Articles | Volume 17, issue 7
https://doi.org/10.5194/nhess-17-1159-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/nhess-17-1159-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Prediction of the area affected by earthquake-induced landsliding based on seismological parameters
Helmholtz Centre Potsdam, German Research Center for Geosciences (GFZ), Telegrafenberg, 14473 Potsdam, Germany
now at: Institut de Physique du Globe de Strasbourg, CNRS UMR 7516, University of Strasbourg, 5 rue Descartes, 67084 Strasbourg, France
Patrick Meunier
Ecole Normale Superieure de Paris, Laboratoire de Geologie, 75231 Paris CEDEX 5, France
Niels Hovius
Helmholtz Centre Potsdam, German Research Center for Geosciences (GFZ), Telegrafenberg, 14473 Potsdam, Germany
Institute of Earth and Environmental Science, University of Potsdam, Potsdam, Germany
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Cited
48 citations as recorded by crossref.
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- Effects of finite source rupture on landslide triggering: the 2016 <i>M</i><sub>w</sub> 7.1 Kumamoto earthquake S. von Specht et al. 10.5194/se-10-463-2019
- Analysis of three-dimensional slope stability combined with rainfall and earthquake J. Wang et al. 10.5194/nhess-24-1741-2024
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- Improving earthquake prediction accuracy in Los Angeles with machine learning C. Yavas et al. 10.1038/s41598-024-76483-x
- Insights into the geohazards triggered by the 2017 Ms 6.9 Nyingchi earthquake in the east Himalayan syntaxis, China B. Zhao et al. 10.1016/j.catena.2021.105467
- Morphology, timing, and drivers of post‐glacial landslides in the northern Yellowstone region J. Dixon et al. 10.1002/esp.5943
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- Assessment of attenuation regressions for earthquake-triggered landslides in the Italian Apennines: insights from recent and historical events F. Livio & M. Ferrario 10.1007/s10346-020-01464-w
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- Landslide mapping with remote sensing: challenges and opportunities C. Zhong et al. 10.1080/01431161.2019.1672904
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48 citations as recorded by crossref.
- Initial insights from a global database of rainfall-induced landslide inventories: the weak influence of slope and strong influence of total storm rainfall O. Marc et al. 10.5194/esurf-6-903-2018
- Geomorphic and tectonic controls of landslides induced by the 2022 Luding earthquake B. Zhao et al. 10.1007/s11629-022-7732-8
- Valuable Clues for DCNN-Based Landslide Detection from a Comparative Assessment in the Wenchuan Earthquake Area C. Li et al. 10.3390/s21155191
- Machine Learning Prediction of Co-Seismic Landslide with Distance and Azimuth Instead of Peak Ground Acceleration Y. Shi et al. 10.3390/su16198332
- 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
- Effects of finite source rupture on landslide triggering: the 2016 <i>M</i><sub>w</sub> 7.1 Kumamoto earthquake S. von Specht et al. 10.5194/se-10-463-2019
- Analysis of three-dimensional slope stability combined with rainfall and earthquake J. Wang et al. 10.5194/nhess-24-1741-2024
- Comparative analysis of disaster information website based on web usability evaluation and quality content of disaster information I. Agus Riyanto et al. 10.1051/e3sconf/20197603009
- Coseismic landslides triggered by the 8th August 2017 Ms 7.0 Jiuzhaigou earthquake (Sichuan, China): factors controlling their spatial distribution and implications for the seismogenic blind fault identification X. Fan et al. 10.1007/s10346-018-0960-x
- Modeling of earthquake-induced landslide distributions based on the active fault parameters C. Chen et al. 10.1016/j.enggeo.2022.106640
- Improving earthquake prediction accuracy in Los Angeles with machine learning C. Yavas et al. 10.1038/s41598-024-76483-x
- Insights into the geohazards triggered by the 2017 Ms 6.9 Nyingchi earthquake in the east Himalayan syntaxis, China B. Zhao et al. 10.1016/j.catena.2021.105467
- Morphology, timing, and drivers of post‐glacial landslides in the northern Yellowstone region J. Dixon et al. 10.1002/esp.5943
- Two multi-temporal datasets that track the enhanced landsliding after the 2008 Wenchuan earthquake X. Fan et al. 10.5194/essd-11-35-2019
- Evaluation of road network slopes susceptibility to seismically-induced landslides in the Granada Basin (S Spain) J. Román-Herrera et al. 10.3389/feart.2023.1226894
- Statistical analyses of landslide size and spatial distribution triggered by 1990 Rudbar-Manjil (Mw 7.3) earthquake, northern Iran: revised inventory, and controlling factors A. Ghaedi Vanani et al. 10.1007/s10064-021-02106-8
- The added value of a regional landslide susceptibility assessment: The western branch of the East African Rift A. Depicker et al. 10.1016/j.geomorph.2019.106886
- Interrelated impacts of seismic ground motion and topography on coseismic landslide occurrence using high-resolution displacement SAR data Y. Sakai et al. 10.1007/s10346-022-01909-4
- Numerical analysis of environmental influences on evaporation in a cracked soil slope Z. Zeng et al. 10.1016/j.compgeo.2024.106126
- Coseismic Debris Remains in the Orogen Despite a Decade of Enhanced Landsliding L. Dai et al. 10.1029/2021GL095850
- Spatial Patterns of Storm‐Induced Landslides and Their Relation to Rainfall Anomaly Maps O. Marc et al. 10.1029/2019GL083173
- Remote Sensing for Assessing Landslides and Associated Hazards C. Lissak et al. 10.1007/s10712-020-09609-1
- The Importance of Rock Mass Damage in the Kinematics of Landslides D. Donati et al. 10.3390/geosciences13020052
- Long-term erosion of the Nepal Himalayas by bedrock landsliding: the role of monsoons, earthquakes and giant landslides O. Marc et al. 10.5194/esurf-7-107-2019
- Seismic and geological controls on earthquake-induced landslide size A. Valagussa et al. 10.1016/j.epsl.2018.11.005
- Toward Using Seismic Interferometry to Quantify Landscape Mechanical Variations after Earthquakes O. Marc et al. 10.1785/0120200264
- Seismic and geologic controls on spatial clustering of landslides in three large earthquakes C. Rault et al. 10.5194/esurf-7-829-2019
- Suspended Sediments in Chilean Rivers Reveal Low Postseismic Erosion After the Maule Earthquake (Mw 8.8) During a Severe Drought V. Tolorza et al. 10.1029/2018JF004766
- Statistical analysis of the landslides triggered by the 2021 SW Chelgard earthquake (ML = 6) using an automatic linear regression (LINEAR) and artificial neural network (ANN) model based on controlling parameters A. Vanani et al. 10.1007/s11069-023-06240-2
- A review of recent earthquake-induced landslides on the Tibetan Plateau B. Zhao et al. 10.1016/j.earscirev.2023.104534
- Variation in landslide-affected area under the control of ground motion and topography H. Tanyaş & L. Lombardo 10.1016/j.enggeo.2019.105229
- A web-based GIS (web-GIS) database of the scientific articles on earthquake-triggered landslides L. Schilirò et al. 10.5194/nhess-23-1789-2023
- Stability Analysis of a Water‐Rich Slope Under Seismic Disturbance S. Li et al. 10.1155/2024/8894948
- Increase in landslide activity after a low-magnitude earthquake as inferred from DInSAR interferometry S. Martino et al. 10.1038/s41598-022-06508-w
- Stability evaluation of slope subjected to seismic effect combined with consequent rainfall Y. Chen et al. 10.1016/j.enggeo.2019.105461
- Satellite-based emergency mapping using optical imagery: experience and reflections from the 2015 Nepal earthquakes J. Williams et al. 10.5194/nhess-18-185-2018
- Dynamic response of the Daguangbao landslide triggered by the Wenchuan earthquake with a composite hypocenter F. Cui et al. 10.1080/19475705.2021.1944916
- Predictive Modeling of Earthquakes in Los Angeles With Machine Learning and Neural Networks C. Emre Yavas et al. 10.1109/ACCESS.2024.3438556
- Hazard and risk assessment of earthquake-induced landslides—case study J. Bojadjieva et al. 10.1007/s10346-017-0905-9
- 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
- Assessment of attenuation regressions for earthquake-triggered landslides in the Italian Apennines: insights from recent and historical events F. Livio & M. Ferrario 10.1007/s10346-020-01464-w
- Competing Effects of Mountain Uplift and Landslide Erosion Over Earthquake Cycles G. Li et al. 10.1029/2018JB016986
- Probabilistic seismic source inversion from regional landslide evidence R. Rasanen & B. Maurer 10.1007/s10346-021-01780-9
- Towards identification of sediment sources, and processes of sediment production, in the Yarlung-Tsangpo-Brahmaputra River catchment for reduction of fluvial sediment loads R. Wasson et al. 10.1016/j.earscirev.2022.103932
- Landslide mapping with remote sensing: challenges and opportunities C. Zhong et al. 10.1080/01431161.2019.1672904
- Evaluating the post-earthquake landslides sediment supply capacity for debris flows W. Jin et al. 10.1016/j.catena.2022.106649
- Earthquake-induced landslides in Haiti: analysis of seismotectonic and possible climatic influences H. Havenith et al. 10.5194/nhess-22-3361-2022
- Landslide kinematics inferred from in situ measurements: the Cliets rock-slide (Savoie, French Alps) M. Desrues et al. 10.1007/s10346-021-01726-1
Latest update: 20 Nov 2024
Short summary
We present an analytical expression for the surface area of the region within which landslides induced by a given earthquake are distributed. The expression is based on seismological scaling laws. Without calibration the model predicts, within a factor of 2, up to 49 out of 83 cases reported in the literature and agrees with the smallest region around the fault containing 95 % of the total landslide area. This model may be used for hazard assessment based on early earthquake detection parameters.
We present an analytical expression for the surface area of the region within which landslides...
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