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A Simple Method of Mapping Landslides Runout Zones Considering Kinematic Uncertainties
by
Gao, Xing
, Wu, Yuming
, Liu, Jia
, Zhang, Xuehua
in
Algorithms
/ Anisotropy
/ Deformation
/ diffusion angle
/ Energy
/ Friction
/ humans
/ kinematic uncertainties
/ Kinematics
/ landslide runout zone
/ Landslides
/ Landslides & mudslides
/ Mapping
/ Methods
/ microrelief
/ Monte Carlo simulation
/ Particle collisions
/ Propagation
/ Regions
/ Remote sensing
/ Risk assessment
/ Risk reduction
/ rivers
/ semi-empirical method
/ Shear strength
/ Simulation
/ Uncertainty
2022
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A Simple Method of Mapping Landslides Runout Zones Considering Kinematic Uncertainties
by
Gao, Xing
, Wu, Yuming
, Liu, Jia
, Zhang, Xuehua
in
Algorithms
/ Anisotropy
/ Deformation
/ diffusion angle
/ Energy
/ Friction
/ humans
/ kinematic uncertainties
/ Kinematics
/ landslide runout zone
/ Landslides
/ Landslides & mudslides
/ Mapping
/ Methods
/ microrelief
/ Monte Carlo simulation
/ Particle collisions
/ Propagation
/ Regions
/ Remote sensing
/ Risk assessment
/ Risk reduction
/ rivers
/ semi-empirical method
/ Shear strength
/ Simulation
/ Uncertainty
2022
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Do you wish to request the book?
A Simple Method of Mapping Landslides Runout Zones Considering Kinematic Uncertainties
by
Gao, Xing
, Wu, Yuming
, Liu, Jia
, Zhang, Xuehua
in
Algorithms
/ Anisotropy
/ Deformation
/ diffusion angle
/ Energy
/ Friction
/ humans
/ kinematic uncertainties
/ Kinematics
/ landslide runout zone
/ Landslides
/ Landslides & mudslides
/ Mapping
/ Methods
/ microrelief
/ Monte Carlo simulation
/ Particle collisions
/ Propagation
/ Regions
/ Remote sensing
/ Risk assessment
/ Risk reduction
/ rivers
/ semi-empirical method
/ Shear strength
/ Simulation
/ Uncertainty
2022
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A Simple Method of Mapping Landslides Runout Zones Considering Kinematic Uncertainties
Journal Article
A Simple Method of Mapping Landslides Runout Zones Considering Kinematic Uncertainties
2022
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Overview
Landslides can be triggered by natural and human activities, threatening the safety of buildings and infrastructures. Mapping potential landslide runout zones are critical for regional risk evaluation. Although remote sensing technology has been widely used to discover unstable areas, an entire landslide runout zone is difficult to identify using these techniques alone. Some simplified methods based on empirical models are used to simulate full-scale movements, but these methods do not consider the kinematic uncertainties caused by random particle collisions in practice. In this paper, we develop a semi-empirical landslide dynamics method considering kinematic uncertainties to solve this problem. The uncertainties caused by the microtopography and anisotropy of the material are expressed by the diffusion angle. Monte Carlo (MC) simulations are adopted to calculate the probability of each cell. Compared with the existing Flow-R model, this method can more accurately and effectively estimate runout zones of the Yigong landslide where random particle collisions are intense. Combining the D-InSAR technique, we evaluate the runout zones in the Jinsha River from June 2019 to December 2020. This result shows that the method is of great significance in early warning and risk mitigation, especially in remote areas. The source area of the landslide and DEM resolution together affect the number of MC simulations required. A landslide with a larger volume requires a larger diffusion angle and more MC simulations.
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