsourcing, drones, and satellite imaging. The analysis grants the opportunity to investigate how different methods to evaluate surveys' results may influence final preferences. We find that the different assumptions on which these methods rely deliver diverging results.
This article is included in the Encyclopedia of Geosciences
Yuting Zhang, Kai Liu, Xiaoyong Ni, Ming Wang, Jianchun Zheng, Mengting Liu, and Dapeng Yu
Nat. Hazards Earth Syst. Sci., 24, 63–77, https://doi.org/10.5194/nhess-24-63-2024, https://doi.org/10.5194/nhess-24-63-2024, 2024
Short summary
Short summary
This article is aimed at developing a method to quantify the influence of inclement weather on the accessibility of emergency medical services (EMSs) in Beijing, China, and identifying the vulnerable areas that could not get timely EMSs under inclement weather. We found that inclement weather could reduce the accessibility of EMSs by up to 40%. Furthermore, towns with lower baseline EMSs accessibility are more vulnerable when inclement weather occurs.
This article is included in the Encyclopedia of Geosciences
Soheil Mohammadi, Silvia De Angeli, Giorgio Boni, Francesca Pirlone, and Serena Cattari
Nat. Hazards Earth Syst. Sci., 24, 79–107, https://doi.org/10.5194/nhess-24-79-2024, https://doi.org/10.5194/nhess-24-79-2024, 2024
Short summary
Short summary
This paper critically reviews disaster recovery literature from a multi-risk perspective. Identified key challenges encompass the lack of approaches integrating physical reconstruction and socio-economic recovery, the neglect of multi-risk interactions, the limited exploration of recovery from a pre-disaster planning perspective, and the low consideration of disaster recovery as a non-linear process in which communities need change over time.
This article is included in the Encyclopedia of Geosciences
Emilio Berny, Carlos Avelar, Mario A. Salgado-Gálvez, and Mario Ordaz
Nat. Hazards Earth Syst. Sci., 24, 53–62, https://doi.org/10.5194/nhess-24-53-2024, https://doi.org/10.5194/nhess-24-53-2024, 2024
Short summary
Short summary
This paper presents a methodology to estimate the total emergency costs based on modelled damages for earthquakes and floods, together with the demographic and building characteristics of the study area. The methodology has been applied in five countries in central Asia, the first time that these estimates are made available for the study area and are intended to be useful for regional and local stakeholders and decision makers.
This article is included in the Encyclopedia of Geosciences
Andra-Cosmina Albulescu and Iuliana Armaș
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-5, https://doi.org/10.5194/nhess-2024-5, 2024
Revised manuscript accepted for NHESS
Short summary
Short summary
This study delves into 1) compounded impacts and 2) the dynamics of vulnerability within a multi-hazard context, proposing an Impact Chain-based framework that analyses the augmentation of vulnerability. The case study refers to the flood events and the COVID-19 pandemic that affected Romania (2020–2021). The Impact Chain shows that 1) the unforseen implications of impacts, 2) wrongful action of adaptation options, and 3) inaction can set the premises for increased vulnerability.
This article is included in the Encyclopedia of Geosciences
Henrique M. D. Goulart, Irene Benito Lazaro, Linda van Garderen, Karin van der Wiel, Dewi Le Bars, Elco Koks, and Bart van den Hurk
Nat. Hazards Earth Syst. Sci., 24, 29–45, https://doi.org/10.5194/nhess-24-29-2024, https://doi.org/10.5194/nhess-24-29-2024, 2024
Short summary
Short summary
We explore how Hurricane Sandy (2012) could flood New York City under different scenarios, including climate change and internal variability. We find that sea level rise can quadruple coastal flood volumes, while changes in Sandy's landfall location can double flood volumes. Our results show the need for diverse scenarios that include climate change and internal variability and for integrating climate information into a modelling framework, offering insights for high-impact event assessments.
This article is included in the Encyclopedia of Geosciences
Francesco Caleca, Chiara Scaini, William Frodella, and Veronica Tofani
Nat. Hazards Earth Syst. Sci., 24, 13–27, https://doi.org/10.5194/nhess-24-13-2024, https://doi.org/10.5194/nhess-24-13-2024, 2024
Short summary
Short summary
Landslide risk analysis is a powerful tool because it allows us to identify where physical and economic losses could occur due to a landslide event. The purpose of our work was to provide the first regional-scale analysis of landslide risk for central Asia, and it represents an advanced step in the field of risk analysis for very large areas. Our findings show, per square kilometer, a total risk of about USD 3.9 billion and a mean risk of USD 0.6 million.
This article is included in the Encyclopedia of Geosciences
Marta Sapena, Moritz Gamperl, Marlene Kühnl, Carolina Garcia-Londoño, John Singer, and Hannes Taubenböck
Nat. Hazards Earth Syst. Sci., 23, 3913–3930, https://doi.org/10.5194/nhess-23-3913-2023, https://doi.org/10.5194/nhess-23-3913-2023, 2023
Short summary
Short summary
A new approach for the deployment of landslide early warning systems (LEWSs) is proposed. We combine data-driven landslide susceptibility mapping and population maps to identify exposed locations. We estimate the cost of monitoring sensors and demonstrate that LEWSs could be installed with a budget ranging from EUR 5 to EUR 41 per person in Medellín, Colombia. We provide recommendations for stakeholders and outline the challenges and opportunities for successful LEWS implementation.
This article is included in the Encyclopedia of Geosciences
Dong Qiu, Binglin Lv, Yuepeng Cui, and Zexiong Zhan
Nat. Hazards Earth Syst. Sci., 23, 3789–3803, https://doi.org/10.5194/nhess-23-3789-2023, https://doi.org/10.5194/nhess-23-3789-2023, 2023
Short summary
Short summary
This paper divides preparedness behavior into minimal and adequate preparedness. In addition to studying the main factors that promote families' disaster preparedness, we also study the moderating effects of response efficacy and self-efficacy on preparedness actions by vulnerable families. Based on the findings of this study, policymakers can target interventions and programs that can be designed to remedy the current lack of disaster preparedness education for vulnerable families.
This article is included in the Encyclopedia of Geosciences
Jenni Barclay, Richie Robertson, and M. Teresa Armijos
Nat. Hazards Earth Syst. Sci., 23, 3603–3615, https://doi.org/10.5194/nhess-23-3603-2023, https://doi.org/10.5194/nhess-23-3603-2023, 2023
Short summary
Short summary
Stories create avenues for sharing the meanings and social implications of scientific knowledge. We explore their value when told between scientists during a volcanic eruption. They are important vehicles for understanding how risk is generated during volcanic eruptions and create new knowledge about these interactions. Stories explore how risk is negotiated when scientific information is ambiguous or uncertain, identify cause and effect, and rationalize the emotional intensity of a crisis.
This article is included in the Encyclopedia of Geosciences
Isabelle Ousset, Guillaume Evin, Damien Raynaud, and Thierry Faug
Nat. Hazards Earth Syst. Sci., 23, 3509–3523, https://doi.org/10.5194/nhess-23-3509-2023, https://doi.org/10.5194/nhess-23-3509-2023, 2023
Short summary
Short summary
This paper deals with an exceptional snow and rain event in a Mediterranean region of France which is usually not prone to heavy snowfall and its consequences on a particular building that collapsed completely. Independent analyses of the meteorological episode are carried out, and the response of the building to different snow and rain loads is confronted to identify the main critical factors that led to the collapse.
This article is included in the Encyclopedia of Geosciences
Jiachang Tu, Jiahong Wen, Liang Emlyn Yang, Andrea Reimuth, Stephen S. Young, Min Zhang, Luyang Wang, and Matthias Garschagen
Nat. Hazards Earth Syst. Sci., 23, 3247–3260, https://doi.org/10.5194/nhess-23-3247-2023, https://doi.org/10.5194/nhess-23-3247-2023, 2023
Short summary
Short summary
This paper evaluates the flood risk and the resulting patterns in buildings following low-probability, high-impact flood scenarios by a risk analysis chain in Shanghai. The results provide a benchmark and also a clear future for buildings with respect to flood risks in Shanghai. This study links directly to disaster risk management, e.g., the Shanghai Master Plan. We also discussed different potential adaptation options for flood risk management.
This article is included in the Encyclopedia of Geosciences
Kang He, Qing Yang, Xinyi Shen, Elias Dimitriou, Angeliki Mentzafou, Christina Papadaki, Maria Stoumboudi, and Emmanouil N. Anagnostou
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2023-173, https://doi.org/10.5194/nhess-2023-173, 2023
Revised manuscript accepted for NHESS
Short summary
Short summary
~820 km2 of agricultural land is inundated in central Greece due to storm Daniel flood. A detailed analysis revealed that the crop most affected by the flooding was cotton; the inundated area of more than 282 km2 comprised ~30 % of the total area planted with cotton in central Greece. In terms of livestock, we estimated more than 14,000 ornithoids and 21,500 sheep and goats were affected. Consequences for agriculture and animal husbandry in Greece are expected to be severe.
This article is included in the Encyclopedia of Geosciences
Javier Revilla Diez, Roxana Leitold, Van Tran, and Matthias Garschagen
EGUsphere, https://doi.org/10.5194/egusphere-2023-2185, https://doi.org/10.5194/egusphere-2023-2185, 2023
Short summary
Short summary
Micro-businesses, often overlooked in adaptation research, show surprising willingness to contribute to collective adaptation despite limited finances and local support. Based on a study in Ho-Chi-Minh City in Vietnam, approximately 70 % are ready for awareness campaigns, and 39 % would provide financial support if costs were shared. These findings underscore the need for increased involvement of micro-businesses in local adaptation plans to enhance collective adaptive capacity.
This article is included in the Encyclopedia of Geosciences
Ignace Pelckmans, Jean-Philippe Belliard, Luis E. Dominguez-Granda, Cornelis Slobbe, Stijn Temmerman, and Olivier Gourgue
Nat. Hazards Earth Syst. Sci., 23, 3169–3183, https://doi.org/10.5194/nhess-23-3169-2023, https://doi.org/10.5194/nhess-23-3169-2023, 2023
Short summary
Short summary
Mangroves are increasingly recognized as a coastal protection against extreme sea levels. Their effectiveness in doing so, however, is still poorly understood, as mangroves are typically located in tropical countries where data on mangrove vegetation and topography properties are often scarce. Through a modelling study, we identified the degree of channelization and the mangrove forest floor topography as the key properties for regulating high water levels in a tropical delta.
This article is included in the Encyclopedia of Geosciences
André Felipe Rocha Silva and Julian Cardoso Eleutério
Nat. Hazards Earth Syst. Sci., 23, 3095–3110, https://doi.org/10.5194/nhess-23-3095-2023, https://doi.org/10.5194/nhess-23-3095-2023, 2023
Short summary
Short summary
This work evaluates the application of flood consequence models through their application in a real case related to a tailings dam failure. Furthermore, we simulated the implementation of less efficient alert systems on life-loss alleviation. The results revealed that the models represented the event well and were able to estimate the relevance of implementing efficient alert systems. They highlight that their use may be an important tool for new regulations for dam safety legislation.
This article is included in the Encyclopedia of Geosciences
Max Schneider, Fabrice Cotton, and Pia-Johanna Schweizer
Nat. Hazards Earth Syst. Sci., 23, 2505–2521, https://doi.org/10.5194/nhess-23-2505-2023, https://doi.org/10.5194/nhess-23-2505-2023, 2023
Short summary
Short summary
Hazard maps are fundamental to earthquake risk reduction, but research is missing on how to design them. We review the visualization literature to identify evidence-based criteria for color and classification schemes for hazard maps. We implement these for the German seismic hazard map, focusing on communicating four properties of seismic hazard. Our evaluation finds that the redesigned map successfully communicates seismic hazard in Germany, improving on the baseline map for two key properties.
This article is included in the Encyclopedia of Geosciences
Leon Scheiber, Christoph Gabriel David, Mazen Hoballah Jalloul, Jan Visscher, Hong Quan Nguyen, Roxana Leitold, Javier Revilla Diez, and Torsten Schlurmann
Nat. Hazards Earth Syst. Sci., 23, 2333–2347, https://doi.org/10.5194/nhess-23-2333-2023, https://doi.org/10.5194/nhess-23-2333-2023, 2023
Short summary
Short summary
Like many other megacities in low-elevation coastal zones, Ho Chi Minh City in southern Vietnam suffers from the convoluting impact of changing environmental stressors and rapid urbanization. This study assesses quantitative hydro-numerical results against the background of the low-regret paradigm for (1) a large-scale flood protection scheme as currently constructed and (2) the widespread implementation of small-scale rainwater detention as envisioned in the Chinese Sponge City Program.
This article is included in the Encyclopedia of Geosciences
Dirk Eilander, Anaïs Couasnon, Frederiek C. Sperna Weiland, Willem Ligtvoet, Arno Bouwman, Hessel C. Winsemius, and Philip J. Ward
Nat. Hazards Earth Syst. Sci., 23, 2251–2272, https://doi.org/10.5194/nhess-23-2251-2023, https://doi.org/10.5194/nhess-23-2251-2023, 2023
Short summary
Short summary
This study presents a framework for assessing compound flood risk using hydrodynamic, impact, and statistical modeling. A pilot in Mozambique shows the importance of accounting for compound events in risk assessments. We also show how the framework can be used to assess the effectiveness of different risk reduction measures. As the framework is based on global datasets and is largely automated, it can easily be applied in other areas for first-order assessments of compound flood risk.
This article is included in the Encyclopedia of Geosciences
Juan Camilo Gómez Zapata, Massimiliano Pittore, Nils Brinckmann, Juan Lizarazo-Marriaga, Sergio Medina, Nicola Tarque, and Fabrice Cotton
Nat. Hazards Earth Syst. Sci., 23, 2203–2228, https://doi.org/10.5194/nhess-23-2203-2023, https://doi.org/10.5194/nhess-23-2203-2023, 2023
Short summary
Short summary
To investigate cumulative damage on extended building portfolios, we propose an alternative and modular method to probabilistically integrate sets of single-hazard vulnerability models that are being constantly developed by experts from various research fields to be used within a multi-risk context. We demonstrate its application by assessing the economic losses expected for the residential building stock of Lima, Peru, a megacity commonly exposed to consecutive earthquake and tsunami scenarios.
This article is included in the Encyclopedia of Geosciences
Mohsen Ghafory-Ashtiany and Hooman Motamed
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2023-81, https://doi.org/10.5194/nhess-2023-81, 2023
Revised manuscript accepted for NHESS
Short summary
Short summary
Iranian insurers has been offering earthquake cover since 1990's. However, despite international best practices they do not still use modern methods for risk pricing and management. As such, they seem to continue accumulating seismic risk over time. This paper examines the viability of this market in Iran by comparing the local market practice with international best practices in earthquake risk pricing (catastrophe modelling) and insurance risk management (European Solvency II regime).
This article is included in the Encyclopedia of Geosciences
Oya Kalaycıoğlu, Serhat Emre Akhanlı, Emin Yahya Menteşe, Mehmet Kalaycıoğlu, and Sibel Kalaycıoğlu
Nat. Hazards Earth Syst. Sci., 23, 2133–2156, https://doi.org/10.5194/nhess-23-2133-2023, https://doi.org/10.5194/nhess-23-2133-2023, 2023
Short summary
Short summary
The associations between household characteristics and hazard-related social vulnerability in Istanbul, Türkiye, were assessed using machine learning techniques. The results indicated that less educated households with no social security and job insecurity that live in squatter houses are at a higher risk of social vulnerability. We present the findings in an open-access R Shiny web application, which can serve as a guidance for identifying the target groups in the interest of risk mitigation.
This article is included in the Encyclopedia of Geosciences
Gregor Ortner, Michael Bründl, Chahan M. Kropf, Thomas Röösli, Yves Bühler, and David N. Bresch
Nat. Hazards Earth Syst. Sci., 23, 2089–2110, https://doi.org/10.5194/nhess-23-2089-2023, https://doi.org/10.5194/nhess-23-2089-2023, 2023
Short summary
Short summary
This paper presents a new approach to assess avalanche risk on a large scale in mountainous regions. It combines a large-scale avalanche modeling method with a state-of-the-art probabilistic risk tool. Over 40 000 individual avalanches were simulated, and a building dataset with over 13 000 single buildings was investigated. With this new method, risk hotspots can be identified and surveyed. This enables current and future risk analysis to assist decision makers in risk reduction and adaptation.
This article is included in the Encyclopedia of Geosciences
Prateek Arora and Luis Ceferino
Nat. Hazards Earth Syst. Sci., 23, 1665–1683, https://doi.org/10.5194/nhess-23-1665-2023, https://doi.org/10.5194/nhess-23-1665-2023, 2023
Short summary
Short summary
Power outage models can help utilities manage risks for outages from hurricanes. Our article reviews the existing outage models during hurricanes and highlights their strengths and limitations. Existing models can give erroneous estimates with outage predictions larger than the number of customers, can struggle with predictions for catastrophic hurricanes, and do not adequately represent infrastructure failure's uncertainties. We suggest models for the future that can overcome these challenges.
This article is included in the Encyclopedia of Geosciences
Huige Xing, Ting Que, Yuxin Wu, Shiyu Hu, Haibo Li, Hongyang Li, Martin Skitmore, and Nima Talebian
Nat. Hazards Earth Syst. Sci., 23, 1529–1547, https://doi.org/10.5194/nhess-23-1529-2023, https://doi.org/10.5194/nhess-23-1529-2023, 2023
Short summary
Short summary
Disaster risk reduction requires public power. The aim of this study is to investigate the factors influencing the public's intention to participate in disaster risk reduction. An empirical study was conducted using structural equation modeling data analysis methods. The findings show that public attitudes, perceptions of those around them, ability to participate, and sense of participation are important factors.
This article is included in the Encyclopedia of Geosciences
Di Wang, Ming Wang, Kai Liu, and Jun Xie
Nat. Hazards Earth Syst. Sci., 23, 1409–1423, https://doi.org/10.5194/nhess-23-1409-2023, https://doi.org/10.5194/nhess-23-1409-2023, 2023
Short summary
Short summary
The short–medium-term intervention effect on the post-earthquake area was analysed by simulations in different scenarios. The sediment transport patterns varied in different sub-regions, and the relative effectiveness in different scenarios changed over time with a general downward trend, where the steady stage implicated the scenario with more facilities performing better in controlling sediment output. Therefore, the simulation methods could support optimal rehabilitation strategies.
This article is included in the Encyclopedia of Geosciences
Marcos Roberto Benso, Gabriela Chiquito Gesualdo, Roberto Fray Silva, Greicelene Jesus Silva, Luis Miguel Castillo Rápalo, Fabricio Alonso Richmond Navarro, Patricia Angélica Alves Marques, José Antônio Marengo, and Eduardo Mario Mendiondo
Nat. Hazards Earth Syst. Sci., 23, 1335–1354, https://doi.org/10.5194/nhess-23-1335-2023, https://doi.org/10.5194/nhess-23-1335-2023, 2023
Short summary
Short summary
This article is about how farmers can better protect themselves from disasters like droughts, extreme temperatures, and floods. The authors suggest that one way to do this is by offering insurance contracts that cover these different types of disasters. By having this insurance, farmers can receive financial support and recover more quickly. The article elicits different ideas about how to design this type of insurance and suggests ways to make it better.
This article is included in the Encyclopedia of Geosciences
Shivani Chouhan and Mahua Mukherjee
Nat. Hazards Earth Syst. Sci., 23, 1267–1286, https://doi.org/10.5194/nhess-23-1267-2023, https://doi.org/10.5194/nhess-23-1267-2023, 2023
Short summary
Short summary
The Himalayas are prone to multi-hazards. To minimise loss, proper planning and execution are necessary. Data collection is the basis of any risk assessment process. This enhanced survey form is easy to understand and pictorial and identifies high-risk components of any building (structural and non-structural) surrounded by multi-hazards. Its results can help to utilise the budget in a prioritised way. A SWOT (strengths, weaknesses, threats and opportunities) analysis has been performed.
This article is included in the Encyclopedia of Geosciences
Thulasi Vishwanath Harish, Nivedita Sairam, Liang Emlyn Yang, Matthias Garschagen, and Heidi Kreibich
Nat. Hazards Earth Syst. Sci., 23, 1125–1138, https://doi.org/10.5194/nhess-23-1125-2023, https://doi.org/10.5194/nhess-23-1125-2023, 2023
Short summary
Short summary
Coastal Asian cities are becoming more vulnerable to flooding. In this study we analyse the data collected from flood-prone houses in Ho Chi Minh City to identify what motivates the households to adopt flood precautionary measures. The results revealed that educating the households about the available flood precautionary measures and communicating the flood protection measures taken by the government encourage the households to adopt measures without having to experience multiple flood events.
This article is included in the Encyclopedia of Geosciences
Annegret H. Thieken, Philip Bubeck, Anna Heidenreich, Jennifer von Keyserlingk, Lisa Dillenardt, and Antje Otto
Nat. Hazards Earth Syst. Sci., 23, 973–990, https://doi.org/10.5194/nhess-23-973-2023, https://doi.org/10.5194/nhess-23-973-2023, 2023
Short summary
Short summary
In July 2021 intense rainfall caused devastating floods in western Europe with 184 fatalities in the German federal states of North Rhine-Westphalia (NW) and Rhineland-Palatinate (RP), calling their warning system into question. An online survey revealed that 35 % of respondents from NW and 29 % from RP did not receive any warning. Many of those who were warned did not expect severe flooding, nor did they know how to react. The study provides entry points for improving Germany's warning system.
This article is included in the Encyclopedia of Geosciences
Blaise Mafuko Nyandwi, Matthieu Kervyn, François Muhashy Habiyaremye, François Kervyn, and Caroline Michellier
Nat. Hazards Earth Syst. Sci., 23, 933–953, https://doi.org/10.5194/nhess-23-933-2023, https://doi.org/10.5194/nhess-23-933-2023, 2023
Short summary
Short summary
Risk perception involves the processes of collecting, selecting and interpreting signals about the uncertain impacts of hazards. It may contribute to improving risk communication and motivating the protective behaviour of the population living near volcanoes. Our work describes the spatial variation and factors influencing volcanic risk perception of 2204 adults of Goma exposed to Nyiragongo. It contributes to providing a case study for risk perception understanding in the Global South.
This article is included in the Encyclopedia of Geosciences
Fatemeh Jalayer, Hossein Ebrahimian, Konstantinos Trevlopoulos, and Brendon Bradley
Nat. Hazards Earth Syst. Sci., 23, 909–931, https://doi.org/10.5194/nhess-23-909-2023, https://doi.org/10.5194/nhess-23-909-2023, 2023
Short summary
Short summary
Assessing tsunami fragility and the related uncertainties is crucial in the evaluation of incurred losses. Empirical fragility modelling is based on observed tsunami intensity and damage data. Fragility curves for hierarchical damage levels are distinguished by their laminar shape; that is, the curves should not intersect. However, this condition is not satisfied automatically. We present a workflow for hierarchical fragility modelling, uncertainty propagation and fragility model selection.
This article is included in the Encyclopedia of Geosciences
Cited articles
Abatzoglou, J. T. and Williams, A. P.: Impact of anthropogenic climate change on wildfire across western US forests, P. Natl. Acad. Sci. USA, 113, 11770–11775, 2016.
Aicardi, I., Chiabrando, F., Lingua, A., Noardo, F., Piras, M., and Vigna, B.: A methodology for acquisition and processing of thermal data acquired by UAVs: a test about subfluvial springs' investigations, Geomatics, Natural Hazards and Risk., 8, 5–17, https://doi.org/10.1080/19475705.2016.1225229, 2017.
Allison, R. S., Johnston, J. M., Craig, G., and Jennings, S.: Airborne Optical and Thermal Remote Sensing for Wildfire Detection and Monitoring, Sensors, 16, 1310, https://doi.org/10.3390/s16081310, 2016.
Andrews, C.: Pressure in the danger zone [volcanoes], Eng. Technol., 10, 56–61, https://doi.org/10.1049/et.2015.0720, 2015.
Ardizzone, F., Fiorucci, F., Santangelo, M., Cardinali, M., Mondini, A. C., Rossi, M., Reichenbach, P., and Guzzetti, F.: Very-high resolution stereoscopic satellite images for landslide mapping, edited by: Margottini, C., Canuti, P., Sassa, K., Landslide Science and Practice, Landslide Inventory and Susceptibility and Hazard Zoning, 1, Springer, Heidelberg, Berlin, New York, 95–101, https://doi.org/10.1007/978-3-642-31325-7_12, 2013.
Astuti, G., Giudice, G., Longo, D., Melita, C. D., Muscato, G., and Orlando, A.: An overview of the “Volcan project”: An UAS for Exploration of volcanic environments, J. Intell. Robot. Syst., 54, 471–494, 2009.
Ayoub, F., LePrince, S., and Keene, L.: User's Guide to Cosi-Corr: Co-Registration of Optically Sensed Images and Correlation, California Institute of Technology, Pasadena, CA, USA, 38 pp., 2009.
Baiocchi, V., Dominici, D., and Mormile, M.: UAV application in post–seismic environment”, International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XL-1/W2, UAV-g2013, 4–6 September 2013, Rostock, Germany, 21–25, 2013.
Baldo M., Bicocchi C., Chiocchini U., Giordan D., and Lollino G.: LIDAR monitoring of mass wasting processes: The Radicofani landslide, Province of Siena, Central Italy, Gemorphology, 105, 193–201, https://doi.org/10.1016/j.geomorph.2008.09.015, 2009.
Benassai, G., Aucelli, P., Budillon, G., De Stefano, M., Di Luccio, D., Di Paola, G., Montella, R., Mucerino, L., Sica, M., and Pennetta, M.: Rip current evidence by hydrodynamic simulations, bathymetric surveys and UAV observation, Nat. Hazards Earth Syst. Sci., 17, 1493–1503, https://doi.org/10.5194/nhess-17-1493-2017, 2017.
Bendea, H., Boccardo, P., Dequal, S., Tondo, G., Marenchino, D., and Piras, M.: Low cost UAV for post-disaster assessment, Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci., 37, 1373–1379, 2008.
Boccardo, P., Chiabrando, F., Dutto, F., Tonolo, F. G., and Lingua, A.: UAV deployment exercise for mapping purposes: Evaluation of emergency response applications, Sensors, 15, 15717–15737, 2015.
Bolognesi, M., Farina, G., Alvisi, S., Franchini, M., Pellegrinelli, A., and Russo, P.: Measurement of surface velocity in open channels using a lightweight remotely piloted aircraft system. Geomatics, Natural Hazards and Risk, 8, 73–86, https://doi.org/10.1080/19475705.2016.1184717, 2016.
Brardinoni, F., Slaymaker, O., and Hassan, M. A.: Landslides inventory in a rugged forested watershed: a comparison between air-photo and field survey data, Geomorphology, 54, 179–196, https://doi.org/10.1016/S0169-555X(02)00355-0, 2003.
Brostow, G. J., Shotton, J., Fauqueur, J., and Cipolla, R.: Segmentation and Recognition Using Structure from Motion Point Clouds. Proc. 10th European Conf. on Computer Vision: Part I, 44–57, https://doi.org/10.1007/978-3-540-88682-2_5, 2008.
Caltabiano, D., Muscato, G., Orlando, A., Federico, C., Giudice, G., and Guerrieri, S.: Architecture of a UAV for volcanic gas sampling, IEEE Int. C. Emerg., 1, 739–744, 2005.
Cannioto, M., D'Alessandro, A., Lo Bosco, G., Scudero, S., and Vitale, G.: Brief communication: Vehicle routing problem and UAV application in the post-earthquake scenario, Nat. Hazards Earth Syst. Sci., 17, 1939–1946, https://doi.org/10.5194/nhess-17-1939-2017, 2017.
Carvajal, F., Agüera, F., and Pérez, M.: Surveying a landslide in a road embankment using Unmanned Aerial Vehicle photogrammetry, ISPRS Arch., 38, 1–6, 2011.
Casagli, N., Frodella, W., Morelli, S., Tofani, V., Ciampalini, A., Intrieri, E., Raspini, F., Rossi, G., Tanteri, L., and Lu, P.: Spaceborne, UAV and ground-based remote sensing techniques for landslide mapping, monitoring and early warning, Geoenvironmental Disasters, 4, 1–23, https://doi.org/10.1186/s40677-017-0073-1, 2017.
Chang, K.-J., Chan, Y.-C., Chen, R.-F., and Hsieh, Y.-C.: Geomorphological evolution of landslides near an active normal fault in northern Taiwan, as revealed by lidar and unmanned aircraft system data, Nat. Hazards Earth Syst. Sci., 18, 709–727, https://doi.org/10.5194/nhess-18-709-2018, 2018.
Chang-Chun, L., Zhang, G., Lei, T., and Gong, A.: Quick image-processing method of UAV without control points data in earthquake disaster area, T. Nonferr. Metal. Soc., 21, s523–s528, 2011.
Chio, S.-H. and Lin, C.-H.: Preliminary Study of UAS Equipped with Thermal Camera for Volcanic Geothermal Monitoring in Taiwan, Sensors, 17, 1649, https://doi.org/10.3390/s17071649, 2017.
Chou, T. Y., Yeh, M. L., Chen, Y., and Chen, Y. H.: Disaster monitoring and management by the unmanned aerial vehicle technology, Int. Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 38, 137–142, 2010.
Costa, D., Burlando, P., and Priadi, C.: The importance of integrated solutions to flooding and water quality problems in the tropical megacity of Jakarta, Sustain. Cities Soc., 20, 199–209, https://doi.org/10.1016/j.scs.2015.09.009, 2016.
DeBell, L., Anderson, K., Brazier, R. E., King, N., and Jones, L.: Water resource management at catchment scales using lightweight UAVs: current capabilities and future perspectives, J. Unmanned Veh. Syst., 4, 7–30, https://doi.org/10.1139/juvs-2015-0026, 2016.
Deffontaines, B., Chang, K. J., Champenois, J., Fruneau, B., Pathier, E., Hu, J. C., Lu, S. T., and Liu, Y. C.: Active interseismic shallow deformation of the Pingting terraces (Longitudinal Valley – Eastern Taiwan) from UAV high-resolution topographic data combined with InSAR time series, Geomatics, Natural Hazards and Risk, 8, 120–136, 2017.
Deffontaines, B., Chang, K.-J., Champenois, J., Lin, K.-C., Lee, C.-T., Chen, R.-F., Hu, J.-C., and Magalhaes, S.: Active tectonics of the onshore Hengchun Fault using UAS DSM combined with ALOS PS-InSAR time series (Southern Taiwan), Nat. Hazards Earth Syst. Sci., 18, 829–845, https://doi.org/10.5194/nhess-18-829-2018, 2018.
Delacourt, C., Allemand, P., Jaud, M., Grandjean, P., Deschamps, A., Ammann, J., Cuq, V., and Suanez, S.: DRELIO: An Unmanned Helicopter for Imaging Coastal Areas. J. Coastal. Res., 56, 1489–1493, 2009.
Derrien, A., Villeneuve, N., Peltier, A., and Beauducel, F.: Retrieving 65 years of volcano summit deformation from multitemporal structure from motion: The case of Piton de la Fournaise (La Réunion Island), Geophys. Res. Lett., 42, 6959–6966, https://doi.org/10.1002/2015GL064820, 2015.
Deurloo, R., Bastos, L., and Bos, M.: On the Use of UAVs for Strapdown Airborne Gravimetry, Springer, Berlin, Heidelberg, 255–261, 2012.
Detzer, S., Weber, M., Touko Tcheumadjeu, L. C., Kuhns, G., and Kendziorra A.: Decision support for multimodal transportation systems at major events and disasters: a case study in the region of Brunswick (Germany), edited by: Sener, S. M., Brebbia, C. A., and Ozcevik, O., Disaster management and Human Health Risk IV, WIT Press, Southampton, UK, 315–326, 2015.
Dewitte, O., Jasselette, J. C., Cornet, Y., Van Den Eeckhaut, M., Collignon, A., Poesen, J., and Demoulin, A.: Tracking landslide displacements by multitemporal DTMs: A combined aerial stereophotogrammetric and LIDAR approach in western Belgium, Eng. Geol., 7, 582–586, 2008.
Diaz, J. A., Pieri, D., Wright, K., Sorensen, P., Kline-Shoder, R., Arkin, C. R., Fladeland, M., Bland, G., Buongiorno, M. F., Ramirez, C., Corrales, E., Alan, A., Alegria, O., Diaz, D., and Linick, J.: Unmanned Aerial Mass Spectrometer Systems for In-Situ Volcanic Plume Analysis, J. Am. Soc. Mass Spectr., 26, 292–304, https://doi.org/10.1007/s13361-014-1058-x, 2015.
Dominici, D., Alicandro, M., and Massimi, V.: UAV photogrammetry in the post-earthquake scenario: case studies in L'Aquila, Geomatics, Natural Hazards and Risk, 8, 87–103, 2017.
Dong, L. and Shan, J.: A comprehensive review of earthquake-induced building damage detection with remote sensing techniques, ISPRS Journal of Photogrammetry and Remote Sensing, 84, 85–99, 2013.
Duarte, D., Nex, F., Kerle, N., and Vosselman, G.: TOWARDS A MORE EFFICIENT DETECTION OF EARTHQUAKE INDUCED FAÇADE DAMAGES USING OBLIQUE UAV IMAGERY, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W6, 93–100, https://doi.org/10.5194/isprs-archives-XLII-2-W6-93-2017, 2017.
Dunford, R., Michel, K., Gagnage, M., Piégay, H., and Trémelo M.-L.: Potential and constraints of Unmanned Aerial Vehicle technology for the characterization of Mediterranean riparian forest, Int. J. Remote Sens., 30, 4915–4935, 2009.
Erdelj, M., Król, M., and Natalizio, E.: Wireless Sensor Networks and Multi-UAV systems for natural disaster management, Comput. Networks, 124, 72–86, https://doi.org/10.1016/j.comnet.2017.05.021, 2017.
Eugster, H. and Nebiker, S.: UAV-based augmented monitoring– real-time georeferencing and integration of video imagery with virtual globes. In: Int. Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, Beijing, China, 37, 1229–1235. 2008.
Ezequiel, C. A. F., Cua, M., Libatiquem, N. C., Tangonan, G. L., Alampay, R., Labuguen, R. T., Favila, C. M., Honrado, J. L. E., Canos, V., Devaney, C., Loreto, L. B., Bacusmo, J., and Palma, B.: UAV Aerial Imaging Applications for Post-Disaster Assessment, Environmental Management and Infrastructure Development. 2014 International Conference on Unmanned Aircraft Systems (ICUAS) Orlando, Fl, USA proceedings, 274–283, 2014.
Fan, J., Zhang, X., Su, F., Ge, Y., Tarolli, P., Yang, Z., Zeng, C., and Zeng, Z.: Geometrical feature analysis and disaster assessment of the Xinmo landslide based on remote sensing data, J. Mt. Sci., 14, 1677–1688, https://doi.org/10.1007/s11629-017-4633-3, 2017.
Feng, Q., Liu, J., and Gong, J.: Urban Flood Mapping Based on Unmanned Aerial Vehicle Remote Sensing and Random Forest Classifier – A Case of Yuyao, China, Water, 7, 1437–1455, https://doi.org/10.3390/w7041437, 2015.
Fernandez Galarreta, J., Kerle, N., and Gerke, M.: UAV-based urban structural damage assessment using object-based image analysis and semantic reasoning, Nat. Hazards Earth Syst. Sci., 15, 1087–1101, https://doi.org/10.5194/nhess-15-1087-2015, 2015.
Feurer, D., Planchon, O., El Maaoui, M. A., Boussema, M. R., and Pierrot-Deseilligny, M.: Potential of kite-borne photogrammetry for decimetric and kilometre square 3D mapping: an application for automatic gully detection, Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2017-60, in review, 2017.
Fikar, C., Gronalt, M., and Hirsch. P. A.: decision support system for coordinated disaster relief distribution, Exp. Syst. Appl., 57, 104–116, https://doi.org/10.1016/j.eswa.2016.03.039, 2016.
Filizzola, C., Corrado, R., Marchese, F., Mazzeo, G., Paciello, R., Pergola, N., and Tramutoli, V.: RST-FIRES, an exportable algorithm for early-fire detection and monitoring: Description, implementation, and field validation in the case of the MSG-SEVIRI sensor, Remote Sens. Environ., 192, 2–25, 2017.
Fiorucci, F., Giordan, D., Santangelo, M., Dutto, F., Rossi, M., and Guzzetti, F.: Criteria for the optimal selection of remote sensing optical images to map event landslides, Nat. Hazards Earth Syst. Sci., 18, 405–417, https://doi.org/10.5194/nhess-18-405-2018, 2018.
Flener, C., Vaaja, M., Jaakkola, A., Krooks, A., Kaartinen, H., Kukko, A., Kasvi, E., Hyyppä, H., Hyyppä, J., and Alho, P.: Seamless mapping of river channels at high resolution using mobile liDAR and UAV-photography, Remote Sens., 5, 6382–6407, https://doi.org/10.3390/rs5126382, 2013.
Fonstad, M. A., Dietrich, J. T., Courville, B. C., Jensen J. L., and Carbonneau, P. E.: Topographic structure from motion: a new development in photogrammetric measurement, Earth Surf. Proc. Land., 38, 421–430, 2013.
Fugazza, D., Scaioni, M., Corti, M., D'Agata, C., Azzoni, R. S., Cernuschi, M., Smiraglia, C., and Diolaiuti, G. A.: Combination of UAV and terrestrial photogrammetry to assess rapid glacier evolution and conditions of glacier hazards, Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2017-198, in review, 2017.
Gerke, M. and Kerle, N.: Automatic structural seismic damage assessment with airborne oblique pictometry imagery, in: PE&RS = Photogrammetric Engineering and Remote Sensing, 77, 885–898, 2011.
Gerke, M. and Przybilla, H. J.: Accuracy analysis of photogrammetric UAV image blocks: Influence of on-board RTK-GNSS and cross flight patterns, Photogramm. Fernerkun., 2016, 17–30, 2016.
Giordan, D., Allasia, P., Manconi, A., Baldo, M., Santangelo, M., Cardinali, M., Corazza, A., Albanese, V., Lollino, G., and Guzzetti, F.: Morphological and kinematic evolution of a large earthflow: The Montaguto landslide, southern Italy, Geomorphology, 187, 61–79, 2013.
Giordan, D., Manconi, A., Facello, A., Baldo, M., dell'Anese, F., Allasia, P., and Dutto, F.: Brief Communication: The use of an unmanned aerial vehicle in a rockfall emergency scenario, Nat. Hazards Earth Syst. Sci., 15, 163–169, https://doi.org/10.5194/nhess-15-163-2015, 2015a.
Giordan, D., Manconi, A., Tannant, D., and Allasia, P.: UAV: low-cost remote sensing for high-resolution investigation of landslides, IEEE International Symposium on Geoscience and Remote Sensing IGARSS, 26–31 July 2015, Milan, Italy, 5344–5347, 2015b.
Giordan, D., Notti, D., Villa, A., Zucca, F., Calò, F., Pepe, A., Dutto, F., Pari, P., Baldo, M., and Allasia, P.: Low cost, multiscale and multi-sensor application for flooded areas mapping, Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2017-420, in review, 2017.
Gomez, C.: Digital photogrammetry and GIS-based analysis of the bio-geomorphological evolution of Sakurajima Volcano, diachronic analysis from 1947 to 2006, J. Volcanol. Geoth. Res., 280, 1–13, https://doi.org/10.1016/j.jvolgeores.2014.04.015, 2014.
Gomez, C. and Kato, A.: Multi-scale voxel-based algorithm for UAV-derived point-clouds of complex surfaces, IEEE International ICARES – Aerospace Electornics and Remote Sensing Technology, 205–209, https://doi.org/10.1109/ICARES.2014.7024399, 2014.
Gomez, C. and Purdie, H.: UAV- based Photogrammetry and Geocomputing for Hazards and Disaster Risk Monitoring – A Review, Geoenvironmental Disasters, 3, 1–11, 2016.
Gomez, C., Hayakawa, Y., and Obanawa, H.: A study of Japanese landscapes using structure from motion derived DSMs and DEMs based on historical aerial photographs: New opportunities for vegetation monitoring and diachronic geomorphology, Geomorphology, 242, 11–20, https://doi.org/10.1016/j.geomorph.2015.02.021, 2015.
GSI: Information on the 2017 Northern Kyushu Heavy Rain, Geospatial Inf. Auth. Japan, available from: http://www.gsi.go.jp/BOUSAI/H29hukuoka_ooita-heavyrain.html, last access: 16 September 2017.
Guha-Sapir, D., Hoyois, P., Wallemacq, P., and Below, R.: Annual Disaster Statistical Review 2016 The numbers and trends. Centre for Research on the Epidemiology of Disasters, Ciaco Imprimerie, Louvain-la-Neuve (Belgium), 91, 2017.
Guzzetti, F., Reichenbach, P., Cardinali, M., Galli, M., and Ardizzone, F.: Probabilistic landslide hazard assessment at the basin scale, Geomorphology, 72, 272–299, 2005.
Haneberg, W. C.: Using close range terrestrial digital photogrammetry for 3-D rock slope modeling and discontinuity mapping in the United States, B. Eng. Geol. Environ., 67, 457–469, 2008.
Harvey, M. C., Rowland, J. V., and Luketina, K. M.: Drone with thermal infrared camera provides high resolution georeferenced imagery of the Waikite geothermal area, New Zealand, J. Volcanol. Geoth. Res., 325, 61–69, https://doi.org/10.1016/j.jvolgeores.2016.06.014, 2016.
Hayakawa, Y. S., Yoshida, H., Obanawa, H., Naruhashi, R., Okumura, K., Zaiki, M., and Kontani, R.: Characteristics of debris avalanche deposits inferred from source volume estimate and hummock morphology around Mt. Erciyes, central Turkey, Nat. Hazards Earth Syst. Sci., 18, 429–444, https://doi.org/10.5194/nhess-18-429-2018, 2018.
Hervouet, A., Dunford, R., Piégay, H., Belletti, B., and Trémélo, M.-L.: Analysis of Post-flood Recruitment Patterns in Braided-Channel Rivers at Multiple Scales Based on an Image Series Collected by Unmanned Aerial Vehicles, Ultra-light Aerial Vehicles, and Satellites, Geosci. Remote Sens., 48, 50–73, 2011.
Hinkley, E. and Zajkowski, T.: USDA forest service-NASA: unmanned aerial systems demonstrations–pushing the leading edge in fire mapping, Geocarto Int., 26, 103–111, 2011.
Hirose, M., Xiao, Y., Zuo, Z., Kamat, V. R., Zekkos, D., and Lynch, J.: Implementation of UAV localization methods for a mobile post-earthquake monitoring system, in: 2015 IEEE Workshop on Environmental, Energy, and Structural Monitoring Systems (EESMS) Proceedings, 66–71, 2015.
Huang, H., Long, J., Lin, H., Zang, L., Yi, W., and Lei, B.: Unmanned aerial vehicle based remote sensing method for monitoring a steep mountainous slope in the Three Gorges Reservoir, China, Earth Sci. Inform., 10, 287–301, 2017a.
Huang, H., Long, J., Yi, W., Yi, Q., Zhang, G., and Lei, B.: A method for using unmanned aerial vehicles for emergency investigation of single geo-hazards and sample applications of this method, Nat. Hazards Earth Syst. Sci., 17, 1961–1979, https://doi.org/10.5194/nhess-17-1961-2017, 2017b.
Immerzeel, W. W., Kraaijenbrink, P. D. A., Shea, J. M., Shrestha, A. B., Pellicciotti, F., Bierkens, M. F. P., and de Jonga, S. M.: High-resolution monitoring of Himalayan glacier dynamics using unmanned aerial vehicles, Remote Sens. Environ., 150, 93–103, 2014.
Izumida, A., Uchiyama, S., and Sugai, T.: Application of UAV-SfM photogrammetry and aerial lidar to a disastrous flood: repeated topographic measurement of a newly formed crevasse splay of the Kinu River, central Japan, Nat. Hazards Earth Syst. Sci., 17, 1505–1519, https://doi.org/10.5194/nhess-17-1505-2017, 2017.
Jaud, M., Grasso, F., Le Dantec, N., Verney, R., Delacourt, C., Ammann, J., Deloffre, J., and Grandjean, P.: Potential of UAVs for Monitoring Mudflat Morphodynamics (Application to the Seine Estuary, France), ISPRS Int. J. Geo-Inf., 5, 50, https://doi.org/10.3390/ijgi5040050,, 2016.
Javernick, L., Brasington, J., and Caruso, B.: Modeling the topography of shallow braided rivers using Structure-from-Motion photogrammetry, Geomorphology, 213, 166–182, https://doi.org/10.1016/j.geomorph.2014.01.006, 2014.
Joyce, K. E., Belliss, S. E., Samsonov, S. V., McNeill, S. J., and Glassey, P. J.: A review of the status of satellite remote sensing and image processing techniques for mapping natural hazards and disasters, Prog. Phys. Geog., 33, 83–207, 2009.
Kraft, T., Geßner, M., Meißner, H., Cramer, M., Gerke, M., and Przybilla, H. J.: Evaluation of a metric camera system tailored for high precision UAV applications, in: Proceedings of the XXIII ISPRS Congress : From human history to the future with spatial information, 12–19 July 2016, Prague, Czech Republic. Peer reviewed Annals, Volume III-2, 2016, Comm II, ThS14 recent developments in Open Data – Prague, Vol. XLI-B1, ISSN 2194-9034, 2016.
Klemas, V. V.: Coastal and Environmental Remote Sensing from Unmanned Aerial Vehicles: An Overview, J. Coastal. Res., 31, 1260–1267, 2015.
Koutsoudisa, A., Vidmarb, B., Ioannakisa, G., Arnaoutogloua, F., Pavlidis, V., and Chamzasc, C.: Multi-image 3D reconstruction data evaluation, J. Cult. Herit., 15, 73–79, 2014.
Lazzari, M. and Gioia, D.: UAV images and high-resolution DEMs for geomorphological analysis and hazard evaluation: the case of the Uggiano archaeological site (Ferrandina, southern Italy), Geomatics, Natural Hazards and Risk, 8, 104–119, 2017.
Langhammer, J., Lendzioch, T., Miřijovskyý, J., and Hartvich, F.: UAV-based optical granulometry as tool for detecting changes in structure of flood depositions, Remote Sens., 9, 240, https://doi.org/10.3390/rs9030240, 2017.
Le Coz, J., Patalano, A., Collins, D., Guillén, N. F., García, C. M., Smart, G. M., Bind, J., Chiaverini, A., Le Boursicaud, R., Dramais, G., and Braud, I.: Crowdsourced data for flood hydrology: Feedback from recent citizen science projects in Argentina, France and New Zealand, J. Hydrol., 541, 766–777, https://doi.org/10.1016/j.jhydrol.2016.07.036, 2016.
Lehmann, F., Berger, R., Brauchle, J., Hein, D., Meißner, H., and Pless, S.: MACS – Modular Airborne Camera System for generating photogrammetric high-resolution products, Zeitschrift der Deutschen Gesellschaft für Geowissenschaften, Schweizerbart Science Publishers, Stuttgart, Germany, 435–446, 2011.
Leprince, S., Barbot, S., Ayoub, F., and Ayouac, J. P.: Automatic and precise orthorectification, co-registration, and sub-pixel correlation of satellite images, application to ground deformation measurements, IEEE T. Geosci. Remote, 46, 1529–1558, 2007.
Leprince, S., Berthier, E., Ayoub, F., Delacourt, C., and Avouac, J.-P.: Monitoring Earth Surface Dynamics With Optical Imagery, EOS T. Am. Geophys. Un., 89, 1–2, https://doi.org/10.1029/2008EO010001, 2008.
Li, Y., Gong, J. H., Zhu, J., Ye, L., Song, Y. Q., and Yue, Y. J.: Efficient dam break flood simulation methods for developing a preliminary evacuation plan after the Wenchuan Earthquake, Nat. Hazards Earth Syst. Sci., 12, 97–106, https://doi.org/10.5194/nhess-12-97-2012, 2012.
Lindner, G., Schraml, K., Mansberger, R., and Hubl, J.: UAV monitoring and documentation of a large landslide, Appl Geomat., 8, 1–11, 2016.
Liu, C.-C., Chen, P.-L., Tomoya, M., and Chen, C.-Y.: Rapidly responding to landslides and debris flow events using a low-cost unmanned aerial vehicle, J. Remote Sens. 9, 1–11, https://doi.org/10.1117/1.JRS.9.096016, 2015.
Lucieer, A., de Jong, S. M., and Turner, D.: Mapping landslide displacements using Structure from Motion (SfM) and image correlation of multi-temporal UAV photography, Prog, Phys. Geog., 38, 97–116, 2014a.
Lucieer, A., Turner, D., King, D. H., and Robinson, S. A.: Using an Unmanned Aerial Vehicle (UAV) to capture microtopography of Antarctic moss beds. Int. J. Appl. Earth Obs.. 27, 53–62, 2014b.
Manferdini, A., Baroncini V., and Corsi, C.: An integrated and automated segmentation approach to deteriorated regions recognition on 3D reality-based models of cultural heritage artifacts, J. Cult. Herit., 13, 371–378, 2012.
Marek, L., Miřijovský, J., and Tuček, P.: Monitoring of the Shallow Landslide Using UAV Photogrammetry and Geodetic Measurements, in: Engineering Geology for Society and Territory – Landslide Processes, edited by: Lollino, G., Giordan, D., Crosta, G. B., Corominas, J., Azzam, R. Wasowski, J., and Sciarra, N., Springer International Publishing, Switzerland, 2, 113–116, 2015.
Martin, P. G., Smith, N. T., Yamashiki, Y., Payton, O. D., Russell-Pavier F. S., Fardoulis, J. S., Richards D. A., and Scott, T. B.: 3D unmanned aerial vehicle radiation mapping for assessing contaminant distribution and mobility, Int. J. Appl. Earth Obs., 52, 12–19, 2016.
Martinez-de, Dios, J. R., Merino, L., Caballero, F., and Ollero, A.: Automatic forest-fire measuring using ground stations and unmanned aerial systems, Sensors, 11, 6328–6353, 2011.
McGonigle, A. J. S., Aiuppa, A., Giudice, G., Tamburello, G., Hodson, A. J., and Gurrieri, S.: Unmanned aerial vehicle measurements of volcanic carbon dioxide fluxes, Geophys. Res. Lett., 35, 3–6, https://doi.org/10.1029/2007GL032508, 2008.
McKenzie, D., Shankar, U., Keane, R. E., Stavros, E. N., Heilman, W. E., Fox, D. G., and Riebau, A. C.: Smoke consequences of new wildfire regimes driven by climate change, Earth's Future, 2, 35–59, 2014.
Merino, L., Caballero, F., Martínez-de-Dios, J. R., Iván, M., and Aníbal, O.: An unmanned aircraft system for automatic forest fire monitoring and measurement, J. Intell. Robot. Syst., 65, 533–548, 2012.
Middlemiss, R. P., Samarelli, A., Paul, D. J., Hough, J., Rowan, S., and Hammond, G. D.: The First Measurement of the Earth Tides with a MEMS Gravimeter, Nature, 531, 614–617, https://doi.org/10.1038/nature17397, 2016.
Molina, P., Colomina, I., Vitoria, T., Silva, P. F., Skaloud, J., Kornus, W., Prades, R., and Aguilera, C.: Searching lost people with UAVs: the system and results of the close-search project, International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 39, 441–446, 2012.
Mori, T., Hashimoto, T., Terada, A., Yoshimoto, M., Kazahaya, R., Shinohara, H., and Tanaka, R.: Volcanic plume measurements using a UAV for the 2014 Mt. Ontake eruption, Earth, Planets Sp., 68, 49, https://doi.org/10.1186/s40623-016-0418-0, 2016.
Murphy, R. R., Steimle, E., Griffin, C., Cullins, C., Hall, M., and Pratt, K.: Cooperative use of unmanned sea surface and micro aerial vehicles at Hurricane Wilma, J. Field Robot., 25, 164–180, 2008.
Nagatani, K., Akiyama, K., Yamauchi, G., Otsuka, H., Nakamura, T., Kiribayashi, S., Yoshida, K., Hada, Y., Yuta, S., Fujino, K., Izu, T., and Mackay, R.: Volcanic ash observation in active volcano areas using teleoperated mobile robots – Introduction to our robotic-volcano-observation project and field experiments, in: Proc. 2013 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR), Linkoping, Sweden, 21–26 October 2013, 1–6, 2013.
Nakamura, F., Shimatani, Y., Nishihiro, J., Ohtsuki, K., Itsukushima, R., and Yamada, H.: Report on flood disaster in Kinu River, occurred in September, 2015, Ecol. Civ. Eng., 19, 259–267, https://doi.org/10.3825/ece.19.259, 2017 (in Japanese with English abstract).
Nakano, T., Kamiya, I., Tobita, M., Iwahashi, J., and Nakajima, H.: Landform monitoring in active volcano by UAV and SFM-MVS technique, Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. – ISPRS Arch., 40, 71–75, 2014.
Nedjati, A., Vizvari, B., and Izbirak, G.: Post-earthquake response by small UAV helicopters, Nat. Hazards, 80, 1669–1688, https://doi.org/10.1007/s11069-015-2046-6, 2016.
Nex, F. and Remondino, F.: UAV for 3D mapping applications: a review, Appl. Geomatics, 6, 1–15, https://doi.org/10.1007/s12518-013-0120-x, 2014.
Nex, F., Rupnik, E., Toschi, I., and Remondino, F.: Automated processing of high resolution airborne images for earthquake damage assessment, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-1, 315–321, https://doi.org/10.5194/isprsarchives-XL-1-315-2014, 2014.
Nex, F., Gerke, M., Remondino, F., Przybilla, H.-J., Bäumker, M., and Zurhorst, A.: ISPRS Benchmark for Multi-Platform Photogrammetry, ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, II3/W4, 135–142, 2015.
Niculiţǎ, M.: Automatic landslide length and width estimation based on the geometric processing of the bounding box and the geomorphometric analysis of DEMs, Nat. Hazards Earth Syst. Sci., 16, 2021–2030, https://doi.org/10.5194/nhess-16-2021-2016, 2016.
Niethammer, U., Rothmund, S., and Joswig, M.: UAV-based remote sensing of the slow-moving landslide Super-Sauze, in: Proceedings of the International Conference on Landslide Processes: from geomorpholgic mapping to dynamic modelling, edited by: Malet, J.-P., Remaître, A., and Boogard, T., Strasbourg, CERG Editions, 69–74, 2009.
Niethammer, U., Rothmund, S., James, M. R., Travelletti, J., and Joswig, M.: UAV-based remote sensing of landslides. In Proceedings of the International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, Commission V Symposium, Newcastle upon Tyne, UK, 21–24 June 2010, 496–501, 2010.
Niethammer, U., Rothmund, S., Schwaderer, U., Zeman, J., and Joswig, M.: Open Source Image-Processing Tools for Low-Cost UAV-Based Landslide Investigations. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXVIII-1/C22, 2011 ISPRS Zurich 2011 Workshop, 14–16 September 2011, Zurich, Switzerland, 161–166, 2011.
Niethammer, U., James, M. R., Rothmund, S., Travelletti, J., and Joswig, M.: UAV-based remote sensing of the Super-Sauze landslide: evaluation and results, Eng. Geol., 128, 2–11, 2012.
Nishar, A., Richards, S., Breen, D., Robertson, J., and Breen, B.: Thermal infrared imaging of geothermal environments and by an unmanned aerial vehicle (UAV): A case study of the Wairakei – Tauhara geothermal field, Taupo, New Zealand, Renew. Energ., 86, 1256–1264, https://doi.org/10.1016/j.renene.2015.09.042, 2016.
Nocerino, E., Menna, F., Remondino, F., and Saleri, R: Accuracy and block deformation analysis in automatic UAV and terrestrial photogrammetry – Lesson learnt. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. II(5/W1), Proc. 24th Intern. CIPA Symposium, 2–6 Sept., Strasbourg, France, 203–208, 2013.
Obanawa, H., Hayakawa, Y., and Gomez, C.: 3D Modelling of inaccessible Areas using UAV-based Aerial Photography and Structure from Motion, Transactions of the Japanese Geomorphological Union, 35, 283–294, 2014.
Peppa, M. V., Mills, J. P., Moore, P., Miller, P. E., and Chambers, J. E.: Brief communication: Landslide motion from cross correlation of UAV-derived morphological attributes, Nat. Hazards Earth Syst. Sci., 17, 2143–2150, https://doi.org/10.5194/nhess-17-2143-2017, 2017.
Peters, M. P., Iverson, L. R., Matthews, S. N., and Prasad, A. M.: Wildfire hazard mapping: exploring site conditions in eastern US wildland–urban interfaces, Int. J. Wildland Fire, 22, 567–578, 2013.
Pham, T.-T.-H., Apparicio, P., Gomez, C., Weber, C., and Mathon, D.: Towards a rapid automatic detection of building damage using remote sensing for disaster management. The Haiti earthquake, Dis. Prev. Manage., 23, 53–66, https://doi.org/10.1108/DPM-12-2012-0148, 2014.
Piras, M., Taddia, G., Forno, M. G., Gattiglio, M., Aicardi, I., Dabove, P., Lo Russo, S., and Lingua, A.: Detailed geological mapping in mountain areas using an unmanned aerial vehicle: application to the Rodoretto Valley, NW Italian Alps, Geomatics, Natural Hazards and Risk, 8, 137–149, 2017.
Pollefeys, M., Gool, L. V., Vergauwen, M., Cornelis, K., Verbiest, F., and Tops, J.: Image-Based 3D Acquisition of Archaeological Heritage and Applications, Proc. Conf. on Virtual Reality, Archeology, and Cultural Heritage, 255–262, 2001.
Pratt, K. S., Murphy, R., Stover, S., and Griffin, C.: Conops and autonomy recommendations for VTOL small unmanned aerial system based on Hurricane Katrina operations, J. Field Robot., 26, 636–650, 2009.
Pyo, J., Cho, H., Joe, H., Ura, T., and Yu, S.: Development of hovering type AUV “Cyclops” and its performance evaluation using image mosaicing, Ocean Eng., 109, 517–530, https://doi.org/10.1016/j.oceaneng.2015.09.023, 2015.
Rau, J. Y., Jhan, J. P., Lo, C. F., and Lin, Y. S.: Landslide mapping using imagery acquired by a fixed-wing UAV, International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXVIII-1/C22, 2011 ISPRS Zurich 2011 Workshop, 14–16 September 2011, Zurich, Switzerland, 195–200, 2011.
Razak, K. A., Santangelo, M., Van Westen, C. J., Straatsma, M. W., and de Jong, S. M.: Generating an optimal DTM from airborne laser scanning data for landslide mapping in a tropical forest environment, Geomorphology, 190, 112–125, https://doi.org/10.1016/j.geomorph.2013.02.021, 2013.
Rossi, G., Tanteri, L., Tofani, V., Vannocci, P., Moretti, S., and Casagli, N.: Brief Communication: Use of multicopter drone optical images for landslide mapping and characterization, Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2017-46, 2017.
Ryan, J. C., Hubbard, A. L., Box, J. E., Todd, J., Christoffersen, P., Carr, J. R., Holt, T. O., and Snooke, N.: UAV photogrammetry and structure from motion to assess calving dynamics at Store Glacier, a large outlet draining the Greenland ice sheet, The Cryosphere, 9, 1–11, https://doi.org/10.5194/tc-9-1-2015, 2015.
Saiki, K. and Ohba, T.: Development of an unmanned observation aerial vehicle (UAV) as a tool for volcano survey (in Japanese with English abstract), Bull. Volcanol. Soc. Japan Second Ser., 55, 137–146, 2010.
Salvini, R., Mastrorocco, G., Seddaiu, M., Rossi, D., and Vanneschi, C.: The use of an unmanned aerial vehicle for fracture mapping within a marble quarry (Carrara, Italy): photogrammetry and discrete fracture network modelling, Geomatics, Natural Hazards and Risk, 8, 34–52, 2017.
Salvini, R., Mastrorocco, G., Esposito, G., Di Bartolo, S., Coggan, J., and Vanneschi, C.: Use of a remotely piloted aircraft system for hazard assessment in a rocky mining area (Lucca, Italy), Nat. Hazards Earth Syst. Sci., 18, 287–302, https://doi.org/10.5194/nhess-18-287-2018, 2018.
Sanada, Y. and Torii T.: Aerial radiation monitoring around the Fukushima Dai-ichi nuclear power plant using an unmanned helicopter, J. Environ. Radioactiv., 139, 294–299, 2015.
Santangelo, M., Cardinali, M., Rossi, M., Mondini, A. C., and Guzzetti, F.: Remote landslide mapping using a laser rangefinder binocular and GPS, Nat. Hazards Earth Syst. Sci., 10, 2539–2546, https://doi.org/10.5194/nhess-10-2539-2010, 2010.
Saroglou, C., Asteriou, P., Zekkos, D., Tsiambaos, G., Clark, M., and Manousakis, J.: UAV-based mapping, back analysis and trajectory modeling of a coseismic rockfall in Lefkada island, Greece, Nat. Hazards Earth Syst. Sci., 18, 321–333, https://doi.org/10.5194/nhess-18-321-2018, 2018.
Scaioni, M., Longoni, L., Melillo, V., and Papini, M.: Remote Sensing for Landslide Investigations: An Overview of Recent Achievements and Perspectives, Remote Sens., 6, 9600–9652, 2014,
Schroeder, W., Oliva, P., Giglio, L., Quayle, B., Lorenz, E., and Morelli, F.: Active fire detection using Landsat-8/OLI data, Remote Sens. Environ., 185, 210–220, 2016.
Şerban, G., Rus, I., Vele, D., Breţcan, P., Alexe, M., and Petrea, D.: Flood-prone area delimitation using UAV technology, in the areas hard-to-reach for classic aircrafts: case study in the north-east of Apuseni Mountains, Transylvania, Nat. Hazards, 82, 1817–1832, https://doi.org/10.1007/s11069-016-2266-4, 2016.
Shinohara, H.: Composition of volcanic gases emitted during repeating Vulcanian eruption stage of Shinmoedake, Kirishima volcano, Japan, Earth Planets Sp., 65, 667–675, https://doi.org/10.5047/eps.2012.11.001, 2013.
Smith, M. W., Carrivick, J. L., Hooke, J., and Kirkby, M. J.: Reconstructing flash flood magnitudes using “Structure-from-Motion”: A rapid assessment tool, J. Hydrol., 519, 1914–1927, https://doi.org/10.1016/j.jhydrol.2014.09.078, 2014.
Sohn, H., Heo, J., Yoo, H., Kim, S., and Cho, H.: Hierarchical multi-sensor approach for the assessment of flood related damages, Proc. XXI Congr., 207–210, 2008.
Stöcker, C., Bennett, R., Nex, F., Gerke, M., and Zevenbergen, J.: Review of the current state of UAV regulations, Remote Sens., 9, 459, https://doi.org/10.3390/rs9050459, 2017.
Tang, L. and Shao, G.: Drone remote sensing for forestry research and practices, J. Forest Res., 26, 791–797, 2015.
Tamminga, A. D., Eaton, B. C., and Hugenholtz, C. H.: UAS-based remote sensing of fluvial change following an extreme flood event, Earth Surf. Proc. Land., 40, 1464–1476, https://doi.org/10.1002/esp.3728, 2015.
Tannant, D. D., Giordan, D., and Morgenroth, J.: Characterization and analysis of a translational rockslide on a stepped-planar slip surface, Eng. Geol., 220, 144–151, 2017.
Tarolli, P.: High-resolution topography for understanding Earth surface processes: opportunities and challenges, Geomorphology, 216, 295–312, 2014.
Thamm, H. P. and Judex, M.: The “Low cost drone” – An interesting tool for process monitoring in a high spatial and temporal resolution. The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, Enschede, the Netherlands, Vol. XXXVI part 7, 2006.
Tobita, M., Kamiya, I., Iwahashi, J., Nakano, T., and Takakuwa, N.: UAV aerial photogrammetry in Nishinoshima Island and its analysis, Bull. Geospatial Inf. Auth. Japan, 125, 115–124, 2014a (in Japanese).
Tobita, M., Kamiya, I., Nakano, T., Iwahashi, J., Osumi, K., and Takakuwa, N.: Precise UAV aerial photogrammetry in Nishinoshima Island, Bull. Geospatial Inf. Auth. Japan, 125, 145–154, 2014b (in Japanese).
Tokarczyk, P., Leitao, J. P., Rieckermann, J., Schindler, K., and Blumensaat, F.: High-quality observation of surface imperviousness for urban runoff modelling using UAV imagery, Hydrol. Earth Syst. Sci., 19, 4215–4228, https://doi.org/10.5194/hess-19-4215-2015, 2015.
Torrero, L. Seoli, L. Molino, A. Giordan, D. Manconi, A. Allasia, P., and Baldo, M.: The Use of Micro-UAV to Monitor Active Landslide Scenarios, in: Engineering Geology for Society and Territory, edited by: Lollino, G., Manconi, A., Guzzetti, F., Culshaw, M., Bobrowsky P., and Luino, F., Springer International Publishing, Switzerland, 5, 701–704, https://doi.org/10.1007/978-3-319-09048-1_136, 2015.
Török, Á., Barsi, Á., Bögöly, G., Lovas, T., Somogyi, Á., and Görög, P.: Slope stability and rockfall assessment of volcanic tuffs using RPAS with 2-D FEM slope modelling, Nat. Hazards Earth Syst. Sci., 18, 583–597, https://doi.org/10.5194/nhess-18-583-2018, 2018.
Travelletti, J., Delacourt, C., Allemand, P., Malet, J. P., Schmittbuhl, J., Toussaint, R., and Bastard, M.: Correlation of multi-temporal ground-based optical images for landslide monitoring: application, potential and limitations, ISPRS J. Photogramm. Remote Sens., 70, 39–55, 2012.
Tu, J., Sui, H., Feng, W., Sun, K., Xu, C., and Han, Q.: Detecting building facade damage from oblique aerial images using local symmetry feature and the Gini Index, Remote Sens. Lett., 8, 676–685, 2017.
Turner, D. and Lucieer, A.: Using a micro unmanned aerial vehicle (UAV) for ultra-high resolution mapping and monitoring of landslide dynamics, in: Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, Melbourne, Australia, 25 July 2013.
Turner, D., Lucieer, A., and Watson, C.: An automated technique for generating georectified mosaics from ultrahigh resolution unmanned aerial vehicle (UAV) imagery, structure from motion (SfM) point clouds, Remote Sens., 4, 1392–1410, 2012.
Turner, D., Lucieer, A., and de Jong, S. M.: Time Series Analysis of Landslide Dynamics Using an Unmanned Aerial Vehicle (UAV), Remote Sens., 7, 1736–1757, 2015.
UVS international: https://uvs-international.org, last access: 3 March 2018.
Van Den Eeckhaut, M., Poesen, J., Verstraeten, G., Vanacker, V., Nyssen, J., Moeyersons, J., van Beek, L. P. H., and Vandekerckhove, L.: Use of LIDAR-derived images for mapping old landslides under forest, Earth Surf. Proc. Land., 32, 754–769, https://doi.org/10.1002/esp.1417, 2007.
Van Westen, J. C., Castellanos, E., and Kuriakose, S. L.: Spatial data for landslide susceptibility, hazard, and vulnerability assessment: An overview, Eng. Geol., 102, 112–131, 2008.
Vetrivel, A., Gerke, M., Kerle, N., and Vosselman, G.: Identification of damage in buildings based on gaps in 3D point clouds from very high resolution oblique airborne images, ISPRS Journal of Photogrammetry and Remote Sensing, 105, 61–78, 2015.
Vetrivel, A., Gerke, M., Kerle, N., Nex, F., and Vosselman, G.: Disaster damage detection through synergistic use of deep learning and 3D point cloud features derived from very high resolution oblique aerial images, and multiple-kernel-learning, ISPRS Journal of Photogrammetry and Remote Sensing, https://doi.org/10.1016/j.isprsjprs.2017.03.001, in press, 2017.
Walter, M., Niethammer, U., Rothmund, S., and Joswig, M.: Joint analysis of the Super-Sauze (French Alps) mudslide by nanoseismic monitoring and UAV-based remote sensing, EAGE First Break, 27, 75–82, 2009.
Wen, Q., He, H., Wang, X., Wu, W., Wang, L., Xu, F., Wang, P., Tang, T., and Lei, Y.: UAV remote sensing hazard assessment in Zhouqu debris flow disaster, in: Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions, edited by: Bostater, C. R., Ertikas, S. P., Neyt, X., and Velez-Reyes, M., 8 pp., 2011.
Westoby, M. J., Brasington, J., Glasser, N. F., Hambrey, M. J., and Reynolds, M. J.: Structure-from-Motion photogrammetry: A low-cost, effective tool for geoscience applications, Geomorphology, 179, 300–314, 2012.
Wing, M. G., Burnett, J. D., and Sessions, J.: Remote sensing and unmanned aerial system technology for monitoring and quantifying forest fire impacts, Int. J. Remote. Sens. Appl., 4, 18–35, 2014.
Witek, M., Jeziorska, J., and Niedzielski, T.: An experimental approach to verifying prognoses of floods using an unmanned aerial vehicle, Meteorol. Hydrol. Water Manag., 2, 3–11, 2014.
Woodget, A. S., Carbonneau, P. E., Visser, F., and Maddock, I. P.: Quantifying submerged fluvial topography using hyperspatial resolution UAS imagery and structure from motion photogrammetry, Earth Surf. Proc. Land., 40, 47–64, https://doi.org/10.1002/esp.3613, 2015.
Xie, Z., Yang, J., Peng, C., Wu, Y., Jiang, X., Li, R., Zheng, Y., Gao, Y., Liu, S., and Tian, B.: Development of an UAS for post-earthquake disaster surveying and its application in Ms7.0 Lushan Earthquake, Sichuan, China, Comput. Geosci., 68, 22–30, 2014.
Yajima, R., Nagatani, K., and Yoshida, K.: Development and field testing of UAV-based sampling devices for obtaining volcanic products, in 2014 IEEE International Symposium on Safety, Security, and Rescue Robotics, 27–30 October 2014, Hokkaido, Japan, 1–5, 2014.
Yoon, W. S., Jeong, U. J., and Kim, J. H.: Kinematic analysis for sliding failure of multi-faced rock slopes, Eng. Geol., 67, 51–61, 2002.
Zajkowski, T. J., Dickinson, M. B., Hiers, J. K., Holley, W., Williams, B. W., Paxton, A., Martinez, O., and Walker, G. W.: Evaluation and use of remotely piloted aircraft systems for operations and research – RxCADRE 2012, Int. J. Wildland Fire, 25, 114–128, 2015.
Zazo, S., Molina, J. L., and Rodríguez-Gonzálvez, P.: Analysis of flood modeling through innovative geomatic methods, J. Hydrol., 524, 522–537, https://doi.org/10.1016/j.jhydrol.2015.03.011, 2015.
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.
Remotely piloted aerial systems can acquire on-demand ultra-high-resolution images that can be...
Altmetrics
Final-revised paper
Preprint