Articles | Volume 20, issue 12
https://doi.org/10.5194/nhess-20-3413-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/nhess-20-3413-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| Highlight paper
| 
14 Dec 2020
Research article | Highlight paper |
| 14 Dec 2020
| 14 Dec 2020
New global characterisation of landslide exposure
Robert Emberson
CORRESPONDING AUTHOR
Hydrological Sciences Laboratory, NASA Goddard Space Flight Center, 8800 Greenbelt Road, Greenbelt, MD 20771, USA
Universities Space Research Association, Columbia, MD 21046, USA
Goddard Earth Sciences Technology and Research, Columbia, MD 21046, USA
Dalia Kirschbaum
Hydrological Sciences Laboratory, NASA Goddard Space Flight Center, 8800 Greenbelt Road, Greenbelt, MD 20771, USA
Thomas Stanley
Hydrological Sciences Laboratory, NASA Goddard Space Flight Center, 8800 Greenbelt Road, Greenbelt, MD 20771, USA
Universities Space Research Association, Columbia, MD 21046, USA
Goddard Earth Sciences Technology and Research, Columbia, MD 21046, USA
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41 citations as recorded by crossref.
- HazMapper: a global open-source natural hazard mapping application in Google Earth Engine C. Scheip & K. Wegmann 10.5194/nhess-21-1495-2021
- Historical dynamics of landslide risk from population and forest-cover changes in the Kivu Rift A. Depicker et al. 10.1038/s41893-021-00757-9
- Changes in the factors contributing to the reduction of landslide fatalities between 1945 and 2019 in Japan Y. Shinohara & T. Kume 10.1016/j.scitotenv.2022.154392
- Global Landslide Forecasting System for Hazard Assessment and Situational Awareness S. Khan et al. 10.3389/feart.2022.878996
- A Reinforcement Learning approach to the location of the non-circular critical slip surface of slopes E. Soranzo et al. 10.1016/j.cageo.2022.105182
- A GIS-Based Approach for Shallow Landslides Risk Assessment in the Giampilieri and Briga Catchments Areas (Sicily, Italy) G. Vegliante et al. 10.3390/geohazards5010011
- Community adaptive capacity in facing landslide disaster P. Wijayanti et al. 10.1088/1755-1315/1314/1/012107
- Mitigation measures of debris flow and landslide risk carried out in two mountain areas of North-Eastern Italy R. Genevois et al. 10.1007/s11629-021-7212-6
- Assessing Global Landslide Casualty Risk Under Moderate Climate Change Based on Multiple GCM Projections X. Wang et al. 10.1007/s13753-023-00514-w
- Data-Driven Landslide Nowcasting at the Global Scale T. Stanley et al. 10.3389/feart.2021.640043
- Convolutional neural networks prediction of the factor of safety of random layered slopes by the strength reduction method E. Soranzo et al. 10.1007/s11440-022-01783-3
- Quantifying climate risks to infrastructure systems: A comparative review of developments across infrastructure sectors J. Verschuur et al. 10.1371/journal.pclm.0000331
- Characteristics and Distribution of Landslides in the Populated Hillslopes of Bujumbura, Burundi D. Kubwimana et al. 10.3390/geosciences11060259
- From theoretical to sustainable potential for run-of-river hydropower development in the upper Indus basin S. Dhaubanjar et al. 10.1016/j.apenergy.2023.122372
- Insights from the topographic characteristics of a large global catalog of rainfall-induced landslide event inventories R. Emberson et al. 10.5194/nhess-22-1129-2022
- Investigation of Model Uncertainty in Rainfall-Induced Landslide Prediction under Changing Climate Conditions Y. Chen et al. 10.3390/land12091732
- Mobilization rates of landslides in a changing tropical environment: 60-year record over a large region of the East African Rift A. Depicker et al. 10.1016/j.geomorph.2024.109156
- Generating landslide density heatmaps for rapid detection using open-access satellite radar data in Google Earth Engine A. Handwerger et al. 10.5194/nhess-22-753-2022
- Contrasting Population Projections to Induce Divergent Estimates of Landslides Exposure Under Climate Change Q. Lin et al. 10.1029/2023EF003741
- A near-real-time global landslide incident reporting tool demonstrator using social media and artificial intelligence C. Pennington et al. 10.1016/j.ijdrr.2022.103089
- Evaluation of potential changes in landslide susceptibility and landslide occurrence frequency in China under climate change Q. Lin et al. 10.1016/j.scitotenv.2022.158049
- Framework for rainfall-triggered landslide-prone critical infrastructure zonation K. Gnyawali et al. 10.1016/j.scitotenv.2023.162242
- Potential for small and micro modular reactors to electrify developing regions G. L’Her et al. 10.1038/s41560-024-01512-y
- Event-based rainfall-induced landslide inventories and rainfall thresholds for Malawi P. Niyokwiringirwa et al. 10.1007/s10346-023-02203-7
- Mass Movement Hazard and Exposure in the Himalaya S. Dubey et al. 10.1029/2022EF003253
- Phenomenology of Avalanche Recordings From Distributed Acoustic Sensing P. Paitz et al. 10.1029/2022JF007011
- Keynote lecture. Landslide Early Warning Systems: Resources or Problems? F. Guzzetti et al. 10.1051/e3sconf/202341503010
- A Framework for Calculating Peak Discharge and Flood Inundation in Ungauged Urban Watersheds Using Remotely Sensed Precipitation Data: A Case Study in Freetown, Sierra Leone A. Cotugno et al. 10.3390/rs13193806
- Time-Lapse Electrical Resistivity Tomography (TL-ERT) for Landslide Monitoring: Recent Advances and Future Directions V. Lapenna & A. Perrone 10.3390/app12031425
- Detection of slow‐moving landslides through automated monitoring of surface deformation using Sentinel‐2 satellite imagery M. Van Wyk de Vries et al. 10.1002/esp.5775
- Regional-scale landslide risk assessment in Central Asia F. Caleca et al. 10.5194/nhess-24-13-2024
- A near-real-time model for estimating probability of road obstruction due to earthquake-triggered landslides B. Wilson et al. 10.1177/87552930211020022
- Indicating landslide hazard from tree rings – Ecosystem service provided by an alder forest in the hengduan Mts, Sichuan, China M. Wistuba et al. 10.1016/j.ecoser.2024.101619
- Timing landslide and flash flood events from SAR satellite: a regionally applicable methodology illustrated in African cloud-covered tropical environments A. Deijns et al. 10.5194/nhess-22-3679-2022
- Trees as bioindicators of hillslope degradation by debris flows and dangerous rockfalls along the Lefthand Canyon, Colorado Front Range Ł. Pawlik et al. 10.1002/ldr.4575
- Differences in factors determining landslide hazards among three types of landslides in Japan Y. Shinohara & Y. Watanabe 10.1007/s11069-023-06075-x
- Analysis of human exposure to landslides with a GIS multiscale approach S. Modugno et al. 10.1007/s11069-021-05186-7
- 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) J. Maki Mateso et al. 10.5194/nhess-23-643-2023
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- Constraining landslide timing in a data-scarce context: from recent to very old processes in the tropical environment of the North Tanganyika-Kivu Rift region O. Dewitte et al. 10.1007/s10346-020-01452-0
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Latest update: 29 Jun 2024
Short summary
Landslides cause thousands of fatalities and cost billions of dollars of damage worldwide every year, but different inventories of landslide events can have widely diverging completeness. This can lead to spatial biases in our understanding of the impacts. Here we use a globally homogeneous model of landslide hazard and exposure to provide consistent estimates of where landslides are most likely to cause damage to people, roads and other critical infrastructure at 1 km resolution.
Landslides cause thousands of fatalities and cost billions of dollars of damage worldwide every...
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