  Landslide inventories show that the statistical distribution of the area of
recorded events is well described by a power law over a range of decades. To
understand these distributions, we consider a cellular automaton to model a
time and position dependent factor of safety. The model is able to reproduce
the complex structure of landslide distribution, as experimentally reported. In
particular, we investigate the role of the rate of change of the system
dynamical variables, induced by an external drive, on landslide modeling and
its implications on hazard assessment. As the rate is increased, the model has
a crossover from a critical regime with power-laws to non power-law behaviors.
We suggest that the detection of patterns of correlated domains in monitored
regions can be crucial to identify the response of the system to perturbations,
i.e., for hazard assessment.
