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Titel |
Cellular Automata Models Applied to the Study of Landslide Dynamics |
VerfasserIn |
Luisa Liucci, Laura Melelli, Cristian Suteanu |
Konferenz |
EGU General Assembly 2015
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Medientyp |
Artikel
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Sprache |
Englisch
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Digitales Dokument |
PDF |
Erschienen |
In: GRA - Volume 17 (2015) |
Datensatznummer |
250107249
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Publikation (Nr.) |
EGU/EGU2015-6944.pdf |
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Zusammenfassung |
Landslides are caused by complex processes controlled by the interaction of numerous
factors. Increasing efforts are being made to understand the spatial and temporal evolution of
this phenomenon, and the use of remote sensing data is making significant contributions in
improving forecast.
This paper studies landslides seen as complex dynamic systems, in order to
investigate their potential Self Organized Critical (SOC) behavior, and in particular,
scale-invariant aspects of processes governing the spatial development of landslides
and their temporal evolution, as well as the mechanisms involved in driving the
system and keeping it in a critical state. For this purpose, we build Cellular Automata
Models, which have been shown to be capable of reproducing the complexity of real
world features using a small number of variables and simple rules, thus allowing for
the reduction of the number of input parameters commonly used in the study of
processes governing landslide evolution, such as those linked to the geomechanical
properties of soils. This type of models has already been successfully applied in
studying the dynamics of other natural hazards, such as earthquakes and forest
fires.
The basic structure of the model is composed of three modules: (i) An initialization
module, which defines the topographic surface at time zero as a grid of square cells, each
described by an altitude value; the surface is acquired from real Digital Elevation Models
(DEMs). (ii) A transition function, which defines the rules used by the model to update the
state of the system at each iteration. The rules use a stability criterion based on the slope
angle and introduce a variable describing the weakening of the material over time,
caused for example by rainfall. The weakening brings some sites of the system out of
equilibrium thus causing the triggering of landslides, which propagate within the
system through local interactions between neighboring cells. By using different
rates of weakening in space and in time it is possible to represent different rainfall
scenarios and different physical responses of the material, which in the real world are
the consequence of many factors, such as the geomechanical properties and the
water content of soils. (iii) Finally, a driving rule, which allows the system to work
continuously.
The analysis of the resulting space-time patterns shows that these models represent useful
ways of investigating the SOC behavior of landslide dynamics. Geomorphological processes
can thus be studied using altitude values as real input data, and comparing outcomes based on
DEMs of different areas. This approach supports the study of areas for which detailed
information is not available, and for which the investigation of landslide processes is usually
problematic. Implications of model choices in terms of stability criteria, weakening
rates, and space-time weakening patterns are identified by comparing the patterns
produced by different sets of model parameters to those obtained from real datasets. |
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