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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Cited
19 citations as recorded by crossref.
- Refined Zoning of Landslide Susceptibility: A Case Study in Enshi County, Hubei, China Z. Wang et al. 10.3390/ijerph19159412
- 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
- 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
- The influence of spatial patterns in rainfall on shallow landslides H. Smith et al. 10.1016/j.geomorph.2023.108795
- Estimating global landslide susceptibility and its uncertainty through ensemble modeling A. Felsberg et al. 10.5194/nhess-22-3063-2022
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- Multi-event assessment of typhoon-triggered landslide susceptibility in the Philippines J. Jones et al. 10.5194/nhess-23-1095-2023
19 citations as recorded by crossref.
- Refined Zoning of Landslide Susceptibility: A Case Study in Enshi County, Hubei, China Z. Wang et al. 10.3390/ijerph19159412
- 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
- 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
- The influence of spatial patterns in rainfall on shallow landslides H. Smith et al. 10.1016/j.geomorph.2023.108795
- Estimating global landslide susceptibility and its uncertainty through ensemble modeling A. Felsberg et al. 10.5194/nhess-22-3063-2022
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- Multi-event assessment of typhoon-triggered landslide susceptibility in the Philippines J. Jones et al. 10.5194/nhess-23-1095-2023
Latest update: 04 Dec 2023
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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