Articles | Volume 18, issue 6
https://doi.org/10.5194/nhess-18-1583-2018
© 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-18-1583-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
08 Jun 2018
Research article |
| 08 Jun 2018
| 08 Jun 2018
Usability of aerial video footage for 3-D scene reconstruction and structural damage assessment
Johnny Cusicanqui
CORRESPONDING AUTHOR
Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, Enschede, the Netherlands
Norman Kerle
Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, Enschede, the Netherlands
Francesco Nex
Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, Enschede, the Netherlands
Related authors
No articles found.
Aulia Imania Sukma, Mila N. Koeva, Diana Reckien, Marija Bockarjova, Andre da Silva Mano, Giulia Canili, Giovanni Vicentini, and Norman Kerle
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4-W11-2024, 129–136, https://doi.org/10.5194/isprs-archives-XLVIII-4-W11-2024-129-2024, https://doi.org/10.5194/isprs-archives-XLVIII-4-W11-2024-129-2024, 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
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
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. 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
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
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
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
Seyedabdolhossein Mehvar, Kathelijne Wijnberg, Bas Borsje, Norman Kerle, Jan Maarten Schraagen, Joanne Vinke-de Kruijf, Karst Geurs, Andreas Hartmann, Rick Hogeboom, and Suzanne Hulscher
Nat. Hazards Earth Syst. Sci., 21, 1383–1407, https://doi.org/10.5194/nhess-21-1383-2021, https://doi.org/10.5194/nhess-21-1383-2021, 2021
Short summary
Short summary
This review synthesizes and complements existing knowledge in designing resilient vital infrastructure systems (VIS). Results from a systematic literature review indicate that (i) VIS are still being built without taking resilience explicitly into account and (ii) measures to enhance the resilience of VIS have not been widely applied in practice. The main pressing topic to address is the integration of the combined social, ecological, and technical resilience of these systems.
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
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
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
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
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
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
S. Ghaffarian and N. Kerle
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 297–302, https://doi.org/10.5194/isprs-archives-XLII-2-W13-297-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W13-297-2019, 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. 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
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
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.
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
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
Daniele Giordan, Yuichi Hayakawa, Francesco Nex, Fabio Remondino, and Paolo Tarolli
Nat. Hazards Earth Syst. Sci., 18, 1079–1096, https://doi.org/10.5194/nhess-18-1079-2018, https://doi.org/10.5194/nhess-18-1079-2018, 2018
Short summary
Short summary
Remotely piloted aerial systems can acquire on-demand ultra-high-resolution images that can be used for the identification of active processes like landslides or volcanic activities but also for the definition of effects of earthquakes, wildfires and floods. In this paper, we present a review of published literature that describes experimental methodologies developed for the study and monitoring of natural hazards.
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
D. Duarte, F. Nex, N. Kerle, and G. Vosselman
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, https://doi.org/10.5194/isprs-archives-XLII-2-W6-93-2017, 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
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
W. Kim, N. Kerle, and M. Gerke
Nat. Hazards Earth Syst. Sci., 16, 287–298, https://doi.org/10.5194/nhess-16-287-2016, https://doi.org/10.5194/nhess-16-287-2016, 2016
Short summary
Short summary
This study assesses the value of a novel technology, mobile augmented reality, for rapid damage and safety assessment of the state of buildings in the aftermath of a disaster event. In this study, we propose and demonstrate conceptual frameworks and approaches for in situ ground-based assessment based on augmented reality using mobile devices such as smartphones and tablet PCs.
J. Fernandez Galarreta, N. Kerle, and M. Gerke
Nat. Hazards Earth Syst. Sci., 15, 1087–1101, https://doi.org/10.5194/nhess-15-1087-2015, https://doi.org/10.5194/nhess-15-1087-2015, 2015
W. T. Yang, M. Wang, N. Kerle, C. J. Van Westen, L. Y. Liu, and P. J. Shi
Nat. Hazards Earth Syst. Sci., 15, 817–825, https://doi.org/10.5194/nhess-15-817-2015, https://doi.org/10.5194/nhess-15-817-2015, 2015
N. Kerle and R. R. Hoffman
Nat. Hazards Earth Syst. Sci., 13, 97–113, https://doi.org/10.5194/nhess-13-97-2013, https://doi.org/10.5194/nhess-13-97-2013, 2013
Related subject area
Databases, GIS, Remote Sensing, Early Warning Systems and Monitoring Technologies
Insights into the development of a landslide early warning system prototype in an informal settlement: the case of Bello Oriente in Medellín, Colombia
Tsunami hazard perception and knowledge of alert: early findings in five municipalities along the French Mediterranean coastlines
Exploiting radar polarimetry for nowcasting thunderstorm hazards using deep learning
Machine-learning-based nowcasting of the Vögelsberg deep-seated landslide: why predicting slow deformation is not so easy
Fixed photogrammetric systems for natural hazard monitoring with high spatio-temporal resolution
A neural network model for automated prediction of avalanche danger level
Brief communication: Landslide activity on the Argentinian Santa Cruz River mega dam works confirmed by PSI DInSAR
Impact of topography on in situ soil wetness measurements for regional landslide early warning – a case study from the Swiss Alpine Foreland
Earthquake building damage detection based on synthetic-aperture-radar imagery and machine learning
Assessing riverbank erosion in Bangladesh using time series of Sentinel-1 radar imagery in the Google Earth Engine
Quantifying unequal urban resilience to rainfall across China from location-aware big data
Comparison of machine learning techniques for reservoir outflow forecasting
Development of black ice prediction model using GIS-based multi-sensor model validation
Forecasting vegetation condition with a Bayesian auto-regressive distributed lags (BARDL) model
A dynamic hierarchical Bayesian approach for forecasting vegetation condition
Using a single remote-sensing image to calculate the height of a landslide dam and the maximum volume of a lake
Enhancing disaster risk resilience using greenspace in urbanising Quito, Ecuador
Gridded flood depth estimates from satellite-derived inundations
ProbFire: a probabilistic fire early warning system for Indonesia
Index establishment and capability evaluation of space–air–ground remote sensing cooperation in geohazard emergency response
Brief communication: Monitoring a soft-rock coastal cliff using webcams and strain sensors
Multiscale analysis of surface roughness for the improvement of natural hazard modelling
EUNADICS-AV early warning system dedicated to supporting aviation in the case of a crisis from natural airborne hazards and radionuclide clouds
Are sirens effective tools to alert the population in France?
UAV survey method to monitor and analyze geological hazards: the case study of the mud volcano of Villaggio Santa Barbara, Caltanissetta (Sicily)
Timely prediction potential of landslide early warning systems with multispectral remote sensing: a conceptual approach tested in the Sattelkar, Austria
CHILDA – Czech Historical Landslide Database
Review article: Detection of actionable tweets in crisis events
Long-term magnetic anomalies and their possible relationship to the latest greater Chilean earthquakes in the context of the seismo-electromagnetic theory
HazMapper: a global open-source natural hazard mapping application in Google Earth Engine
Opportunities and risks of disaster data from social media: a systematic review of incident information
Online urban-waterlogging monitoring based on a recurrent neural network for classification of microblogging text
Predicting power outages caused by extratropical storms
Near-real-time automated classification of seismic signals of slope failures with continuous random forests
Assessing the accuracy of remotely sensed fire datasets across the southwestern Mediterranean Basin
Responses to severe weather warnings and affective decision-making
The object-specific flood damage database HOWAS 21
A spaceborne SAR-based procedure to support the detection of landslides
GIS-based DRASTIC and composite DRASTIC indices for assessing groundwater vulnerability in the Baghin aquifer, Kerman, Iran
Review article: The spatial dimension in the assessment of urban socio-economic vulnerability related to geohazards
Design and implementation of a mobile device app for network-based earthquake early warning systems (EEWSs): application to the PRESTo EEWS in southern Italy
CCAF-DB: the Caribbean and Central American active fault database
Evaluation of a combined drought indicator and its potential for agricultural drought prediction in southern Spain
Study on real-time correction of site amplification factor
Three-dimensional rockfall shape back analysis: methods and implications
Effects of high-resolution geostationary satellite imagery on the predictability of tropical thunderstorms over Southeast Asia
InSAR technique applied to the monitoring of the Qinghai–Tibet Railway
Understanding the spatiotemporal development of human settlement in hurricane-prone areas on the US Atlantic and Gulf coasts using nighttime remote sensing
Pre-disaster mapping with drones: an urban case study in Victoria, British Columbia, Canada
New approaches to modelling of local seismic amplification susceptibility using direct characteristics of influencing criteria: case study of Bam City, Iran
Christian Werthmann, Marta Sapena, Marlene Kühnl, John Singer, Carolina Garcia, Tamara Breuninger, Moritz Gamperl, Bettina Menschik, Heike Schäfer, Sebastian Schröck, Lisa Seiler, Kurosch Thuro, and Hannes Taubenböck
Nat. Hazards Earth Syst. Sci., 24, 1843–1870, https://doi.org/10.5194/nhess-24-1843-2024, https://doi.org/10.5194/nhess-24-1843-2024, 2024
Short summary
Short summary
Early warning systems (EWSs) promise to decrease the vulnerability of self-constructed (informal) settlements. A living lab developed a partially functional prototype of an EWS for landslides in a Medellín neighborhood. The first findings indicate that technical aspects can be manageable, unlike social and political dynamics. A resilient EWS for informal settlements has to achieve sufficient social and technical redundancy to maintain basic functionality in a reduced-support scenario.
Johnny Douvinet, Noé Carles, Pierre Foulquier, and Matthieu Peroche
Nat. Hazards Earth Syst. Sci., 24, 715–735, https://doi.org/10.5194/nhess-24-715-2024, https://doi.org/10.5194/nhess-24-715-2024, 2024
Short summary
Short summary
This study provided an opportunity to assess both the perception of the tsunami hazard and the knowledge of alerts in five municipalities located along the French Mediterranean coastlines. The age and location of the respondents explain several differences between the five municipalities surveyed – more so than gender or residence status. This study may help local authorities to develop future tsunami awareness actions and to identify more appropriate strategies to be applied in the short term.
Nathalie Rombeek, Jussi Leinonen, and Ulrich Hamann
Nat. Hazards Earth Syst. Sci., 24, 133–144, https://doi.org/10.5194/nhess-24-133-2024, https://doi.org/10.5194/nhess-24-133-2024, 2024
Short summary
Short summary
Severe weather such as hail, lightning, and heavy rainfall can be hazardous to humans and property. Dual-polarization weather radars provide crucial information to forecast these events by detecting precipitation types. This study analyses the importance of dual-polarization data for predicting severe weather for 60 min using an existing deep learning model. The results indicate that including these variables improves the accuracy of predicting heavy rainfall and lightning.
Adriaan L. van Natijne, Thom A. Bogaard, Thomas Zieher, Jan Pfeiffer, and Roderik C. Lindenbergh
Nat. Hazards Earth Syst. Sci., 23, 3723–3745, https://doi.org/10.5194/nhess-23-3723-2023, https://doi.org/10.5194/nhess-23-3723-2023, 2023
Short summary
Short summary
Landslides are one of the major weather-related geohazards. To assess their potential impact and design mitigation solutions, a detailed understanding of the slope is required. We tested if the use of machine learning, combined with satellite remote sensing data, would allow us to forecast deformation. Our results on the Vögelsberg landslide, a deep-seated landslide near Innsbruck, Austria, show that the formulation of such a machine learning system is not as straightforward as often hoped for.
Xabier Blanch, Marta Guinau, Anette Eltner, and Antonio Abellan
Nat. Hazards Earth Syst. Sci., 23, 3285–3303, https://doi.org/10.5194/nhess-23-3285-2023, https://doi.org/10.5194/nhess-23-3285-2023, 2023
Short summary
Short summary
We present cost-effective photogrammetric systems for high-resolution rockfall monitoring. The paper outlines the components, assembly, and programming codes required. The systems utilize prime cameras to generate 3D models and offer comparable performance to lidar for change detection monitoring. Real-world applications highlight their potential in geohazard monitoring which enables accurate detection of pre-failure deformation and rockfalls with a high temporal resolution.
Vipasana Sharma, Sushil Kumar, and Rama Sushil
Nat. Hazards Earth Syst. Sci., 23, 2523–2530, https://doi.org/10.5194/nhess-23-2523-2023, https://doi.org/10.5194/nhess-23-2523-2023, 2023
Short summary
Short summary
Snow avalanches are a natural hazard that can cause danger to human lives. This threat can be reduced by accurate prediction of the danger levels. The development of mathematical models based on past data and present conditions can help to improve the accuracy of prediction. This research aims to develop a neural-network-based model for correlating complex relationships between the meteorological variables and the profile variables.
Guillermo Tamburini-Beliveau, Sebastián Balbarani, and Oriol Monserrat
Nat. Hazards Earth Syst. Sci., 23, 1987–1999, https://doi.org/10.5194/nhess-23-1987-2023, https://doi.org/10.5194/nhess-23-1987-2023, 2023
Short summary
Short summary
Landslides and ground deformation associated with the construction of a hydropower mega dam in the Santa Cruz River in Argentine Patagonia have been monitored using radar and optical satellite data, together with the analysis of technical reports. This allowed us to assess the integrity of the construction, providing a new and independent dataset. We have been able to identify ground deformation trends that put the construction works at risk.
Adrian Wicki, Peter Lehmann, Christian Hauck, and Manfred Stähli
Nat. Hazards Earth Syst. Sci., 23, 1059–1077, https://doi.org/10.5194/nhess-23-1059-2023, https://doi.org/10.5194/nhess-23-1059-2023, 2023
Short summary
Short summary
Soil wetness measurements are used for shallow landslide prediction; however, existing sites are often located in flat terrain. Here, we assessed the ability of monitoring sites at flat locations to detect critically saturated conditions compared to if they were situated at a landslide-prone location. We found that differences exist but that both sites could equally well distinguish critical from non-critical conditions for shallow landslide triggering if relative changes are considered.
Anirudh Rao, Jungkyo Jung, Vitor Silva, Giuseppe Molinario, and Sang-Ho Yun
Nat. Hazards Earth Syst. Sci., 23, 789–807, https://doi.org/10.5194/nhess-23-789-2023, https://doi.org/10.5194/nhess-23-789-2023, 2023
Short summary
Short summary
This article presents a framework for semi-automated building damage assessment due to earthquakes from remote-sensing data and other supplementary datasets including high-resolution building inventories, while also leveraging recent advances in machine-learning algorithms. For three out of the four recent earthquakes studied, the machine-learning framework is able to identify over 50 % or nearly half of the damaged buildings successfully.
Jan Freihardt and Othmar Frey
Nat. Hazards Earth Syst. Sci., 23, 751–770, https://doi.org/10.5194/nhess-23-751-2023, https://doi.org/10.5194/nhess-23-751-2023, 2023
Short summary
Short summary
In Bangladesh, riverbank erosion occurs every year during the monsoon and affects thousands of households. Information on locations and extent of past erosion can help anticipate where erosion might occur in the upcoming monsoon season and to take preventive measures. In our study, we show how time series of radar satellite imagery can be used to retrieve information on past erosion events shortly after the monsoon season using a novel interactive online tool based on the Google Earth Engine.
Jiale Qian, Yunyan Du, Jiawei Yi, Fuyuan Liang, Nan Wang, Ting Ma, and Tao Pei
Nat. Hazards Earth Syst. Sci., 23, 317–328, https://doi.org/10.5194/nhess-23-317-2023, https://doi.org/10.5194/nhess-23-317-2023, 2023
Short summary
Short summary
Human activities across China show a similar trend in response to rains. However, urban resilience varies significantly by region. The northwestern arid region and the central underdeveloped areas are very fragile, and even low-intensity rains can trigger significant human activity anomalies. By contrast, even high-intensity rains might not affect residents in the southeast.
Orlando García-Feal, José González-Cao, Diego Fernández-Nóvoa, Gonzalo Astray Dopazo, and Moncho Gómez-Gesteira
Nat. Hazards Earth Syst. Sci., 22, 3859–3874, https://doi.org/10.5194/nhess-22-3859-2022, https://doi.org/10.5194/nhess-22-3859-2022, 2022
Short summary
Short summary
Extreme events have increased in the last few decades; having a good estimation of the outflow of a reservoir can be an advantage for water management or early warning systems. This study analyzes the efficiency of different machine learning techniques to predict reservoir outflow. The results obtained showed that the proposed models provided a good estimation of the outflow of the reservoirs, improving the results obtained with classical approaches.
Seok Bum Hong, Hong Sik Yun, Sang Guk Yum, Seung Yeop Ryu, In Seong Jeong, and Jisung Kim
Nat. Hazards Earth Syst. Sci., 22, 3435–3459, https://doi.org/10.5194/nhess-22-3435-2022, https://doi.org/10.5194/nhess-22-3435-2022, 2022
Short summary
Short summary
This study advances previous models through machine learning and multi-sensor-verified results. Using spatial and meteorological data from the study area (Suncheon–Wanju Highway in Gurye-gun), the amount and location of black ice were modelled based on system dynamics to predict black ice and then simulated with the geographic information system (m2). Based on the model results, multiple sensors were buried at four selected points in the study area, and the model was compared with sensor data.
Edward E. Salakpi, Peter D. Hurley, James M. Muthoka, Adam B. Barrett, Andrew Bowell, Seb Oliver, and Pedram Rowhani
Nat. Hazards Earth Syst. Sci., 22, 2703–2723, https://doi.org/10.5194/nhess-22-2703-2022, https://doi.org/10.5194/nhess-22-2703-2022, 2022
Short summary
Short summary
The devastating effects of recurring drought conditions are mostly felt by pastoralists that rely on grass and shrubs as fodder for their animals. Using historical information from precipitation, soil moisture, and vegetation health data, we developed a model that can forecast vegetation condition and the probability of drought occurrence up till a 10-week lead time with an accuracy of 74 %. Our model can be adopted by policymakers and relief agencies for drought early warning and early action.
Edward E. Salakpi, Peter D. Hurley, James M. Muthoka, Andrew Bowell, Seb Oliver, and Pedram Rowhani
Nat. Hazards Earth Syst. Sci., 22, 2725–2749, https://doi.org/10.5194/nhess-22-2725-2022, https://doi.org/10.5194/nhess-22-2725-2022, 2022
Short summary
Short summary
The impact of drought may vary in a given region depending on whether it is dominated by trees, grasslands, or croplands. The differences in impact can also be the agro-ecological zones within the region. This paper proposes a hierarchical Bayesian model (HBM) for forecasting vegetation condition in spatially diverse areas. Compared to a non-hierarchical model, the HBM proved to be a more natural method for forecasting drought in areas with different land covers and
agro-ecological zones.
Weijie Zou, Yi Zhou, Shixin Wang, Futao Wang, Litao Wang, Qing Zhao, Wenliang Liu, Jinfeng Zhu, Yibing Xiong, Zhenqing Wang, and Gang Qin
Nat. Hazards Earth Syst. Sci., 22, 2081–2097, https://doi.org/10.5194/nhess-22-2081-2022, https://doi.org/10.5194/nhess-22-2081-2022, 2022
Short summary
Short summary
Landslide dams are secondary disasters caused by landslides, which can cause great damage to mountains. We have proposed a procedure to calculate the key parameters of these dams that uses only a single remote-sensing image and a pre-landslide DEM combined with landslide theory. The core of this study is a modeling problem. We have found the bridge between the theory of landslide dams and the requirements of disaster relief.
C. Scott Watson, John R. Elliott, Susanna K. Ebmeier, María Antonieta Vásquez, Camilo Zapata, Santiago Bonilla-Bedoya, Paulina Cubillo, Diego Francisco Orbe, Marco Córdova, Jonathan Menoscal, and Elisa Sevilla
Nat. Hazards Earth Syst. Sci., 22, 1699–1721, https://doi.org/10.5194/nhess-22-1699-2022, https://doi.org/10.5194/nhess-22-1699-2022, 2022
Short summary
Short summary
We assess how greenspaces could guide risk-informed planning and reduce disaster risk for the urbanising city of Quito, Ecuador, which experiences earthquake, volcano, landslide, and flood hazards. We use satellite data to evaluate the use of greenspaces as safe spaces following an earthquake. We find disparities regarding access to and availability of greenspaces. The availability of greenspaces that could contribute to community resilience is high; however, many require official designation.
Seth Bryant, Heather McGrath, and Mathieu Boudreault
Nat. Hazards Earth Syst. Sci., 22, 1437–1450, https://doi.org/10.5194/nhess-22-1437-2022, https://doi.org/10.5194/nhess-22-1437-2022, 2022
Short summary
Short summary
The advent of new satellite technologies improves our ability to study floods. While the depth of water at flooded buildings is generally the most important variable for flood researchers, extracting this accurately from satellite data is challenging. The software tool presented here accomplishes this, and tests show the tool is more accurate than competing tools. This achievement unlocks more detailed studies of past floods and improves our ability to plan for and mitigate disasters.
Tadas Nikonovas, Allan Spessa, Stefan H. Doerr, Gareth D. Clay, and Symon Mezbahuddin
Nat. Hazards Earth Syst. Sci., 22, 303–322, https://doi.org/10.5194/nhess-22-303-2022, https://doi.org/10.5194/nhess-22-303-2022, 2022
Short summary
Short summary
Extreme fire episodes in Indonesia emit large amounts of greenhouse gasses and have negative effects on human health in the region. In this study we show that such burning events can be predicted several months in advance in large parts of Indonesia using existing seasonal climate forecasts and forest cover change datasets. A reliable early fire warning system would enable local agencies to prepare and mitigate the worst of the effects.
Yahong Liu and Jin Zhang
Nat. Hazards Earth Syst. Sci., 22, 227–244, https://doi.org/10.5194/nhess-22-227-2022, https://doi.org/10.5194/nhess-22-227-2022, 2022
Short summary
Short summary
Through a comprehensive analysis of the current remote sensing technology resources, this paper establishes the database to realize the unified management of heterogeneous sensor resources and proposes a capability evaluation method of remote sensing cooperative technology in geohazard emergencies, providing a decision-making basis for the establishment of remote sensing cooperative observations in geohazard emergencies.
Diego Guenzi, Danilo Godone, Paolo Allasia, Nunzio Luciano Fazio, Michele Perrotti, and Piernicola Lollino
Nat. Hazards Earth Syst. Sci., 22, 207–212, https://doi.org/10.5194/nhess-22-207-2022, https://doi.org/10.5194/nhess-22-207-2022, 2022
Short summary
Short summary
In the Apulia region (southeastern Italy) we are monitoring a soft-rock coastal cliff using webcams and strain sensors. In this urban and touristic area, coastal recession is extremely rapid and rockfalls are very frequent. In our work we are using low-cost and open-source hardware and software, trying to correlate both meteorological information with measures obtained from crack meters and webcams, aiming to recognize potential precursor signals that could be triggered by instability phenomena.
Natalie Brožová, Tommaso Baggio, Vincenzo D'Agostino, Yves Bühler, and Peter Bebi
Nat. Hazards Earth Syst. Sci., 21, 3539–3562, https://doi.org/10.5194/nhess-21-3539-2021, https://doi.org/10.5194/nhess-21-3539-2021, 2021
Short summary
Short summary
Surface roughness plays a great role in natural hazard processes but is not always well implemented in natural hazard modelling. The results of our study show how surface roughness can be useful in representing vegetation and ground structures, which are currently underrated. By including surface roughness in natural hazard modelling, we could better illustrate the processes and thus improve hazard mapping, which is crucial for infrastructure and settlement planning in mountainous areas.
Hugues Brenot, Nicolas Theys, Lieven Clarisse, Jeroen van Gent, Daniel R. Hurtmans, Sophie Vandenbussche, Nikolaos Papagiannopoulos, Lucia Mona, Timo Virtanen, Andreas Uppstu, Mikhail Sofiev, Luca Bugliaro, Margarita Vázquez-Navarro, Pascal Hedelt, Michelle Maree Parks, Sara Barsotti, Mauro Coltelli, William Moreland, Simona Scollo, Giuseppe Salerno, Delia Arnold-Arias, Marcus Hirtl, Tuomas Peltonen, Juhani Lahtinen, Klaus Sievers, Florian Lipok, Rolf Rüfenacht, Alexander Haefele, Maxime Hervo, Saskia Wagenaar, Wim Som de Cerff, Jos de Laat, Arnoud Apituley, Piet Stammes, Quentin Laffineur, Andy Delcloo, Robertson Lennart, Carl-Herbert Rokitansky, Arturo Vargas, Markus Kerschbaum, Christian Resch, Raimund Zopp, Matthieu Plu, Vincent-Henri Peuch, Michel Van Roozendael, and Gerhard Wotawa
Nat. Hazards Earth Syst. Sci., 21, 3367–3405, https://doi.org/10.5194/nhess-21-3367-2021, https://doi.org/10.5194/nhess-21-3367-2021, 2021
Short summary
Short summary
The purpose of the EUNADICS-AV (European Natural Airborne Disaster Information and Coordination System for Aviation) prototype early warning system (EWS) is to develop the combined use of harmonised data products from satellite, ground-based and in situ instruments to produce alerts of airborne hazards (volcanic, dust, smoke and radionuclide clouds), satisfying the requirement of aviation air traffic management (ATM) stakeholders (https://cordis.europa.eu/project/id/723986).
Johnny Douvinet, Anna Serra-Llobet, Esteban Bopp, and G. Mathias Kondolf
Nat. Hazards Earth Syst. Sci., 21, 2899–2920, https://doi.org/10.5194/nhess-21-2899-2021, https://doi.org/10.5194/nhess-21-2899-2021, 2021
Short summary
Short summary
This study proposes to combine results of research regarding the spatial inequalities due to the siren coverage, the political dilemma of siren activation, and the social problem of siren awareness and trust for people in France. Surveys were conducted using a range of complementary methods (GIS analysis, statistical analysis, questionnaires, interviews) through different scales. Results show that siren coverage in France is often determined by population density but not risks or disasters.
Fabio Brighenti, Francesco Carnemolla, Danilo Messina, and Giorgio De Guidi
Nat. Hazards Earth Syst. Sci., 21, 2881–2898, https://doi.org/10.5194/nhess-21-2881-2021, https://doi.org/10.5194/nhess-21-2881-2021, 2021
Short summary
Short summary
In this paper we propose a methodology to mitigate hazard in a natural environment in an urbanized context. The deformation of the ground is a precursor of paroxysms in mud volcanoes. Therefore, through the analysis of the deformation supported by a statistical approach, this methodology was tested to reduce the hazard around the mud volcano. In the future, the goal is that this dangerous area will become both a naturalistic heritage and a source of development for the community of the area.
Doris Hermle, Markus Keuschnig, Ingo Hartmeyer, Robert Delleske, and Michael Krautblatter
Nat. Hazards Earth Syst. Sci., 21, 2753–2772, https://doi.org/10.5194/nhess-21-2753-2021, https://doi.org/10.5194/nhess-21-2753-2021, 2021
Short summary
Short summary
Multispectral remote sensing imagery enables landslide detection and monitoring, but its applicability to time-critical early warning is rarely studied. We present a concept to operationalise its use for landslide early warning, aiming to extend lead time. We tested PlanetScope and unmanned aerial system images on a complex mass movement and compared processing times to historic benchmarks. Acquired data are within the forecasting window, indicating the feasibility for landslide early warning.
Michal Bíl, Pavel Raška, Lukáš Dolák, and Jan Kubeček
Nat. Hazards Earth Syst. Sci., 21, 2581–2596, https://doi.org/10.5194/nhess-21-2581-2021, https://doi.org/10.5194/nhess-21-2581-2021, 2021
Short summary
Short summary
The online landslide database CHILDA (Czech Historical Landslide Database) summarises information about landslides which occurred in the area of Czechia (the Czech Republic). The database is freely accessible via the https://childa.cz/ website. It includes 699 records (spanning the period of 1132–1989). Overall, 55 % of all recorded landslide events occurred only within 15 years of the extreme landslide incidence.
Anna Kruspe, Jens Kersten, and Friederike Klan
Nat. Hazards Earth Syst. Sci., 21, 1825–1845, https://doi.org/10.5194/nhess-21-1825-2021, https://doi.org/10.5194/nhess-21-1825-2021, 2021
Short summary
Short summary
Messages on social media can be an important source of information during crisis situations. This article reviews approaches for the reliable detection of informative messages in a flood of data. We demonstrate the varying goals of these approaches and present existing data sets. We then compare approaches based (1) on keyword and location filtering, (2) on crowdsourcing, and (3) on machine learning. We also point out challenges and suggest future research.
Enrique Guillermo Cordaro, Patricio Venegas-Aravena, and David Laroze
Nat. Hazards Earth Syst. Sci., 21, 1785–1806, https://doi.org/10.5194/nhess-21-1785-2021, https://doi.org/10.5194/nhess-21-1785-2021, 2021
Short summary
Short summary
We developed a methodology that generates free externally disturbed magnetic variations in ground magnetometers close to the Chilean convergent margin. Spectral analysis (~ mHz) and magnetic anomalies increased prior to large Chilean earthquakes (Maule 2010, Mw 8.8; Iquique 2014, Mw 8.2; Illapel 2015, Mw 8.3). These findings relate to microcracks within the lithosphere due to stress state changes. This physical evidence should be thought of as a last stage of the earthquake preparation process.
Corey M. Scheip and Karl W. Wegmann
Nat. Hazards Earth Syst. Sci., 21, 1495–1511, https://doi.org/10.5194/nhess-21-1495-2021, https://doi.org/10.5194/nhess-21-1495-2021, 2021
Short summary
Short summary
For many decades, natural disasters have been monitored by trained analysts using multiple satellite images to observe landscape change. This approach is incredibly useful, but our new tool, HazMapper, offers researchers and the scientifically curious public a web-accessible
cloud-based tool to perform similar analysis. We intend for the tool to both be used in scientific research and provide rapid response to global natural disasters like landslides, wildfires, and volcanic eruptions.
Matti Wiegmann, Jens Kersten, Hansi Senaratne, Martin Potthast, Friederike Klan, and Benno Stein
Nat. Hazards Earth Syst. Sci., 21, 1431–1444, https://doi.org/10.5194/nhess-21-1431-2021, https://doi.org/10.5194/nhess-21-1431-2021, 2021
Short summary
Short summary
In this paper, we study when social media is an adequate source to find metadata about incidents that cannot be acquired by traditional means. We identify six major use cases: impact assessment and verification of model predictions, narrative generation, recruiting citizen volunteers, supporting weakly institutionalized areas, narrowing surveillance areas, and reporting triggers for periodical surveillance.
Hui Liu, Ya Hao, Wenhao Zhang, Hanyue Zhang, Fei Gao, and Jinping Tong
Nat. Hazards Earth Syst. Sci., 21, 1179–1194, https://doi.org/10.5194/nhess-21-1179-2021, https://doi.org/10.5194/nhess-21-1179-2021, 2021
Short summary
Short summary
We trained a recurrent neural network model to classify microblogging posts related to urban waterlogging and establish an online monitoring system of urban waterlogging caused by flood disasters. We manually curated more than 4400 waterlogging posts to train the RNN model so that it can precisely identify waterlogging-related posts of Sina Weibo to timely determine urban waterlogging.
Roope Tervo, Ilona Láng, Alexander Jung, and Antti Mäkelä
Nat. Hazards Earth Syst. Sci., 21, 607–627, https://doi.org/10.5194/nhess-21-607-2021, https://doi.org/10.5194/nhess-21-607-2021, 2021
Short summary
Short summary
Predicting the number of power outages caused by extratropical storms is a key challenge for power grid operators. We introduce a novel method to predict the storm severity for the power grid employing ERA5 reanalysis data combined with a forest inventory. The storms are first identified from the data and then classified using several machine-learning methods. While there is plenty of room to improve, the results are already usable, with support vector classifier providing the best performance.
Michaela Wenner, Clément Hibert, Alec van Herwijnen, Lorenz Meier, and Fabian Walter
Nat. Hazards Earth Syst. Sci., 21, 339–361, https://doi.org/10.5194/nhess-21-339-2021, https://doi.org/10.5194/nhess-21-339-2021, 2021
Short summary
Short summary
Mass movements constitute a risk to property and human life. In this study we use machine learning to automatically detect and classify slope failure events using ground vibrations. We explore the influence of non-ideal though commonly encountered conditions: poor network coverage, small number of events, and low signal-to-noise ratios. Our approach enables us to detect the occurrence of rare events of high interest in a large data set of more than a million windowed seismic signals.
Luiz Felipe Galizia, Thomas Curt, Renaud Barbero, and Marcos Rodrigues
Nat. Hazards Earth Syst. Sci., 21, 73–86, https://doi.org/10.5194/nhess-21-73-2021, https://doi.org/10.5194/nhess-21-73-2021, 2021
Short summary
Short summary
This paper aims to provide a quantitative evaluation of three remotely sensed fire datasets which have recently emerged as an important resource to improve our understanding of fire regimes. Our findings suggest that remotely sensed fire datasets can be used to proxy variations in fire activity on monthly and annual timescales; however, caution is advised when drawing information from smaller fires (< 100 ha) across the Mediterranean region.
Philippe Weyrich, Anna Scolobig, Florian Walther, and Anthony Patt
Nat. Hazards Earth Syst. Sci., 20, 2811–2821, https://doi.org/10.5194/nhess-20-2811-2020, https://doi.org/10.5194/nhess-20-2811-2020, 2020
Patric Kellermann, Kai Schröter, Annegret H. Thieken, Sören-Nils Haubrock, and Heidi Kreibich
Nat. Hazards Earth Syst. Sci., 20, 2503–2519, https://doi.org/10.5194/nhess-20-2503-2020, https://doi.org/10.5194/nhess-20-2503-2020, 2020
Short summary
Short summary
The flood damage database HOWAS 21 contains object-specific flood damage data resulting from fluvial, pluvial and groundwater flooding. The datasets incorporate various variables of flood hazard, exposure, vulnerability and direct tangible damage at properties from several economic sectors. This paper presents HOWAS 21 and highlights exemplary analyses to demonstrate the use of HOWAS 21 flood damage data.
Giuseppe Esposito, Ivan Marchesini, Alessandro Cesare Mondini, Paola Reichenbach, Mauro Rossi, and Simone Sterlacchini
Nat. Hazards Earth Syst. Sci., 20, 2379–2395, https://doi.org/10.5194/nhess-20-2379-2020, https://doi.org/10.5194/nhess-20-2379-2020, 2020
Short summary
Short summary
In this article, we present an automatic processing chain aimed to support the detection of landslides that induce sharp land cover changes. The chain exploits free software and spaceborne SAR data, allowing the systematic monitoring of wide mountainous regions exposed to mass movements. In the test site, we verified a general accordance between the spatial distribution of seismically induced landslides and the detected land cover changes, demonstrating its potential use in emergency management.
Mohammad Malakootian and Majid Nozari
Nat. Hazards Earth Syst. Sci., 20, 2351–2363, https://doi.org/10.5194/nhess-20-2351-2020, https://doi.org/10.5194/nhess-20-2351-2020, 2020
Short summary
Short summary
The present study estimated the Kerman–Baghin aquifer vulnerability using DRASTIC and composite DRASTIC (CDRASTIC) indices with the aid of geographic information system (GIS) techniques. The aquifer vulnerability maps indicated very similar results, identifying the north-west parts of the aquifer as areas with high to very high vulnerability. According to the results, parts of the studied aquifer have a high vulnerability and require protective measures.
Diana Contreras, Alondra Chamorro, and Sean Wilkinson
Nat. Hazards Earth Syst. Sci., 20, 1663–1687, https://doi.org/10.5194/nhess-20-1663-2020, https://doi.org/10.5194/nhess-20-1663-2020, 2020
Short summary
Short summary
The socio-economic condition of the population determines their vulnerability to earthquakes, tsunamis, volcanic eruptions, landslides, soil erosion and land degradation. This condition is estimated mainly from population censuses. The lack to access to basic services, proximity to hazard zones, poverty and population density highly influence the vulnerability of communities. Mapping the location of this vulnerable population makes it possible to prevent and mitigate their risk.
Simona Colombelli, Francesco Carotenuto, Luca Elia, and Aldo Zollo
Nat. Hazards Earth Syst. Sci., 20, 921–931, https://doi.org/10.5194/nhess-20-921-2020, https://doi.org/10.5194/nhess-20-921-2020, 2020
Short summary
Short summary
We developed a mobile app for Android devices which receives the alerts generated by a network-based early warning system, predicts the expected ground-shaking intensity and the available lead time at the user position, and provides customized messages to inform the user about the proper reaction to the alert. The app represents a powerful tool for informing in real time a wide audience of end users and stakeholders about the potential damaging shaking in the occurrence of an earthquake.
Richard Styron, Julio García-Pelaez, and Marco Pagani
Nat. Hazards Earth Syst. Sci., 20, 831–857, https://doi.org/10.5194/nhess-20-831-2020, https://doi.org/10.5194/nhess-20-831-2020, 2020
Short summary
Short summary
The Caribbean and Central American region is both tectonically active and densely populated, leading to a large population that is exposed to earthquake hazards. Until now, no comprehensive fault data covering the region have been available. We present a new public fault database for Central America and the Caribbean that synthesizes published studies with new mapping from remote sensing to provide fault sources for the CCARA seismic hazard and risk analysis project and to aid future research.
María del Pilar Jiménez-Donaire, Ana Tarquis, and Juan Vicente Giráldez
Nat. Hazards Earth Syst. Sci., 20, 21–33, https://doi.org/10.5194/nhess-20-21-2020, https://doi.org/10.5194/nhess-20-21-2020, 2020
Short summary
Short summary
A new combined drought indicator (CDI) is proposed that integrates rainfall, soil moisture and vegetation dynamics. The performance of this indicator was evaluated against crop damage data from agricultural insurance schemes in five different areas in SW Spain. Results show that this indicator was able to predict important droughts in 2004–2005 and 2011–2012, marked by crop damage of between 70 % and 95 % of the total insured area. This opens important applications for improving insurance schemes.
Quancai Xie, Qiang Ma, Jingfa Zhang, and Haiying Yu
Nat. Hazards Earth Syst. Sci., 19, 2827–2839, https://doi.org/10.5194/nhess-19-2827-2019, https://doi.org/10.5194/nhess-19-2827-2019, 2019
Short summary
Short summary
This paper evaluates a new method for modeling the site amplification factor. Through implementing this method and making simulations for different cases, we find that this method shows better performance than the previous method and JMA report. We better understand the advantages and disadvantages of this method, although there are some problems that need to be considered carefully and solved; it shows good potential to be used in future earthquake early warning systems.
David A. Bonneau, D. Jean Hutchinson, Paul-Mark DiFrancesco, Melanie Coombs, and Zac Sala
Nat. Hazards Earth Syst. Sci., 19, 2745–2765, https://doi.org/10.5194/nhess-19-2745-2019, https://doi.org/10.5194/nhess-19-2745-2019, 2019
Short summary
Short summary
In mountainous regions around the world rockfalls pose a hazard to infrastructure and society. To aid in our understanding and management of these complex hazards, an inventory can be compiled. Three-dimensional remote sensing data can be used to locate the source zones of these events and generate models of areas which detached. We address the way in which the shape of a rockfall object can be measured. The shape of a rockfall has implications for forward modelling of potential runout zones.
Kwonmin Lee, Hye-Sil Kim, and Yong-Sang Choi
Nat. Hazards Earth Syst. Sci., 19, 2241–2248, https://doi.org/10.5194/nhess-19-2241-2019, https://doi.org/10.5194/nhess-19-2241-2019, 2019
Short summary
Short summary
This study examined the advances in the predictability of thunderstorms using geostationary satellite imageries. Our present results show that by using the latest geostationary satellite data (with a resolution of 2 km and 10 min), thunderstorms can be predicted 90–180 min ahead of their mature state. These data can capture the rapidly growing cloud tops before the cloud moisture falls as precipitation and enable prompt preparation and the mitigation of hazards.
Qingyun Zhang, Yongsheng Li, Jingfa Zhang, and Yi Luo
Nat. Hazards Earth Syst. Sci., 19, 2229–2240, https://doi.org/10.5194/nhess-19-2229-2019, https://doi.org/10.5194/nhess-19-2229-2019, 2019
Short summary
Short summary
Before the opening of the railway, the deformation of the Qinghai–Tibet Railway was very small and considered stable. After opening, the overall stability of the railway section was good. The main deformation areas are concentrated in the areas where railway lines turn and geological disasters are concentrated. In order to ensure the safety of railway operation, it is necessary to carry out long-term time series observation along the Qinghai–Tibet Railway.
Xiao Huang, Cuizhen Wang, and Junyu Lu
Nat. Hazards Earth Syst. Sci., 19, 2141–2155, https://doi.org/10.5194/nhess-19-2141-2019, https://doi.org/10.5194/nhess-19-2141-2019, 2019
Short summary
Short summary
This study examined the spatiotemporal dynamics of nighttime satellite-derived human settlement in response to different levels of hurricane proneness in a period from 1992 to 2013. It confirms the
Snow Belt-to-Sun BeltUS population shift trend. The results also suggest that hurricane-exposed human settlement has grown in extent and area, as more hurricane exposure has experienced a larger increase rate in settlement intensity.
Maja Kucharczyk and Chris H. Hugenholtz
Nat. Hazards Earth Syst. Sci., 19, 2039–2051, https://doi.org/10.5194/nhess-19-2039-2019, https://doi.org/10.5194/nhess-19-2039-2019, 2019
Short summary
Short summary
We performed pre-disaster 3-D mapping with a drone in downtown Victoria, BC, Canada. This was the first drone mapping mission over a Canadian city approved by Canada’s aviation authority. We were legally constrained to using a specific drone. The goal was to assess the quality of the 3-D map. Results indicate that the spatial accuracies achieved with this drone would allow for sub-meter building collapse detection, but the non-tilting camera was insufficient for mapping buildings in 3-D.
Reza Hassanzadeh, Mehdi Honarmand, Mahdieh Hossienjani Zadeh, and Farzin Naseri
Nat. Hazards Earth Syst. Sci., 19, 1989–2009, https://doi.org/10.5194/nhess-19-1989-2019, https://doi.org/10.5194/nhess-19-1989-2019, 2019
Short summary
Short summary
This paper proposes a new model for evaluating local seismic amplification susceptibility by considering direct characteristics of influencing criteria and dealing with uncertainty of modelling through production of fuzzy membership functions and GIS. This model helps planners and decision makers easily produce local seismic amplification susceptibility to be incorporated in designing development plans of urban areas and to evaluate safety measures of existing infrastructure.
Cited articles
Achanta, R., Shaji, A., Smith, K., Lucchi, A., Fua, P., and Süsstrunk, S.:
Slic superpixels, Tech. rep., 2010. a
Ahmed, M. T., Dailey, M. N., Landabaso, J. L., and Herrero, N.: Robust Key
Frame Extraction for 3D Reconstruction from Video Streams, in: VISAPP (1),
edited by: Richard, P. and Braz, J., 231–236, INSTICC Press,
http://dblp.uni-trier.de/db/conf/visapp/visapp2010-1.html#AhmedDLH10, 2010. a
Clift, L. G. and Clark, A. F.: Video frame extraction for 3D reconstruction,
in: 2016 8th Computer Science and Electronic Engineering (CEEC), 152–157, https://doi.org/10.1109/CEEC.2016.7835905, 2016. a, b
CloudCompare: CloudCompare 3D point cloud and mesh processing software Open
Source Project, http://www.cloudcompare.org/, 2017. (last access: 29 May 2018) a
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,
https://doi.org/10.1016/j.isprsjprs.2013.06.011,
http://www.sciencedirect.com/science/article/pii/S0924271613001627, 2013. a, b
3DFlow: 3DF Zephyr, Version 3.0, computersoftware, available at:
http://www.3dflow.net/, 2017. a
3D Flow: 3DF Zephyr 3.0 user manual, available at: http://www.3dflow.net/technology/documents/3df-zephyr-tutorials/,
computersoftwaremanual, 2017. a
Eugster, H. and Nebiker, S.: Geo-registration of video sequences captured from
Mini UAVs: Approaches and accuracy assessment, in: The 5th International
Symposium on Mobile Mapping Technology, Padua, Italy. Retrieved March,
vol. 12, 2012, 2007. a
FSD: Drones in Humanitarian Action. A guide to the use of airbirne systems in
humanitarian crises, Tech. rep., Swiss Foundation for Mine Action (FSD),
Geneva, http://drones.fsd.ch/, 2016. (last access: 29 May 2018) a
Gerke, M. and Kerle, N.: Automatic structural seismic damage assessment with
airborne oblique Pictometry© imagery, Photogr. Eng. Remote Sens., 77, 885–898, 2011. a
Girardeau-Montaut, D.: Completeness/Coverage of point cloud,
http://www.cloudcompare.org/forum/viewtopic.php?t=1433#p5553,
2017. (last access: 29 May 2018) a
Jarzabek-Rychard, M. and Karpina, M.: Quality analysis on 3D building models
reconstructed from UAV imagery, ISPRS - International Archives of the
Photogrammetry, Remote Sensing and Spatial Information Sciences, XLI-B1,
1121–1126, https://doi.org/10.5194/isprs-archives-XLI-B1-1121-2016, 2016. a
Kersten, T. P. and Lindstaedt, M.: Automatic 3D object reconstruction from
multiple images for architectural, cultural heritage and archaeological
applications using open-source software and web services,
Photogrammetrie-Fernerkundung-Geoinformation, 2012, 727–740, 2012. a
Khoshelham, K., Elberink, S. O., and Xu, S.: Segment-based classification of
damaged building roofs in aerial laser scanning data, IEEE Geosci. Remote Sens. Lett., 10, 1258–1262, 2013. a
Krizhevsky, A., Sutskever, I., and Hinton, G. E.: ImageNet Classification with
Deep Convolutional Neural Networks, in: Advances in Neural Information
Processing Systems 25, edited by: Pereira, F., Burges, C. J. C., Bottou, L.,
and Weinberger, K. Q., 1097–1105, Curran Associates, Inc.,
http://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks.pdf,
2012. (last access: 29 May 2018) a
Nex, F. and Remondino, F.: UAV for 3D mapping applications: a review, Appl. Geomat., 6, 1–15, https://doi.org/10.1007/s12518-013-0120-x, 2014. a
Ogawa, N. and Yamazaki, F.: Photo-interpretation of building damage due to
earthquakes using aerial photographs, in: Proceedings of the 12th World
Conference on Earthquake Engineering, 1906, 2000. a
Oude Elberink, S. and Vosselman, G.: Quality analysis on 3D building
models reconstructed from airborne laser scanning data, ISPRS Journal of
Photogrammetry and Remote Sensing, 66, 157–165,
https://doi.org/10.1016/j.isprsjprs.2010.09.009, 2011. a
Pix4D: Pix4D Mapper: Drone Mapping Software for Desktop + Cloud + Mobile,
https://pix4d.com/, version 3.1.18, 2017. a
Saito, K., Spence, R., Booth, E., Madabhushi, M., Eguchi, R., and Gill, S.:
Damage assessment of Port au Prince using Pictometry, in: 8th International
Conference on Remote Sensing for Disaster Response, Vol. 30, p. 2010, Tokyo,
2010. a
Samadzadegan, F. and Rastiveisi, H.: Automatic detection and classification of
damaged buildings, using high resolution satellite imagery and vector data,
The International Archives of the Photogrammetry, Remote Sensing and Spatial
Information Sciences, 37, 415–420, 2008. a
Singh, S. P. Jain, K., and Ravibabu Mandla, V.:
3D scene reconstruction from video camera for virtual 3d city modeling,
Am. J. Eng. Res., 3, 140–148, 2014. a
Soudarissanane, S., Lindenbergh, R., and Gorte, B.: Reducing the error in
terrestrial laser scanning by optimizing the measurement set-up, in: XXI
ISPRS Congress, Commission I-VIII, 3–11 July 2008, Beijing, China,
International Society for Photogrammetry and Remote Sensing, 2008. a
Tu, J., Sui, H., Feng, W., and Song, Z.: Automatic Building Damage Detection
Method Using High-Resolution Remote Sensing Images and 3D GIS Model., ISPRS
Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences,
43–50, 2016. a
Turner, D., Lucieer, A., and Wallace, L.: Direct georeferencing of
ultrahigh-resolution UAV imagery, IEEE Transactions on Geoscience and Remote
Sensing, 52, 2738–2745, 2014. a
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, https://doi.org/10.1016/j.isprsjprs.2015.03.016, 2015. a, b, c
Vetrivel, A., Duarte, D., Nex, F., Gerke, M., Kerle, N., and Vosselman, G.:
Potential of multi-temporal oblique airborne imagery for structural damage
assessment, ISPRS Annals of Photogrammetry, Remote Sensing and Spatial
Information Sciences, III-3, 355–362,
https://doi.org/10.5194/isprs-annals-III-3-355-2016, 2016a. a
Vetrivel, A., Gerke, M., Kerle, N., and Vosselman, G.: Identification of
structurally damaged areas in airborne oblique images using a
Visual-Bag-of-Words approach, Remote Sens., https://doi.org/10.3390/rs8030231,
2016b. a
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, 2017.
a, b, c, d, e, f
Weinmann, M., Jutzi, B., Hinz, S., and Mallet, C.: Semantic point cloud
interpretation based on optimal neighborhoods, relevant features and
efficient classifiers, ISPRS Journal of Photogrammetry and Remote Sensing,
105, 286–304, 2015. a
Xu, Z., Wu, T. H., Shen, Y., and Wu, L.: Three dimentional reconstruction of
large cultural heritage objects based on UAV video and TLS data, ISPRS -
International Archives of the Photogrammetry, Remote Sensing and Spatial
Information Sciences, XLI-B5, 985–988,
https://doi.org/10.5194/isprs-archives-XLI-B5-985-2016, 2016. a, b, c
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.
Aerial multi-perspective images can be used for the effective assessment of post-disaster...
Altmetrics
Final-revised paper
Preprint