Articles | Volume 22, issue 2
https://doi.org/10.5194/nhess-22-481-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-22-481-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
16 Feb 2022
Research article |
| 16 Feb 2022
| 16 Feb 2022
Automated determination of landslide locations after large trigger events: advantages and disadvantages compared to manual mapping
David G. Milledge
CORRESPONDING AUTHOR
School of Engineering, Newcastle University, Newcastle upon Tyne, UK
Dino G. Bellugi
Department of Geography, University of California, Berkeley, Berkeley, CA, USA
Jack Watt
Institute of Hazard, Risk and Resilience, Durham University, Durham, UK
Department of Geography, Durham University, Durham, UK
Alexander L. Densmore
Institute of Hazard, Risk and Resilience, Durham University, Durham, UK
Department of Geography, Durham University, Durham, UK
Related authors
Katy Burrows, David Milledge, Richard J. Walters, and Dino Bellugi
Nat. Hazards Earth Syst. Sci., 21, 2993–3014, https://doi.org/10.5194/nhess-21-2993-2021, https://doi.org/10.5194/nhess-21-2993-2021, 2021
Short summary
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When cloud cover obscures optical satellite imagery, there are two options remaining for generating information on earthquake-triggered landslide locations: (1) models which predict landslide locations based on, e.g., slope and ground shaking data and (2) satellite radar data, which penetrates cloud cover and is sensitive to landslides. Here we show that the two approaches can be combined to give a more consistent and more accurate model of landslide locations after an earthquake.
Katy Burrows, Richard J. Walters, David Milledge, and Alexander L. Densmore
Nat. Hazards Earth Syst. Sci., 20, 3197–3214, https://doi.org/10.5194/nhess-20-3197-2020, https://doi.org/10.5194/nhess-20-3197-2020, 2020
Short summary
Short summary
Satellite radar could provide information on landslide locations within days of an earthquake or rainfall event anywhere on Earth, but until now there has been a lack of systematic testing of possible radar methods, and most methods have been demonstrated using a single case study event and data from a single satellite sensor. Here we test five methods on four events, demonstrating their wide applicability and making recommendations on when different methods should be applied in the future.
David G. Milledge, Alexander L. Densmore, Dino Bellugi, Nick J. Rosser, Jack Watt, Gen Li, and Katie J. Oven
Nat. Hazards Earth Syst. Sci., 19, 837–856, https://doi.org/10.5194/nhess-19-837-2019, https://doi.org/10.5194/nhess-19-837-2019, 2019
Short summary
Short summary
Mitigating landslide risk requires information on landslide hazards on a suitable scale to inform decisions. We develop simple rules to identify landslide hazards and the probability of being hit by a landslide, then test their performance using six existing landslide inventories from recent earthquakes. We find that the best rules are "minimize your maximum look angle to the skyline" and "avoid steep (> 10˚) channels with many steep (> 40˚) areas that are upslope".
Jack G. Williams, Nick J. Rosser, Mark E. Kincey, Jessica Benjamin, Katie J. Oven, Alexander L. Densmore, David G. Milledge, Tom R. Robinson, Colm A. Jordan, and Tom A. Dijkstra
Nat. Hazards Earth Syst. Sci., 18, 185–205, https://doi.org/10.5194/nhess-18-185-2018, https://doi.org/10.5194/nhess-18-185-2018, 2018
Short summary
Short summary
There is currently no protocol for rapid humanitarian-facing landslide assessment and no published recognition of what is possible and useful to compile immediately after a triggering event. Drawing on the 2015 Gorkha earthquake (Nepal), we consider how quickly a landslide assessment based upon manual satellite-based emergency mapping (SEM) can be realistically achieved and review the decisions taken by analysts to ascertain the timeliness and type of useful information that can be generated.
C. Hahn, V. Prasuhn, C. Stamm, D. G. Milledge, and R. Schulin
Hydrol. Earth Syst. Sci., 18, 2975–2991, https://doi.org/10.5194/hess-18-2975-2014, https://doi.org/10.5194/hess-18-2975-2014, 2014
Alex Dunant, Tom R. Robinson, Alexander Logan Densmore, Nick J. Rosser, Ragindra Man Rajbhandari, Mark Kincey, Sihan Li, Prem Raj Awasthi, Max Van Wyk de Vries, Ramesh Guragain, Erin Harvey, and Simon Dadson
EGUsphere, https://doi.org/10.5194/egusphere-2024-1374, https://doi.org/10.5194/egusphere-2024-1374, 2024
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Our study introduces a new method using hypergraph theory to assess risks from interconnected natural hazards. Traditional models often overlook how these hazards can interact and worsen each other's effects. By applying our method to the 2015 Nepal earthquake, we successfully demonstrated its ability to predict broad damage patterns, despite slightly overestimating impacts. Being able to anticipate the effects of complex, interconnected hazards is critical for disaster preparedness.
Maximillian Van Wyk de Vries, Sihan Li, Katherine Arrell, Jeevan Baniya, Dipak Basnet, Gopi K. Basyal, Nyima Dorjee Bhotia, Alexander L. Densmore, Tek Bahadur Dong, Alexandre Dunant, Erin L. Harvey, Ganesh K. Jimee, Mark E. Kincey, Katie Oven, Sarmila Paudyal, Dammar Singh Pujara, Anuradha Puri, Ram Shrestha, Nick J. Rosser, and Simon J. Dadson
EGUsphere, https://doi.org/10.5194/egusphere-2024-397, https://doi.org/10.5194/egusphere-2024-397, 2024
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This study focuses on understanding soil moisture, a key factor for evaluating hillslope stability and landsliding. In Nepal, where landslides are common, we used a computer model to better understand how rapidly soil dries out after the monsoon season. We calibrated the model using field data and found that, by adjusting soil properties, we could predict moisture levels more accurately. This helps understand where landslides might occur, even where direct measurements are not possible.
Maximillian Van Wyk de Vries, Alexandre Dunant, Amy L. Johnson, Erin L. Harvey, Sihan Li, Katherine Arrell, Jeevan Baniya, Dipak Basnet, Gopi K. Basyal, Nyima Dorjee Bhotia, Simon J. Dadson, Alexander L. Densmore, Tek Bahadur Dong, Mark E. Kincey, Katie Oven, Anuradha Puri, and Nick J. Rosser
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-40, https://doi.org/10.5194/nhess-2024-40, 2024
Preprint under review for NHESS
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Mapping exposure to landslides is necessary to mitigate risk and reduce vulnerability. In this study, we show that there is a poor correlation between building damage and deaths from landslides- such that the deadliest landslides do not always destroy the most buildings and vice versa. This has important implications for our management on landslide risk.
Katy Burrows, David Milledge, Richard J. Walters, and Dino Bellugi
Nat. Hazards Earth Syst. Sci., 21, 2993–3014, https://doi.org/10.5194/nhess-21-2993-2021, https://doi.org/10.5194/nhess-21-2993-2021, 2021
Short summary
Short summary
When cloud cover obscures optical satellite imagery, there are two options remaining for generating information on earthquake-triggered landslide locations: (1) models which predict landslide locations based on, e.g., slope and ground shaking data and (2) satellite radar data, which penetrates cloud cover and is sensitive to landslides. Here we show that the two approaches can be combined to give a more consistent and more accurate model of landslide locations after an earthquake.
Thomas Croissant, Robert G. Hilton, Gen K. Li, Jamie Howarth, Jin Wang, Erin L. Harvey, Philippe Steer, and Alexander L. Densmore
Earth Surf. Dynam., 9, 823–844, https://doi.org/10.5194/esurf-9-823-2021, https://doi.org/10.5194/esurf-9-823-2021, 2021
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In mountain ranges, earthquake-derived landslides mobilize large amounts of organic carbon (OC) by eroding soil from hillslopes. We propose a model to explore the role of different parameters in the post-seismic redistribution of soil OC controlled by fluvial export and heterotrophic respiration. Applied to the Southern Alps, our results suggest that efficient OC fluvial export during the first decade after an earthquake promotes carbon sequestration.
Katy Burrows, Richard J. Walters, David Milledge, and Alexander L. Densmore
Nat. Hazards Earth Syst. Sci., 20, 3197–3214, https://doi.org/10.5194/nhess-20-3197-2020, https://doi.org/10.5194/nhess-20-3197-2020, 2020
Short summary
Short summary
Satellite radar could provide information on landslide locations within days of an earthquake or rainfall event anywhere on Earth, but until now there has been a lack of systematic testing of possible radar methods, and most methods have been demonstrated using a single case study event and data from a single satellite sensor. Here we test five methods on four events, demonstrating their wide applicability and making recommendations on when different methods should be applied in the future.
David G. Milledge, Alexander L. Densmore, Dino Bellugi, Nick J. Rosser, Jack Watt, Gen Li, and Katie J. Oven
Nat. Hazards Earth Syst. Sci., 19, 837–856, https://doi.org/10.5194/nhess-19-837-2019, https://doi.org/10.5194/nhess-19-837-2019, 2019
Short summary
Short summary
Mitigating landslide risk requires information on landslide hazards on a suitable scale to inform decisions. We develop simple rules to identify landslide hazards and the probability of being hit by a landslide, then test their performance using six existing landslide inventories from recent earthquakes. We find that the best rules are "minimize your maximum look angle to the skyline" and "avoid steep (> 10˚) channels with many steep (> 40˚) areas that are upslope".
Jack G. Williams, Nick J. Rosser, Mark E. Kincey, Jessica Benjamin, Katie J. Oven, Alexander L. Densmore, David G. Milledge, Tom R. Robinson, Colm A. Jordan, and Tom A. Dijkstra
Nat. Hazards Earth Syst. Sci., 18, 185–205, https://doi.org/10.5194/nhess-18-185-2018, https://doi.org/10.5194/nhess-18-185-2018, 2018
Short summary
Short summary
There is currently no protocol for rapid humanitarian-facing landslide assessment and no published recognition of what is possible and useful to compile immediately after a triggering event. Drawing on the 2015 Gorkha earthquake (Nepal), we consider how quickly a landslide assessment based upon manual satellite-based emergency mapping (SEM) can be realistically achieved and review the decisions taken by analysts to ascertain the timeliness and type of useful information that can be generated.
Tom R. Robinson, Nicholas J. Rosser, Alexander L. Densmore, Jack G. Williams, Mark E. Kincey, Jessica Benjamin, and Heather J. A. Bell
Nat. Hazards Earth Syst. Sci., 17, 1521–1540, https://doi.org/10.5194/nhess-17-1521-2017, https://doi.org/10.5194/nhess-17-1521-2017, 2017
Short summary
Short summary
Current methods to identify landslides after an earthquake are too slow to effectively inform emergency response operations. This study presents an empirical approach for modelling the spatial pattern and landslide density within hours to days of the earthquake. The approach uses small initial samples of landslides to identify locations where as yet unidentified landslides may have occurred. The model requires just 200 initial landslides, provided they have sufficiently wide spatial coverage.
C. Hahn, V. Prasuhn, C. Stamm, D. G. Milledge, and R. Schulin
Hydrol. Earth Syst. Sci., 18, 2975–2991, https://doi.org/10.5194/hess-18-2975-2014, https://doi.org/10.5194/hess-18-2975-2014, 2014
Related subject area
Landslides and Debris Flows Hazards
Analysis of three-dimensional slope stability combined with rainfall and earthquake
Assessing landslide damming susceptibility in Central Asia
Assessing locations susceptible to shallow landslide initiation during prolonged intense rainfall in the Lares, Utuado, and Naranjito municipalities of Puerto Rico
Evaluation of debris-flow building damage forecasts
Characteristics of debris-flow-prone watersheds and debris-flow-triggering rainstorms following the Tadpole Fire, New Mexico, USA
Morphological characteristics and conditions of drainage basins contributing to the formation of debris flow fans: an examination of regions with different rock strength using decision tree analysis
Comparison of debris flow observations, including fine-sediment grain size and composition and runout model results, at Illgraben, Swiss Alps
Simulation analysis of 3D stability of a landslide with a locking segment: a case study of the Tizicao landslide in Maoxian County, southwest China
Space–time landslide hazard modeling via Ensemble Neural Networks
Optimization strategy for flexible barrier structures: investigation and back analysis of a rockfall disaster case in southwestern China
Numerical-model-derived intensity–duration thresholds for early warning of rainfall-induced debris flows in a Himalayan catchment
Slope Unit Maker (SUMak): an efficient and parameter-free algorithm for delineating slope units to improve landslide modeling
Probabilistic Hydrological Estimation of LandSlides (PHELS): global ensemble landslide hazard modelling
A new analytical method for stability analysis of rock blocks with basal erosion in sub-horizontal strata by considering the eccentricity effect
Rockfall monitoring with a Doppler radar on an active rockslide complex in Brienz/Brinzauls (Switzerland)
Landslide initiation thresholds in data-sparse regions: application to landslide early warning criteria in Sitka, Alaska, USA
Lessons learnt from a rockfall time series analysis: data collection, statistical analysis, and applications
Evaluating Post-Wildfire Debris Flow Rainfall Thresholds and Volume Models at the 2020 Grizzly Creek Fire in Glenwood Canyon, Colorado, USA
The concept of event-size-dependent exhaustion and its application to paraglacial rockslides
Coastal earthquake-induced landslide susceptibility during the 2016 Mw 7.8 Kaikōura earthquake, New Zealand
Addressing Class Imbalance in Soil Movement Predictions
Characteristics of debris flows recorded in the Shenmu area of central Taiwan between 2004 and 2021
Semi-automatic mapping of shallow landslides using free Sentinel-2 images and Google Earth Engine
The role of thermokarst evolution in debris flow initiation (Hüttekar Rock Glacier, Austrian Alps)
Accounting for the effect of forest and fragmentation in probabilistic rockfall hazard
Comprehensive landslide susceptibility map of Central Asia
The influence of large woody debris on post-wildfire debris flow sediment storage
Assessing the impact of climate change to landslides using public data, a case study from Vejle, Denmark
Statistical modeling of sediment supply in torrent catchments of the northern French Alps
A data-driven evaluation of post-fire landslide susceptibility
Deciphering seasonal effects of triggering and preparatory precipitation for improved shallow landslide prediction using generalized additive mixed models
Brief communication: The northwest Himalaya towns slipping towards potential disaster
Dynamic response and breakage of trees subject to a landslide-induced air blast
Debris-flow surges of a very active alpine torrent: a field database
Rainfall thresholds estimation for shallow landslides in Peru from gridded daily data
Instantaneous limit equilibrium back analyses of major rockslides triggered during the 2016–2017 central Italy seismic sequence
Deadly disasters in southeastern South America: flash floods and landslides of February 2022 in Petrópolis, Rio de Janeiro
Multi-event assessment of typhoon-triggered landslide susceptibility in the Philippines
Antecedent rainfall as a critical factor for the triggering of debris flows in arid regions
Sensitivity analysis of a built environment exposed to the synthetic monophasic viscous debris flow impacts with 3-D numerical simulations
Characteristics and causes of natural and human-induced landslides in a tropical mountainous region: the rift flank west of Lake Kivu (Democratic Republic of the Congo)
Spatio-temporal analysis of slope-type debris flow activity in Horlachtal, Austria, based on orthophotos and lidar data since 1947
Assessing the relationship between weather conditions and rockfall using terrestrial laser scanning to improve risk management
Using principal component analysis to incorporate multi-layer soil moisture information in hydrometeorological thresholds for landslide prediction: an investigation based on ERA5-Land reanalysis data
Assessing uncertainties in landslide susceptibility predictions in a changing environment (Styrian Basin, Austria)
Brief communication: An autonomous UAV for catchment-wide monitoring of a debris flow torrent
How volcanic stratigraphy constrains headscarp collapse scenarios: the Samperre cliff case study (Martinique island, Lesser Antilles)
Landslide susceptibility assessment in the rocky coast subsystem of Essaouira, Morocco
Landsifier v1.0: a Python library to estimate likely triggers of mapped landslides
Timing landslide and flash flood events from SAR satellite: a regionally applicable methodology illustrated in African cloud-covered tropical environments
Jiao Wang, Zhangxing Wang, Guanhua Sun, and Hongming Luo
Nat. Hazards Earth Syst. Sci., 24, 1741–1756, https://doi.org/10.5194/nhess-24-1741-2024, https://doi.org/10.5194/nhess-24-1741-2024, 2024
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With a simplified formula linking rainfall and groundwater level, the rise of the phreatic surface within the slope can be obtained. Then, a global analysis method that considers both seepage and seismic forces is proposed to determine the safety factor of slopes subjected to the combined effect of rainfall and earthquakes. By taking a slope in the Three Gorges Reservoir area as an example, the safety evolution of the slope combined with both rainfall and earthquake is also examined.
Carlo Tacconi Stefanelli, William Frodella, Francesco Caleca, Zhanar Raimbekova, Ruslan Umaraliev, and Veronica Tofani
Nat. Hazards Earth Syst. Sci., 24, 1697–1720, https://doi.org/10.5194/nhess-24-1697-2024, https://doi.org/10.5194/nhess-24-1697-2024, 2024
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Central Asia regions are marked by active tectonics, high mountains with glaciers, and strong rainfall. These predisposing factors make large landslides a serious threat in the area and a source of possible damming scenarios, which endanger the population. To prevent this, a semi-automated geographic information system (GIS-)based mapping method, centered on a bivariate correlation of morphometric parameters, was applied to give preliminary information on damming susceptibility in Central Asia.
Rex L. Baum, Dianne L. Brien, Mark E. Reid, William H. Schulz, and Matthew J. Tello
Nat. Hazards Earth Syst. Sci., 24, 1579–1605, https://doi.org/10.5194/nhess-24-1579-2024, https://doi.org/10.5194/nhess-24-1579-2024, 2024
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We mapped potential for heavy rainfall to cause landslides in part of the central mountains of Puerto Rico using new tools for estimating soil depth and quasi-3D slope stability. Potential ground-failure locations correlate well with the spatial density of landslides from Hurricane Maria. The smooth boundaries of the very high and high ground-failure susceptibility zones enclose 75 % and 90 %, respectively, of observed landslides. The maps can help mitigate ground-failure hazards.
Katherine R. Barnhart, Christopher R. Miller, Francis K. Rengers, and Jason W. Kean
Nat. Hazards Earth Syst. Sci., 24, 1459–1483, https://doi.org/10.5194/nhess-24-1459-2024, https://doi.org/10.5194/nhess-24-1459-2024, 2024
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Debris flows are a type of fast-moving landslide that start from shallow landslides or during intense rain. Infrastructure located downstream of watersheds susceptible to debris flows may be damaged should a debris flow reach them. We present and evaluate an approach to forecast building damage caused by debris flows. We test three alternative models for simulating the motion of debris flows and find that only one can forecast the correct number and spatial pattern of damaged buildings.
Luke A. McGuire, Francis K. Rengers, Ann M. Youberg, Alexander N. Gorr, Olivia J. Hoch, Rebecca Beers, and Ryan Porter
Nat. Hazards Earth Syst. Sci., 24, 1357–1379, https://doi.org/10.5194/nhess-24-1357-2024, https://doi.org/10.5194/nhess-24-1357-2024, 2024
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Runoff and erosion increase after fire, leading to a greater likelihood of floods and debris flows. We monitored debris flow activity following a fire in western New Mexico, USA, and observed 16 debris flows over a <2-year monitoring period. Rainstorms with recurrence intervals of approximately 1 year were sufficient to initiate debris flows. All debris flows initiated during the first several months following the fire, indicating a rapid decrease in debris flow susceptibility over time.
Ken'ichi Koshimizu, Satoshi Ishimaru, Fumitoshi Imaizumi, and Gentaro Kawakami
Nat. Hazards Earth Syst. Sci., 24, 1287–1301, https://doi.org/10.5194/nhess-24-1287-2024, https://doi.org/10.5194/nhess-24-1287-2024, 2024
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Morphological conditions of drainage basins that classify the presence or absence of debris flow fans were analyzed in areas with different rock strength using decision tree analysis. The relief ratio is the most important morphological factor regardless of the geology. However, the thresholds of morphological parameters needed for forming debris flow fans differ depending on the geology. Decision tree analysis is an effective tool for evaluating the debris flow risk for each geology.
Daniel Bolliger, Fritz Schlunegger, and Brian W. McArdell
Nat. Hazards Earth Syst. Sci., 24, 1035–1049, https://doi.org/10.5194/nhess-24-1035-2024, https://doi.org/10.5194/nhess-24-1035-2024, 2024
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We analysed data from the Illgraben debris flow monitoring station, Switzerland, and we modelled these flows with a debris flow runout model. We found that no correlation exists between the grain size distribution, the mineralogical composition of the matrix, and the debris flow properties. The flow properties rather appear to be determined by the flow volume, from which most other parameters can be derived.
Yuntao Zhou, Xiaoyan Zhao, Guangze Zhang, Bernd Wünnemann, Jiajia Zhang, and Minghui Meng
Nat. Hazards Earth Syst. Sci., 24, 891–906, https://doi.org/10.5194/nhess-24-891-2024, https://doi.org/10.5194/nhess-24-891-2024, 2024
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We developed three rock bridge models to analyze 3D stability and deformation behaviors of the Tizicao landslide and found that the contact surface model with high strength parameters combines advantages of the intact rock mass model in simulating the deformation of slopes with rock bridges and the modeling advantage of the Jennings model. The results help in choosing a rock bridge model to simulate landslide stability and reveal the influence laws of rock bridges on the stability of landslides.
Ashok Dahal, Hakan Tanyas, Cees van Westen, Mark van der Meijde, Paul Martin Mai, Raphaël Huser, and Luigi Lombardo
Nat. Hazards Earth Syst. Sci., 24, 823–845, https://doi.org/10.5194/nhess-24-823-2024, https://doi.org/10.5194/nhess-24-823-2024, 2024
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We propose a modeling approach capable of recognizing slopes that may generate landslides, as well as how large these mass movements may be. This protocol is implemented, tested, and validated with data that change in both space and time via an Ensemble Neural Network architecture.
Li-Ru Luo, Zhi-Xiang Yu, Li-Jun Zhang, Qi Wang, Lin-Xu Liao, and Li Peng
Nat. Hazards Earth Syst. Sci., 24, 631–649, https://doi.org/10.5194/nhess-24-631-2024, https://doi.org/10.5194/nhess-24-631-2024, 2024
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We performed field investigations on a rockfall near Jiguanshan National Forest Park, Chengdu. Vital information was obtained from an unmanned aerial vehicle survey. A finite element model was created to reproduce the damage evolution. We found that the impact kinetic energy was below the design protection energy. Improper member connections prevent the barrier from producing significant deformation to absorb energy. Damage is avoided by improving the ability of the nets and ropes to slide.
Sudhanshu Dixit, Srikrishnan Siva Subramanian, Piyush Srivastava, Ali P. Yunus, Tapas Ranjan Martha, and Sumit Sen
Nat. Hazards Earth Syst. Sci., 24, 465–480, https://doi.org/10.5194/nhess-24-465-2024, https://doi.org/10.5194/nhess-24-465-2024, 2024
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Rainfall intensity–duration (ID) thresholds can aid in the prediction of natural hazards. Large-scale sediment disasters like landslides, debris flows, and flash floods happen frequently in the Himalayas because of their propensity for intense precipitation events. We provide a new framework that combines the Weather Research and Forecasting (WRF) model with a regionally distributed numerical model for debris flows to analyse and predict intense rainfall-induced landslides in the Himalayas.
Jacob B. Woodard, Benjamin B. Mirus, Nathan J. Wood, Kate E. Allstadt, Benjamin A. Leshchinsky, and Matthew M. Crawford
Nat. Hazards Earth Syst. Sci., 24, 1–12, https://doi.org/10.5194/nhess-24-1-2024, https://doi.org/10.5194/nhess-24-1-2024, 2024
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Dividing landscapes into hillslopes greatly improves predictions of landslide potential across landscapes, but their scaling is often arbitrarily set and can require significant computing power to delineate. Here, we present a new computer program that can efficiently divide landscapes into meaningful slope units scaled to best capture landslide processes. The results of this work will allow an improved understanding of landslide potential and can help reduce the impacts of landslides worldwide.
Anne Felsberg, Zdenko Heyvaert, Jean Poesen, Thomas Stanley, and Gabriëlle J. M. De Lannoy
Nat. Hazards Earth Syst. Sci., 23, 3805–3821, https://doi.org/10.5194/nhess-23-3805-2023, https://doi.org/10.5194/nhess-23-3805-2023, 2023
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The Probabilistic Hydrological Estimation of LandSlides (PHELS) model combines ensembles of landslide susceptibility and of hydrological predictor variables to provide daily, global ensembles of hazard for hydrologically triggered landslides. Testing different hydrological predictors showed that the combination of rainfall and soil moisture performed best, with the lowest number of missed and false alarms. The ensemble approach allowed the estimation of the associated prediction uncertainty.
Xushan Shi, Bo Chai, Juan Du, Wei Wang, and Bo Liu
Nat. Hazards Earth Syst. Sci., 23, 3425–3443, https://doi.org/10.5194/nhess-23-3425-2023, https://doi.org/10.5194/nhess-23-3425-2023, 2023
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A 3D stability analysis method is proposed for biased rockfall with external erosion. Four failure modes are considered according to rockfall evolution processes, including partial damage of underlying soft rock and overall failure of hard rock blocks. This method is validated with the biased rockfalls in the Sichuan Basin, China. The critical retreat ratio from low to moderate rockfall susceptibility is 0.33. This method could facilitate rockfall early identification and risk mitigation.
Marius Schneider, Nicolas Oestreicher, Thomas Ehrat, and Simon Loew
Nat. Hazards Earth Syst. Sci., 23, 3337–3354, https://doi.org/10.5194/nhess-23-3337-2023, https://doi.org/10.5194/nhess-23-3337-2023, 2023
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Rockfalls and their hazards are typically treated as statistical events based on rockfall catalogs, but only a few complete rockfall inventories are available today. Here, we present new results from a Doppler radar rockfall alarm system, which has operated since 2018 at a high frequency under all illumination and weather conditions at a site where frequent rockfall events threaten a village and road. The new data set is used to investigate rockfall triggers in an active rockslide complex.
Annette I. Patton, Lisa V. Luna, Joshua J. Roering, Aaron Jacobs, Oliver Korup, and Benjamin B. Mirus
Nat. Hazards Earth Syst. Sci., 23, 3261–3284, https://doi.org/10.5194/nhess-23-3261-2023, https://doi.org/10.5194/nhess-23-3261-2023, 2023
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Landslide warning systems often use statistical models to predict landslides based on rainfall. They are typically trained on large datasets with many landslide occurrences, but in rural areas large datasets may not exist. In this study, we evaluate which statistical model types are best suited to predicting landslides and demonstrate that even a small landslide inventory (five storms) can be used to train useful models for landslide early warning when non-landslide events are also included.
Sandra Melzner, Marco Conedera, Johannes Hübl, and Mauro Rossi
Nat. Hazards Earth Syst. Sci., 23, 3079–3093, https://doi.org/10.5194/nhess-23-3079-2023, https://doi.org/10.5194/nhess-23-3079-2023, 2023
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The estimation of the temporal frequency of the involved rockfall processes is an important part in hazard and risk assessments. Different methods can be used to collect and analyse rockfall data. From a statistical point of view, rockfall datasets are nearly always incomplete. Accurate data collection approaches and the application of statistical methods on existing rockfall data series as reported in this study should be better considered in rockfall hazard and risk assessments in the future.
Francis K. Rengers, Samuel Bower, Andrew Knapp, Jason W. Kean, Danielle W. vonLembke, Matthew A. Thomas, Jaime Kostelnik, Katherine R. Barnhart, Matthew Bethel, Joseph E. Gartner, Madeline Hille, Dennis M. Staley, Justin Anderson, Elizabeth K. Roberts, Stephen B. DeLong, Belize Lane, Paxton Ridgway, and Brendan P. Murphy
EGUsphere, https://doi.org/10.5194/egusphere-2023-2063, https://doi.org/10.5194/egusphere-2023-2063, 2023
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Every year the U.S. Geological Survey produces 50–100 postfire debris flow hazard assessments using models for debris flow likelihood and volume. To refine these models they must be tested with datasets that clearly document rainfall, debris flow response, and debris flow volume. These datasets are difficult to obtain, but this study developed and analyzed a postfire dataset with more than 100 postfire storm responses over a two year period. We also proposed ways to improve these models.
Stefan Hergarten
Nat. Hazards Earth Syst. Sci., 23, 3051–3063, https://doi.org/10.5194/nhess-23-3051-2023, https://doi.org/10.5194/nhess-23-3051-2023, 2023
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Rockslides are a major hazard in mountainous regions. In formerly glaciated regions, the disposition mainly arises from oversteepened topography and decreases through time. However, little is known about this decrease and thus about the present-day hazard of huge, potentially catastrophic rockslides. This paper presents a new theoretical framework that explains the decrease in maximum rockslide size through time and predicts the present-day frequency of large rockslides for the European Alps.
Colin K. Bloom, Corinne Singeisen, Timothy Stahl, Andrew Howell, Chris Massey, and Dougal Mason
Nat. Hazards Earth Syst. Sci., 23, 2987–3013, https://doi.org/10.5194/nhess-23-2987-2023, https://doi.org/10.5194/nhess-23-2987-2023, 2023
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Landslides are often observed on coastlines following large earthquakes, but few studies have explored this occurrence. Here, statistical modelling of landslides triggered by the 2016 Kaikōura earthquake in New Zealand is used to investigate factors driving coastal earthquake-induced landslides. Geology, steep slopes, and shaking intensity are good predictors of landslides from the Kaikōura event. Steeper slopes close to the coast provide the best explanation for a high landslide density.
Praveen Kumar, Priyanka Priyanka, Kala Venkata Uday, and Varun Dutt
EGUsphere, https://doi.org/10.5194/egusphere-2023-1417, https://doi.org/10.5194/egusphere-2023-1417, 2023
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Our study focuses on predicting soil movement to mitigate landslide risks. We develop machine learning models with oversampling techniques to address the class imbalance in monitoring data. The dynamic ensemble model with K-Means SMOTE achieves high accuracy (99.68 %), precision, recall, and F1-score, followed by RF with K-Means SMOTE. Our findings highlight the potential of these models to improve soil movement predictions in landslide-prone areas.
Yi-Min Huang
Nat. Hazards Earth Syst. Sci., 23, 2649–2662, https://doi.org/10.5194/nhess-23-2649-2023, https://doi.org/10.5194/nhess-23-2649-2023, 2023
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Debris flows are common hazards in Taiwan, and debris-flow early warning is important for disaster responses. The rainfall thresholds of debris flows are analyzed and determined in terms of rainfall intensity, accumulated rainfall, and rainfall duration, based on case histories in Taiwan. These thresholds are useful for disaster management, and the cases in Taiwan are useful for global debris-flow databases.
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
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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.
Simon Seelig, Thomas Wagner, Karl Krainer, Michael Avian, Marc Olefs, Klaus Haslinger, and Gerfried Winkler
Nat. Hazards Earth Syst. Sci., 23, 2547–2568, https://doi.org/10.5194/nhess-23-2547-2023, https://doi.org/10.5194/nhess-23-2547-2023, 2023
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A rapid sequence of cascading events involving thermokarst lake outburst, rock glacier front failure, debris flow development, and river blockage hit an alpine valley in Austria during summer 2019. We analyze the environmental conditions initiating the process chain and identify the rapid evolution of a thermokarst channel network as the main driver. Our results highlight the need to account for permafrost degradation in debris flow hazard assessment studies.
Camilla Lanfranconi, Paolo Frattini, Gianluca Sala, Giuseppe Dattola, Davide Bertolo, Juanjuan Sun, and Giovanni Battista Crosta
Nat. Hazards Earth Syst. Sci., 23, 2349–2363, https://doi.org/10.5194/nhess-23-2349-2023, https://doi.org/10.5194/nhess-23-2349-2023, 2023
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This paper presents a study on rockfall dynamics and hazard, examining the impact of the presence of trees along slope and block fragmentation. We compared rockfall simulations that explicitly model the presence of trees and fragmentation with a classical approach that accounts for these phenomena in model parameters (both the hazard and the kinetic energy change). We also used a non-parametric probabilistic rockfall hazard analysis method for hazard mapping.
Ascanio Rosi, William Frodella, Nicola Nocentini, Francesco Caleca, Hans Balder Havenith, Alexander Strom, Mirzo Saidov, Gany Amirgalievich Bimurzaev, and Veronica Tofani
Nat. Hazards Earth Syst. Sci., 23, 2229–2250, https://doi.org/10.5194/nhess-23-2229-2023, https://doi.org/10.5194/nhess-23-2229-2023, 2023
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This work was carried out within the Strengthening Financial Resilience and Accelerating Risk Reduction in Central Asia (SFRARR) project and is focused on the first landslide susceptibility analysis at a regional scale for Central Asia. The most detailed available landslide inventories were implemented in a random forest model. The final aim was to provide a useful tool for reduction strategies to landslide scientists, practitioners, and administrators.
Francis K. Rengers, Luke A. McGuire, Katherine R. Barnhart, Ann M. Youberg, Daniel Cadol, Alexander N. Gorr, Olivia J. Hoch, Rebecca Beers, and Jason W. Kean
Nat. Hazards Earth Syst. Sci., 23, 2075–2088, https://doi.org/10.5194/nhess-23-2075-2023, https://doi.org/10.5194/nhess-23-2075-2023, 2023
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Debris flows often occur after wildfires. These debris flows move water, sediment, and wood. The wood can get stuck in channels, creating a dam that holds boulders, cobbles, sand, and muddy material. We investigated how the channel width and wood length influenced how much sediment is stored. We also used a series of equations to back calculate the debris flow speed using the breaking threshold of wood. These data will help improve models and provide insight into future field investigations.
Kristian Svennevig, Julian Koch, Marie Keiding, and Gregor Luetzenburg
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2023-68, https://doi.org/10.5194/nhess-2023-68, 2023
Revised manuscript accepted for NHESS
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In this study, we examine how future climate change may affect activity in landslides in Denmark using publicly available data. Our findings show that climate change will increase groundwater table depth, which will lead to increased landslide activity. During past events of extremely wet winters in this region, landslides caused damage to buildings and infrastructure.
Maxime Morel, Guillaume Piton, Damien Kuss, Guillaume Evin, and Caroline Le Bouteiller
Nat. Hazards Earth Syst. Sci., 23, 1769–1787, https://doi.org/10.5194/nhess-23-1769-2023, https://doi.org/10.5194/nhess-23-1769-2023, 2023
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In mountain catchments, damage during floods is generally primarily driven by the supply of a massive amount of sediment. Predicting how much sediment can be delivered by frequent and infrequent events is thus important in hazard studies. This paper uses data gathered during the maintenance operation of about 100 debris retention basins to build simple equations aiming at predicting sediment supply from simple parameters describing the upstream catchment.
Elsa S. Culler, Ben Livneh, Balaji Rajagopalan, and Kristy F. Tiampo
Nat. Hazards Earth Syst. Sci., 23, 1631–1652, https://doi.org/10.5194/nhess-23-1631-2023, https://doi.org/10.5194/nhess-23-1631-2023, 2023
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Landslides have often been observed in the aftermath of wildfires. This study explores regional patterns in the rainfall that caused landslides both after fires and in unburned locations. In general, landslides that occur after fires are triggered by less rainfall, confirming that fire helps to set the stage for landslides. However, there are regional differences in the ways in which fire impacts landslides, such as the size and direction of shifts in the seasonality of landslides after fires.
Stefan Steger, Mateo Moreno, Alice Crespi, Peter James Zellner, Stefano Luigi Gariano, Maria Teresa Brunetti, Massimo Melillo, Silvia Peruccacci, Francesco Marra, Robin Kohrs, Jason Goetz, Volkmar Mair, and Massimiliano Pittore
Nat. Hazards Earth Syst. Sci., 23, 1483–1506, https://doi.org/10.5194/nhess-23-1483-2023, https://doi.org/10.5194/nhess-23-1483-2023, 2023
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We present a novel data-driven modelling approach to determine season-specific critical precipitation conditions for landslide occurrence. It is shown that the amount of precipitation required to trigger a landslide in South Tyrol varies from season to season. In summer, a higher amount of preparatory precipitation is required to trigger a landslide, probably due to denser vegetation and higher temperatures. We derive dynamic thresholds that directly relate to hit rates and false-alarm rates.
Yaspal Sundriyal, Vipin Kumar, Neha Chauhan, Sameeksha Kaushik, Rahul Ranjan, and Mohit Kumar Punia
Nat. Hazards Earth Syst. Sci., 23, 1425–1431, https://doi.org/10.5194/nhess-23-1425-2023, https://doi.org/10.5194/nhess-23-1425-2023, 2023
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The NW Himalaya has been one of the most affected terrains of the Himalaya, subject to disastrous landslides. This article focuses on two towns (Joshimath and Bhatwari) of the NW Himalaya, which have been witnessing subsidence for decades. We used a slope stability simulation to determine the response of the hillslopes accommodating these towns under various loading conditions. We found that the maximum displacement in these hillslopes might reach up to 20–25 m.
Yu Zhuang, Aiguo Xing, Perry Bartelt, Muhammad Bilal, and Zhaowei Ding
Nat. Hazards Earth Syst. Sci., 23, 1257–1266, https://doi.org/10.5194/nhess-23-1257-2023, https://doi.org/10.5194/nhess-23-1257-2023, 2023
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Tree destruction is often used to back calculate the air blast impact region and to estimate the air blast power. Here we established a novel model to assess air blast power using tree destruction information. We find that the dynamic magnification effect makes the trees easier to damage by a landslide-induced air blast, but the large tree deformation would weaken the effect. Bending and overturning are two likely failure modes, which depend heavily on the properties of trees.
Suzanne Lapillonne, Firmin Fontaine, Frédéric Liebault, Vincent Richefeu, and Guillaume Piton
Nat. Hazards Earth Syst. Sci., 23, 1241–1256, https://doi.org/10.5194/nhess-23-1241-2023, https://doi.org/10.5194/nhess-23-1241-2023, 2023
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Debris flows are fast flows most often found in torrential watersheds. They are composed of two phases: a liquid phase which can be mud-like and a granular phase, including large boulders, transported along with the flow. Due to their destructive nature, accessing features of the flow, such as velocity and flow height, is difficult. We present a protocol to analyse debris flow data and results of the Réal torrent in France. These results will help experts in designing models.
Carlos Millán-Arancibia and Waldo Lavado-Casimiro
Nat. Hazards Earth Syst. Sci., 23, 1191–1206, https://doi.org/10.5194/nhess-23-1191-2023, https://doi.org/10.5194/nhess-23-1191-2023, 2023
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This study is the first approximation of regional rainfall thresholds for shallow landslide occurrence in Peru. This research was generated from a gridded precipitation data and landslide inventory. The analysis showed that the threshold based on the combination of mean daily intensity–duration variables gives the best results for separating rainfall events that generate landslides. Through this work the potential of thresholds for landslide monitoring at the regional scale is demonstrated.
Luca Verrucci, Giovanni Forte, Melania De Falco, Paolo Tommasi, Giuseppe Lanzo, Kevin W. Franke, and Antonio Santo
Nat. Hazards Earth Syst. Sci., 23, 1177–1190, https://doi.org/10.5194/nhess-23-1177-2023, https://doi.org/10.5194/nhess-23-1177-2023, 2023
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Stability analyses in static and seismic conditions were performed on four rockslides that occurred during the main shocks of the 2016–2017 central Italy seismic sequence. These results also indicate that specific structural features of the slope must carefully be accounted for in evaluating potential hazards on transportation infrastructures in mountainous regions.
Enner Alcântara, José A. Marengo, José Mantovani, Luciana R. Londe, Rachel Lau Yu San, Edward Park, Yunung Nina Lin, Jingyu Wang, Tatiana Mendes, Ana Paula Cunha, Luana Pampuch, Marcelo Seluchi, Silvio Simões, Luz Adriana Cuartas, Demerval Goncalves, Klécia Massi, Regina Alvalá, Osvaldo Moraes, Carlos Souza Filho, Rodolfo Mendes, and Carlos Nobre
Nat. Hazards Earth Syst. Sci., 23, 1157–1175, https://doi.org/10.5194/nhess-23-1157-2023, https://doi.org/10.5194/nhess-23-1157-2023, 2023
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The municipality of Petrópolis (approximately 305 687 inhabitants) is nestled in the mountains 68 km outside the city of Rio de Janeiro. On 15 February 2022, the city of Petrópolis in Rio de Janeiro, Brazil, received an unusually high volume of rain within 3 h (258 mm). This resulted in flash floods and subsequent landslides that caused 231 fatalities, the deadliest landslide disaster recorded in Petrópolis. This work shows how the disaster was triggered.
Joshua N. Jones, Georgina L. Bennett, Claudia Abancó, Mark A. M. Matera, and Fibor J. Tan
Nat. Hazards Earth Syst. Sci., 23, 1095–1115, https://doi.org/10.5194/nhess-23-1095-2023, https://doi.org/10.5194/nhess-23-1095-2023, 2023
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We modelled where landslides occur in the Philippines using landslide data from three typhoon events in 2009, 2018, and 2019. These models show where landslides occurred within the landscape. By comparing the different models, we found that the 2019 landslides were occurring all across the landscape, whereas the 2009 and 2018 landslides were mostly occurring at specific slope angles and aspects. This shows that landslide susceptibility must be considered variable through space and time.
Shalev Siman-Tov and Francesco Marra
Nat. Hazards Earth Syst. Sci., 23, 1079–1093, https://doi.org/10.5194/nhess-23-1079-2023, https://doi.org/10.5194/nhess-23-1079-2023, 2023
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Debris flows represent a threat to infrastructure and the population. In arid areas, they are observed when heavy rainfall hits steep slopes with sediments. Here, we use digital surface models and radar rainfall data to detect and characterize the triggering and non-triggering rainfall conditions. We find that rainfall intensity alone is insufficient to explain the triggering. We suggest that antecedent rainfall could represent a critical factor for debris flow triggering in arid regions.
Xun Huang, Zhijian Zhang, and Guoping Xiang
Nat. Hazards Earth Syst. Sci., 23, 871–889, https://doi.org/10.5194/nhess-23-871-2023, https://doi.org/10.5194/nhess-23-871-2023, 2023
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A sensitivity analysis on the building impact force resulting from the representative built environment parameters is executed through the FLOW-3D model. The surrounding buildings' properties, especially the azimuthal angle, have been confirmed to play significant roles in determining the peak impact forces. The single and combined effects of built environments are analyzed in detail. This will improve understanding of vulnerability assessment and migration design against debris flow hazards.
Jean-Claude Maki Mateso, Charles L. Bielders, Elise Monsieurs, Arthur Depicker, Benoît Smets, Théophile Tambala, Luc Bagalwa Mateso, and Olivier Dewitte
Nat. Hazards Earth Syst. Sci., 23, 643–666, https://doi.org/10.5194/nhess-23-643-2023, https://doi.org/10.5194/nhess-23-643-2023, 2023
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This research highlights the importance of human activities on the occurrence of landslides and the need to consider this context when studying hillslope instability patterns in regions under anthropogenic pressure. Also, this study highlights the importance of considering the timing of landslides and hence the added value of using historical information for compiling an inventory.
Jakob Rom, Florian Haas, Tobias Heckmann, Moritz Altmann, Fabian Fleischer, Camillo Ressl, Sarah Betz-Nutz, and Michael Becht
Nat. Hazards Earth Syst. Sci., 23, 601–622, https://doi.org/10.5194/nhess-23-601-2023, https://doi.org/10.5194/nhess-23-601-2023, 2023
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In this study, an area-wide slope-type debris flow record has been established for Horlachtal, Austria, since 1947 based on historical and recent remote sensing data. Spatial and temporal analyses show variations in debris flow activity in space and time in a high-alpine region. The results can contribute to a better understanding of past slope-type debris flow dynamics in the context of extreme precipitation events and their possible future development.
Tom Birien and Francis Gauthier
Nat. Hazards Earth Syst. Sci., 23, 343–360, https://doi.org/10.5194/nhess-23-343-2023, https://doi.org/10.5194/nhess-23-343-2023, 2023
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On highly fractured rockwalls such as those found in northern Gaspésie, most rockfalls are triggered by weather conditions. This study highlights that in winter, rockfall frequency is 12 times higher during a superficial thaw than during a cold period in which temperature remains below 0 °C. In summer, rockfall frequency is 22 times higher during a heavy rainfall event than during a mainly dry period. This knowledge could be used to implement a risk management strategy.
Nunziarita Palazzolo, David J. Peres, Enrico Creaco, and Antonino Cancelliere
Nat. Hazards Earth Syst. Sci., 23, 279–291, https://doi.org/10.5194/nhess-23-279-2023, https://doi.org/10.5194/nhess-23-279-2023, 2023
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We propose an approach exploiting PCA to derive hydrometeorological landslide-triggering thresholds using multi-layered soil moisture data from ERA5-Land reanalysis. Comparison of thresholds based on single- and multi-layered soil moisture information provides a means to identify the significance of multi-layered data for landslide triggering in a region. In Sicily, the proposed approach yields thresholds with a higher performance than traditional precipitation-based ones (TSS = 0.71 vs. 0.50).
Raphael Knevels, Helene Petschko, Herwig Proske, Philip Leopold, Aditya N. Mishra, Douglas Maraun, and Alexander Brenning
Nat. Hazards Earth Syst. Sci., 23, 205–229, https://doi.org/10.5194/nhess-23-205-2023, https://doi.org/10.5194/nhess-23-205-2023, 2023
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In summer 2009 and 2014, rainfall events occurred in the Styrian Basin (Austria), triggering thousands of landslides. Landslide storylines help to show potential future changes under changing environmental conditions. The often neglected uncertainty quantification was the aim of this study. We found uncertainty arising from the landslide model to be of the same order as climate scenario uncertainty. Understanding the dimensions of uncertainty is crucial for allowing informed decision-making.
Fabian Walter, Elias Hodel, Erik S. Mannerfelt, Kristen Cook, Michael Dietze, Livia Estermann, Michaela Wenner, Daniel Farinotti, Martin Fengler, Lukas Hammerschmidt, Flavia Hänsli, Jacob Hirschberg, Brian McArdell, and Peter Molnar
Nat. Hazards Earth Syst. Sci., 22, 4011–4018, https://doi.org/10.5194/nhess-22-4011-2022, https://doi.org/10.5194/nhess-22-4011-2022, 2022
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Debris flows are dangerous sediment–water mixtures in steep terrain. Their formation takes place in poorly accessible terrain where instrumentation cannot be installed. Here we propose to monitor such source terrain with an autonomous drone for mapping sediments which were left behind by debris flows or may contribute to future events. Short flight intervals elucidate changes of such sediments, providing important information for landscape evolution and the likelihood of future debris flows.
Marc Peruzzetto, Yoann Legendre, Aude Nachbaur, Thomas J. B. Dewez, Yannick Thiery, Clara Levy, and Benoit Vittecoq
Nat. Hazards Earth Syst. Sci., 22, 3973–3992, https://doi.org/10.5194/nhess-22-3973-2022, https://doi.org/10.5194/nhess-22-3973-2022, 2022
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Volcanic edifices result from successive construction and dismantling phases. Thus, the geological units forming volcanoes display complex geometries. We show that such geometries can be reconstructed thanks to aerial views, topographic surveys and photogrammetric models. In our case study of the Samperre cliff (Martinique, Lesser Antilles), it allows us to link destabilizations from a rocky cliff to the existence of a filled paleo-valley and estimate a potentially unstable volume.
Abdellah Khouz, Jorge Trindade, Sérgio C. Oliveira, Fatima El Bchari, Blaid Bougadir, Ricardo A. C. Garcia, and Mourad Jadoud
Nat. Hazards Earth Syst. Sci., 22, 3793–3814, https://doi.org/10.5194/nhess-22-3793-2022, https://doi.org/10.5194/nhess-22-3793-2022, 2022
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The aim of this study was to assess the landslide susceptibility of the rocky coast of Essaouira using the information value model. The resulting susceptibility maps could be used for both environmental protection and general planning of future development activities.
Kamal Rana, Nishant Malik, and Ugur Ozturk
Nat. Hazards Earth Syst. Sci., 22, 3751–3764, https://doi.org/10.5194/nhess-22-3751-2022, https://doi.org/10.5194/nhess-22-3751-2022, 2022
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The landslide hazard models assist in mitigating losses due to landslides. However, these models depend on landslide databases, which often have missing triggering information, rendering these databases unusable for landslide hazard models. In this work, we developed a Python library, Landsifier, consisting of three different methods to identify the triggers of landslides. These methods can classify landslide triggers with high accuracy using only a landslide polygon shapefile as an input.
Axel A. J. Deijns, Olivier Dewitte, Wim Thiery, Nicolas d'Oreye, Jean-Philippe Malet, and François Kervyn
Nat. Hazards Earth Syst. Sci., 22, 3679–3700, https://doi.org/10.5194/nhess-22-3679-2022, https://doi.org/10.5194/nhess-22-3679-2022, 2022
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Landslides and flash floods are rainfall-induced processes that often co-occur and interact, generally very quickly. In mountainous cloud-covered environments, determining when these processes occur remains challenging. We propose a regional methodology using open-access satellite radar images that allow for the timing of landslide and flash floods events, in the contrasting landscapes of tropical Africa, with an accuracy of up to a few days. The methodology shows potential for transferability.
Cited articles
Aimaiti, Y., Liu, W., Yamazaki, F., and Maruyama, Y.: Earthquake-induced
landslide mapping for the 2018 Hokkaido Eastern Iburi earthquake using
PALSAR-2 data, Remote Sensing, 11, 2351, https://doi.org/10.3390/rs11202351, 2019.
Ardizzone, F., Cardinali, M., Carrara, A., Guzzetti, F., and Reichenbach, P.: Impact of mapping errors on the reliability of landslide hazard maps, Nat. Hazards Earth Syst. Sci., 2, 3–14, https://doi.org/10.5194/nhess-2-3-2002, 2002.
ALDI-landslide-detection: https://dgmilledge.users.earthengine.app/view/aldi-landslide-detection, last access: 4 February 2022.
Barlow, J., Martin, Y., and Franklin, S. E.: Detecting translational landslide
scars using segmentation of Landsat ETM+ and DEM data in the northern
Cascade Mountains, British Columbia, Can. J. Remote Sens., 29, 510–517, 2003.
Barlow, J., Barisin, I., Rosser, N., Petley, D., Densmore, A., and Wright,
T.: Seismically-induced mass movements and volumetric fluxes resulting from
the 2010 Mw= 7.2 earthquake in the Sierra Cucapah,
Mexico, Geomorphology, 230, 138–145, 2015.
Barsi, J. A., Lee, K., Kvaran, G., Markham, B. L., and Pedelty, J.A.: The spectral
response of the Landsat-8 Operational Land Imager, Remote Sensing, 6,
10232–10251, https://doi.org/10.3390/rs61010232, 2014.
Basharat, M., Ali, A., Jadoon, I. A. K., and Rohn, J.: Using PCA in evaluating
event-controlling attributes of landsliding in the 2005 Kashmir earthquake
region, NW Himalayas, Pakistan: Natural Hazards, 81, 1999–2017, https://doi.org/10.1007/s11069-016-2172-9, 2016.
Basharat, M., Ali, A., Jadoon, I. A. K., and Rohn, J.: Landsliding in the 2005 Kashmir earthquake region, NW Himalayas, Pakistan, Open Repository of Earthquake-triggered Ground Failure Inventories, U.S. Geological Survey data release collection [data set], https://doi.org/10.5066/F78G8J68, 2017.
Behling, R., Roessner, S., Kaufmann, H., and Kleinschmit, B.: Automated
spatiotemporal landslide mapping over large areas using rapideye time series
data, Remote Sensing, 6, 8026–8055, 2014.
Behling, R., Roessner, S., Golovko, D., and Kleinschmit, B.: Derivation of
long-term spatiotemporal landslide activity—A multi-sensor time series
approach, Remote Sens. Environ., 186, 88–104, 2016.
Bellugi, D., Milledge, D. G., Dietrich, W. E., Perron, J. T., and McKean, J.:
Predicting shallow landslide size and location across a natural landscape:
Application of a spectral clustering search algorithm, J. Geophys. Res.-Earth, 120, 2552–2585,
2015.
Bernard, T. G., Lague, D., and Steer, P.: Beyond 2D landslide inventories and their rollover: synoptic 3D inventories and volume from repeat lidar data, Earth Surf. Dynam., 9, 1013–1044, https://doi.org/10.5194/esurf-9-1013-2021, 2021.
Beven, K. and Binley, A.: The future of distributed models: model
calibration and uncertainty prediction, Hydrol. Process., 6, 279–298, 1992.
Burrows, K., Walters, R. J., Milledge, D., Spaans, K., and Densmore, A. L.: A
New Method for Large-Scale Landslide Classification from Satellite
Radar, Remote Sensing, 11, 237, https://doi.org/10.3390/rs11030237, 2019.
Carrara, A., Cardinali, M., and Guzzetti, F.: Uncertainty in assessing landslide hazard and risk, ITC Journal, 2, 172–183, 1992.
Chander, G., Markham, B. L., and Helder, D. L.: Summary of current radiometric
calibration coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI sensors,
Remote Sens. Environ., 113, 893–903, 2009.
Dietrich, W. E., Bellugi, D. G., Sklar, L. S., Stock, J. D., Heimsath, A. M., and
Roering, J. J.: Geomorphic transport laws for predicting landscape form and
dynamics, Geophys. Monogr.-American Geophysical Union, 135, 103–132, 2003.
Đurić, D., Mladenović, A., Pešić-Georgiadis, M.,
Marjanović, M., and Abolmasov, B.: Using multiresolution and
multitemporal satellite data for post-disaster landslide inventory in the
Republic of Serbia, Landslides, 14, 1467–1482, 2017.
Earth Engine: Landsat Algorithms, available at: https://developers.google.com/earth-engine/landsat, last
access: 5 September 2018.
Earth Engine: Simple cloud score, an example of computing a cloud-free
composite with L8 by selecting the least-cloudy pixel from the collection, available at:
https://code.earthengine.google.com/dc5611259d9ccab952526b3c2d05ce07, last
access: 28 January 2021.
ESA: Sentinel Radiometric Resolutions, available at: https://sentinels.copernicus.eu/web/sentinel/user-guides/sentinel-2-msi/resolutions/radiometric,
last access: 11 January 2022.
Fan, X., Scaringi, G., Domènech, G., Yang, F., Guo, X., Dai, L., He, C., Xu, Q., and Huang, R.: Two multi-temporal datasets that track the enhanced landsliding after the 2008 Wenchuan earthquake, Earth Syst. Sci. Data, 11, 35–55, https://doi.org/10.5194/essd-11-35-2019, 2019.
Frattini, P., Crosta, G., and Carrara, A.: Techniques for evaluating the performance of landslide susceptibility models, Eng. Geol., 111, 62–72, 2010.
Froude, M. J. and Petley, D. N.: Global fatal landslide occurrence from 2004 to 2016, Nat. Hazards Earth Syst. Sci., 18, 2161–2181, https://doi.org/10.5194/nhess-18-2161-2018, 2018.
Galli, M., Ardizzone, F., Cardinali, M., Guzzetti, F., and Reichenbach, P.:
Comparing landslide inventory maps, Geomorphology, 94, 268–289, 2008.
García, V., Mollineda, R. A., and Sánchez, J. S.: Theoretical analysis
of a performance measure for imbalanced data, in: 2010 20th International Conference on Pattern Recognition, IEEE, Istanbul, Turkey, 23–26 August 2010, 617–620, https://doi.org/10.1109/ICPR.2010.156, 2010.
Goodwin, N. R., Collett, L. J., Denham, R. J., Flood, N., and Tindall, D.: Cloud
and cloud shadow screening across Queensland, Australia: An automated method
for Landsat TM/ETM+ time series, Remote Sens. Environ., 134, 50–65, 2013.
Gorelick, N., Hancher, M., Dixon, M., Ilyushchenko, S., Thau, D., and Moore,
R.: Google Earth Engine: Planetary-scale geospatial analysis for everyone,
Remote Sens. Environ., 202, 18–27, 2017.
Gorum, T., van Westen, C. J., Korup, O., van der Meijde, M., Fan, X., and van
der Meer, F. D.: Complex rupture mechanism and topography control symmetry of
mass-wasting pattern, 2010 Haiti earthquake, Geomorphology, 184, 127–138, 2013.
Gorum, T., Korup, O., van Westen, C. J., van der Meijde, M., Xu, C., and van
der Meer, F. D.: Why so few? Landslides triggered by the 2002 Denali
earthquake, Alaska, Quaternary Sci. Rev., 95, 80–94, https://doi.org/10.1016/j.quascirev.2014.04.032,
2014.
Gorum, T., Van Westen, C. J., Korup, O., van der Meijde, M., Fan, X., and van der Meer, F. D.: Mass-wasting triggered by the 50 2010 Haiti earthquake, Open Repository of Earthquake-triggered Ground Failure Inventories, U.S. Geological Survey data release collection [data set], https://doi.org/10.5066/F7H130HG, 2017a.
Gorum, T., Korup, O., vanWesten, C. J., van der Meijde, M., Xu, C., and van der Meer, F. D.: Landslides triggered by the 2007 M 6.2 Aisen, Chile earthquake, Open Repository of Earthquake-triggered Ground Failure Inventories, U.S. Geological Survey data release collection [data set], https://doi.org/10.5066/F7125R5V, 2017b.
Greenbaum, D., Tutton, M., Bowker, M. R., Browne, T. J., Buleka, J., Greally,
K. B., Kuna, G., McDonald, A. J. W., Marsh, S. H., Northmore, K. H., and O'Connor, E. A.: Rapid methods of landslide hazard mapping: Papua New Guinea case study, Technical Report WC/95/27, British Geological Survey (BGS), Natural
Environmental Research Council, Keyworth, Nottingham, 1995.
Guzzetti, F., Mondini, A. C., Cardinali, M., Fiorucci, F., Santangelo, M., and
Chang, K. T.: Landslide inventory maps: New tools for an old
problem, Earth-Sci. Rev., 112, 42–66, 2012.
Haralick, R. M. and Shapiro, L. G.: Computer and Robot Vision, Addison-Wesley, Reading, Mass, ISBN 9780201108774, 1992.
Harp, E. L., Jibson, R. W., and Schmitt, R. G.: Map of landslides triggered by
the January 12, 2010, Haiti earthquake, US Geological Survey Scientific Investigations Map, 3353, p. 15, https://doi.org/10.3133/sim3353, 2016.
Harp, E. L., Jibson, R. W., and Schmitt, R. G.: Map of landslides triggered by the January 12, 2010, Haiti earthquake, Open Repository of Earthquake-triggered Ground Failure Inventories, U.S. Geological Survey data release collection [data set], https://doi.org/10.5066/F7C827SR, 2017.
Hilton, R. G., Galy, A., Hovius, N., Chen, M. C., Horng, M. J., and Chen, H.:
Tropical-cyclone-driven erosion of the terrestrial biosphere from
mountains, Nat. Geosci., 1, 759–762, 2008.
Hovius, N., Meunier, P., Lin, C. W., Chen, H., Chen, Y. G., Dadson, S., Horng, M. J., and Lines, M.: Prolonged seismically induced erosion and the mass balance of a large earthquake, Earth Planet. Sc. Lett., 304, 347–355, 2011.
Irish, R. R.: Landsat 7 automatic cloud cover assessment, in: Algorithms for Multispectral, Hyperspectral, and Ultraspectral Imagery VI, International Society for Optics and Photonics, Vol. 4049,
348–355, https://doi.org/10.1117/12.410358, 2000.
Jeandet, L., Steer, P., Lague, D., and Davy, P.: Coulomb mechanics and relief
constraints explain landslide size distribution, Geophys. Res. Lett., 46, 4258–4266, 2019.
Konishi, T. and Suga, Y.: Landslide detection using COSMO-SkyMed images: a
case study of a landslide event on Kii Peninsula, Japan, Eur. J. Remote Sens., 51, 205–221,
2018.
Larsen, I. J., Montgomery, D. R., and Korup, O.: Landslide erosion controlled
by hillslope material, Nat. Geosci., 3, 247–251, 2010.
Li, G., West, A. J., Densmore, A. L., Jin, Z., Parker, R. N., and Hilton, R. G.:
Seismic mountain building: Landslides associated with the 2008 Wenchuan
earthquake in the context of a generalized model for earthquake volume
balance, Geochem. Geophys. Geosy., 15, 833–844, 2014.
Li, G., West, A. J., Densmore, A. L., Jin, Z., Parker, R. N., and Hilton, R. G.: Landslides associated with the 2008 Wenchuan earthquake, Open Repository of Earthquake-triggered Ground Failure Inventories, U.S. Geological Survey data release collection [data set], https://doi.org/10.5066/F7MS3R8Z, 2017.
Marano, K. D., Wald, D. J., and Allen, T. I.: Global earthquake casualties due
to secondary effects: a quantitative analysis for improving rapid loss
analyses, Nat. Hazards, 52, 319–328, 2010.
Marc, O. and Hovius, N.: Amalgamation in landslide maps: effects and automatic detection, Nat. Hazards Earth Syst. Sci., 15, 723–733, https://doi.org/10.5194/nhess-15-723-2015, 2015.
Marc, O., Hovius, N., Meunier, P., Uchida, T., and Hayashi, S.: Transient
changes of landslide rates after earthquakes, Geology, 43, 883–886, 2015.
Marc, O., Hovius, N., Meunier, P., Gorum, T., and Uchida, T.: A
seismologically consistent expression for the total area and volume of
earthquake-triggered landsliding, J. Geophys. Res.-Earth, 121, 640–663, 2016.
Marc, O., Stumpf, A., Malet, J.-P., Gosset, M., Uchida, T., and Chiang, S.-H.: Initial insights from a global database of rainfall-induced landslide inventories: the weak influence of slope and strong influence of total storm rainfall, Earth Surf. Dynam., 6, 903–922, https://doi.org/10.5194/esurf-6-903-2018, 2018.
Marc, O., Behling, R., Andermann, C., Turowski, J. M., Illien, L., Roessner, S., and Hovius, N.: Long-term erosion of the Nepal Himalayas by bedrock landsliding: the role of monsoons, earthquakes and giant landslides, Earth Surf. Dynam., 7, 107–128, https://doi.org/10.5194/esurf-7-107-2019, 2019.
Martin, Y. E. and Franklin, S. E.: Classification of soil-and
bedrock-dominated landslides in British Columbia using segmentation of
satellite imagery and DEM data, Int. J. Remote Sens., 26, 1505–1509, 2005.
Milledge, D. G.: ALDIv1.1.0 The Automated Landslide Detection Index, Zenodo [code], https://doi.org/10.5281/zenodo.5813872, 2021.
Mondini, A.C., Santangelo, M., Rocchetti, M., Rossetto, E., Manconi, A., and
Monserrat, O.: Sentinel-1 SAR amplitude imagery for rapid landslide
detection, Remote Sensing, 11, 760, https://doi.org/10.3390/rs11070760, 2019.
Parker, R. N., Densmore, A. L., Rosser, N. J., De Michele, M., Li, Y., Huang,
R., Whadcoat, S., and Petley, D. N.: Mass wasting triggered by the 2008
Wenchuan earthquake is greater than orogenic growth, Nat. Geosci., 4, 449, https://doi.org/10.1038/ngeo1154, 2011.
Pawłuszek, K., Borkowski, A., and Tarolli, P.: Towards the optimal pixel size of DEM for automatic mapping of landslide areas, 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, 2017.
Pekel, J. F., Cottam, A., Gorelick, N., and Belward, A. S.: High-resolution
mapping of global surface water and its long-term
changes, Nature, 540, 418, https://doi.org/10.1038/nature20584, 2016.
Prakash, N., Manconi, A., and Loew, S. Mapping landslides on EO data:
Performance of deep learning models vs. traditional machine learning
models, Remote Sensing, 12, 346, https://doi.org/10.3390/rs12030346, 2020.
Reichenbach, P., Rossi, M., Malamud, B. D., Mihir, M., and Guzzetti, F.: A
review of statistically-based landslide susceptibility
models, Earth-Sci. Rev., 180, 60–91, 2018.
Restrepo, C., Walker, L. R., Shiels, A. B., Bussmann, R., Claessens, L.,
Fisch, S., Lozano, P., Negi, G., Paolini, L., Poveda, G., and
Ramos-Scharrón, C.: Landsliding and its multiscale influence on
mountainscapes, BioScience, 59, 685–698, 2009.
Roback, K., Clark, M. K., West, A. J., Zekkos, D., Li, G., Gallen, S. F.,
Champlain, D., and Godt, J. W.: Map data of landslides triggered by the 25
April 2015 Mw 7.8 Gorkha, Nepal earthquake, U.S. Geological Survey data release [data set], https://doi.org/10.5066/F7DZ06F9, 2017.
Roback, K., Clark, M. K., West, A. J., Zekkos, D., Li, G., Gallen, S. F.,
Chamlagain, D., and Godt, J. W.: The size, distribution, and mobility of
landslides caused by the 2015 Mw 7.8 Gorkha earthquake, Nepal,
Geomorphology, 301, 121–138, 2018.
Santangelo, M., Marchesini, I., Bucci, F., Cardinali, M., Fiorucci, F., and Guzzetti, F.: An approach to reduce mapping errors in the production of landslide inventory maps, Nat. Hazards Earth Syst. Sci., 15, 2111–2126, https://doi.org/10.5194/nhess-15-2111-2015, 2015.
Sato, H. P., Hasegawa, H., Fujiwara, S., Tobita, M., Koarai, M., Une, H., and
Iwahashi, J.: Interpretation of landslide distribution triggered by the 2005
Northern Pakistan earthquake using SPOT 5 imagery, Landslides, 4, 113–122, 2007.
Sato, H. P., Hasegawa, H., Fujiwara, S., Tobita, M., Koarai, M., Une, H., and Iwahashi, J.: Landslide distribution triggered by the 2005 Northern Pakistan earthquake using SPOT 5 imagery, Open Repository of Earthquake-triggered Ground Failure Inventories, U.S. Geological Survey data release collection [data set], https://doi.org/10.5066/F7SJ1J42, 2017.
Sauchyn, D. J. and Trench, N. R.: Landsat applied to landslide
mapping, Photogramm. Eng. Rem. S., 44, 735–741, 1978.
Scheip, C. M. and Wegmann, K. W.: HazMapper: a global open-source natural hazard mapping application in Google Earth Engine, Nat. Hazards Earth Syst. Sci., 21, 1495–1511, https://doi.org/10.5194/nhess-21-1495-2021, 2021.
Schmitt, R. G., Tanyas, H., Nowicki Jessee, M. A., Zhu, J., Biegel, K. M., Allstadt, K. E., Jibson, R. W., Thompson, E. M., Van Westen, C. J., Sato, H. P., Wald, D. J., Godt, J. W., Gorum, T., Xu, C., Rathje, E. M., and Knudsen, K. L.: An Open Repository of Earthquake-Triggered Ground-Failure Inventories (ver 3.0, September 2020), U.S. Geological Survey data release collection [data set], https://doi.org/10.5066/F7H70DB4, 2017.
Sepulveda, S., Serey, A., Lara, M., Pavez, A., and Rebolledo, S.: Landslides
induced by the April 2007 Aisen Fjord earthquake, Chilean Patagonia,
Landslides, 7, 483–492, https://doi.org/10.1007/s10346-010-0203-2, 2010a.
Sepulveda, S, Serey, A., Lara, M., Pavez, A., and Rebolledo, S.: Landslides induced by the April 2007 Aisen Fjord earthquake, Chilean Patagonia, Open Repository of Earthquake-triggered Ground Failure Inventories, U.S. Geological Survey data release collection [data set], available at: https://www.sciencebase.gov/catalog/item/5b5f36e3e4b006a11f66e599 (last access: 9 February 2022), 2010b.
Tanyaş, H., Van Westen, C. J., Allstadt, K. E., Anna Nowicki Jessee, M.,
Görüm, T., Jibson, R. W., Godt, J. W., Sato, H. P., Schmitt, R. G.,
Marc, O., and Hovius, N.: Presentation and analysis of a worldwide database
of earthquake-induced landslide inventories, J. Geophys. Res.-Earth, 122, 1991–2015, 2017.
Tanyaş, H., van Westen, C. J., Allstadt, K. E., and Jibson, R. W.: Factors
controlling landslide frequency–area distributions, Earth Surf. Proc. Land., 44, 900–917,
2019.
Taylor, F. E., Malamud, B. D., Witt, A., and Guzzetti, F.: Landslide shape,
ellipticity and length-to-width ratios, Earth Surf. Proc. Land., 43, 3164–3189, 2018.
Tharwat, A.: Classification assessment methods, Applied Computing and Informatics, 17, 168–192, https://doi.org/10.1016/J.ACI.2018.08.003, 2020.
Tucker, C. J.: Red and photographic infrared linear combinations for
monitoring vegetation, Remote Sens. Environ., 8, 127–150, 1979.
USGS: Landsat Collection 1 Level 1 Product Definition, Version 2.0, EROS, Sioux Falls, South Dakota, USA, LSDS-1656, 2019.
Van Westen, C. J., Van Asch, T. W., and Soeters, R.: Landslide hazard and risk
zonation – why is it still so difficult?, B. Eng. Geol. Environ., 65, 167–184, 2006.
Wang, F., Fan, X., Yunus, A. P., Subramanian, S. S., Alonso-Rodriguez, A.,
Dai, L., Xu, Q., and Huang, R.: Coseismic landslides triggered by the 2018
Hokkaido, Japan (Mw 6.6), earthquake: spatial distribution, controlling
factors, and possible failure mechanism, Landslides, 16, 1551–1566, 2019.
Warburton, J., Milledge, D. G., and Johnson, R.: Assessment of shallow landslide activity following the January 2005 storm, Northern Cumbria, Cumberland Geological Society proceedings, 7, 263–283, 2008.
Watt, J.: The characteristics of coseismic landslides triggered by the 2015 Gorkha earthquake, Undergraduate Dissertation, Durham University, 2016.
Williams, J. G., Rosser, N. J., Kincey, M. E., Benjamin, J., Oven, K. J., Densmore, A. L., Milledge, D. G., Robinson, T. R., Jordan, C. A., and Dijkstra, T. A.: Satellite-based emergency mapping using optical imagery: experience and reflections from the 2015 Nepal earthquakes, Nat. Hazards Earth Syst. Sci., 18, 185–205, https://doi.org/10.5194/nhess-18-185-2018, 2018.
Wilson, A. M. and Jetz, W.: Remotely sensed high-resolution global cloud
dynamics for predicting ecosystem and biodiversity distributions, PLoS Biology, 14,
e1002415, https://doi.org/10.1371/journal.pbio.1002415, 2016.
Xu, C., Xu, X., Yao, X., and Dai, F.: Three (nearly) complete inventories of
landslides triggered by the May 12, 2008 Wenchuan Mw 7.9 earthquake of China
and their spatial distribution statistical analysis, Landslides, 11, 441–461,
https://doi.org/10.1007/s10346-013-0404-6, 2014.
Xu, C., Xu, X., Yao, X., and Dai, F.: Landslides triggered by the May 12, 2008, Wenchuan Mw 7.9 earthquake of China, Open Repository of Earthquake-triggered Ground Failure Inventories, U.S. Geological Survey data release collection [data set], https://doi.org/10.5066/F7RJ4H0P, 2017.
Zhang, J. Q., Liu, R. K., Deng, W., Khanal, N. R., Gurung, D. R., Murthy, M. S. R.,
and Wahid, S.: Characteristics of landslide in Koshi River basin, central
Himalaya, J. Mt. Sci,, 13, 1711–1722, 2016.
Zhang, J. Q., Liu, R. K., Deng, W., Khanal, N. R., Gurung, D. R., Murthy, M. S. R., and Wahid, S.: Characteristics of landslides in Koshi River basin, Central Himalaya, Open Repository of Earthquake-triggered Ground Failure Inventories, U.S. Geological Survey data release collection [data set], https://doi.org/10.5066/F73T9FQ1, 2017.
Short summary
Earthquakes can trigger thousands of landslides, causing severe and widespread damage. Efforts to understand what controls these landslides rely heavily on costly and time-consuming manual mapping from satellite imagery. We developed a new method that automatically detects landslides triggered by earthquakes using thousands of free satellite images. We found that in the majority of cases, it was as skilful at identifying the locations of landslides as the manual maps that we tested it against.
Earthquakes can trigger thousands of landslides, causing severe and widespread damage. Efforts...
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