Articles | Volume 22, issue 3
https://doi.org/10.5194/nhess-22-1129-2022
© 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-22-1129-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
01 Apr 2022
Research article |
| 01 Apr 2022
| 01 Apr 2022
Insights from the topographic characteristics of a large global catalog of rainfall-induced landslide event inventories
Robert Emberson
CORRESPONDING AUTHOR
Hydrological Sciences Laboratory, NASA Goddard Space Flight Center,
Greenbelt, MD, USA
Goddard Earth Sciences Technology and Research II, Greenbelt, MD, USA
University of Maryland, Baltimore County, 1000 Hilltop Cir, Baltimore, MD, USA
Dalia B. Kirschbaum
Hydrological Sciences Laboratory, NASA Goddard Space Flight Center,
Greenbelt, MD, USA
Pukar Amatya
Hydrological Sciences Laboratory, NASA Goddard Space Flight Center,
Greenbelt, MD, USA
Goddard Earth Sciences Technology and Research II, Greenbelt, MD, USA
University of Maryland, Baltimore County, 1000 Hilltop Cir, Baltimore, MD, USA
Hakan Tanyas
ITC, University of Twente, Twente, the Netherlands
Odin Marc
Géosciences Environnement Toulouse (GET), UMR 5563,
CNRS/IRD/CNES/UPS, Observatoire Midi-Pyrénées, Toulouse, France
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32 citations as recorded by crossref.
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- Time series analysis of slope displacements using UAV photogrammetry and its relationship with rainfall intensity N. Kim et al. 10.1007/s10346-024-02249-1
- 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
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- Detailed Inventory and Spatial Distribution Analysis of Rainfall-Induced Landslides in Jiexi County, Guangdong Province, China in August 2018 C. Xie et al. 10.3390/su151813930
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- Insight into the Characteristics and Triggers of Loess Landslides during the 2013 Heavy Rainfall Event in the Tianshui Area, China X. Shao et al. 10.3390/rs15174304
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- Using Sentinel-1 radar amplitude time series to constrain the timings of individual landslides: a step towards understanding the controls on monsoon-triggered landsliding K. Burrows et al. 10.5194/nhess-22-2637-2022
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- Understanding fatal landslides at global scales: a summary of topographic, climatic, and anthropogenic perspectives S. Fidan et al. 10.1007/s11069-024-06487-3
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- Characterizing the Distribution Pattern and a Physically Based Susceptibility Assessment of Shallow Landslides Triggered by the 2019 Heavy Rainfall Event in Longchuan County, Guangdong Province, China S. Ma et al. 10.3390/rs14174257
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- Observations and computational multi‐phase modelling in tropical river settings show complex channel changes downstream from rainfall‐triggered landslides D. Panici et al. 10.1002/esp.5841
31 citations as recorded by crossref.
- Application of GIS-based data-driven bivariate statistical models for landslide prediction: a case study of highly affected landslide prone areas of Teesta River basin I. Poddar & R. Roy 10.1016/j.qsa.2023.100150
- Time series analysis of slope displacements using UAV photogrammetry and its relationship with rainfall intensity N. Kim et al. 10.1007/s10346-024-02249-1
- 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
- Multi-hazard susceptibility mapping of cryospheric hazards in a high-Arctic environment: Svalbard Archipelago I. Nicu et al. 10.5194/essd-15-447-2023
- The influence of spatial patterns in rainfall on shallow landslides H. Smith et al. 10.1016/j.geomorph.2023.108795
- Detailed Inventory and Spatial Distribution Analysis of Rainfall-Induced Landslides in Jiexi County, Guangdong Province, China in August 2018 C. Xie et al. 10.3390/su151813930
- The Evaluation of Rainfall Warning Thresholds for Shallow Slope Stability Based on the Local Safety Factor Theory Y. Yang et al. 10.3390/geosciences14100274
- Insight into the Characteristics and Triggers of Loess Landslides during the 2013 Heavy Rainfall Event in the Tianshui Area, China X. Shao et al. 10.3390/rs15174304
- Landslides Triggered by the 2016 Heavy Rainfall Event in Sanming, Fujian Province: Distribution Pattern Analysis and Spatio-Temporal Susceptibility Assessment S. Ma et al. 10.3390/rs15112738
- Using Sentinel-1 radar amplitude time series to constrain the timings of individual landslides: a step towards understanding the controls on monsoon-triggered landsliding K. Burrows et al. 10.5194/nhess-22-2637-2022
- Global Assessment of the Capability of Satellite Precipitation Products to Retrieve Landslide-Triggering Extreme Rainfall Events O. Marc et al. 10.1175/EI-D-21-0022.1
- Understanding fatal landslides at global scales: a summary of topographic, climatic, and anthropogenic perspectives S. Fidan et al. 10.1007/s11069-024-06487-3
- A novel landslide susceptibility prediction framework based on contrastive loss S. Ouyang et al. 10.1080/15481603.2024.2306740
- Hydrogeotechnical Predictive Approach for Rockfall Mountain Hazard Using Elastic Modulus and Peak Shear Stress at Soil–Rock Interface in Dry and Wet Phases at KKH Pakistan E. Mehmood et al. 10.3390/su142416740
- Rainfall-seismic coupling effect induced landslide hazard assessment Z. Li et al. 10.1007/s11069-023-06084-w
- Refined Zoning of Landslide Susceptibility: A Case Study in Enshi County, Hubei, China Z. Wang et al. 10.3390/ijerph19159412
- Size scaling of large landslides from incomplete inventories O. Korup et al. 10.5194/nhess-24-3815-2024
- A survey of machine learning and deep learning in remote sensing of geological environment: Challenges, advances, and opportunities W. Han et al. 10.1016/j.isprsjprs.2023.05.032
- Establishing a Landslide Traces Inventory for the Baota District, Yan’an City, China, Using High-Resolution Satellite Images S. Zhang et al. 10.3390/land13101580
- Rapid Mapping of Landslides Induced by Heavy Rainfall in the Emilia-Romagna (Italy) Region in May 2023 M. Ferrario & F. Livio 10.3390/rs16010122
- Modelling antecedent soil hydrological conditions to improve the prediction of landslide susceptibility in typhoon-prone regions C. Abancó et al. 10.1007/s10346-024-02242-8
- Estimating global landslide susceptibility and its uncertainty through ensemble modeling A. Felsberg et al. 10.5194/nhess-22-3063-2022
- Important considerations in machine learning-based landslide susceptibility assessment under future climate conditions Y. Han & S. Semnani 10.1007/s11440-024-02363-3
- Spatial and Temporal Analysis of Global Landslide Reporting Using a Decade of the Global Landslide Catalog C. Dandridge et al. 10.3390/su15043323
- Destabilization Mechanism of Rainfall-Induced Loess Landslides in the Kara Haisu Gully, Xinyuan County, Ili River Valley, China: Physical Simulation T. Zhang et al. 10.3390/w15213775
- Characterizing the Distribution Pattern and a Physically Based Susceptibility Assessment of Shallow Landslides Triggered by the 2019 Heavy Rainfall Event in Longchuan County, Guangdong Province, China S. Ma et al. 10.3390/rs14174257
- Near Pan-Svalbard permafrost cryospheric hazards inventory (SvalCryo) I. Nicu et al. 10.1038/s41597-024-03754-7
- A hybrid deep learning method for landslide susceptibility analysis with the application of InSAR data R. Yuan & J. Chen 10.1007/s11069-022-05430-8
- Revealing the relation between spatial patterns of rainfall return levels and landslide density S. Mtibaa & H. Tsunetaka 10.5194/esurf-11-461-2023
- Assessing shallow slope stability using electrical conductivity data and soil hydraulic characteristics Y. Yang et al. 10.1016/j.enggeo.2024.107447
- Multi-event assessment of typhoon-triggered landslide susceptibility in the Philippines J. Jones et al. 10.5194/nhess-23-1095-2023
Latest update: 20 Nov 2024
Short summary
Understanding where landslides occur in mountainous areas is critical to support hazard analysis as well as understand landscape evolution. In this study, we present a large compilation of inventories of landslides triggered by rainfall, including several that are described here for the first time. We analyze the topographic characteristics of the landslides, finding consistent relationships for landslide source and deposition areas, despite differences in the inventories' locations.
Understanding where landslides occur in mountainous areas is critical to support hazard analysis...
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