A GRASS GIS based Shell script for Landslide Susceptibility


Landslides are an environmental phenomenon of great socio-economic signi ficance in
many world regions. For this reason they attract the interest of a wide range of
professionals, including engineers, geologists, geomorphologists, planners and policy
makers. Besides the studies to improve investigation techniques and mitigative measures,
there has been a constant development of quantitative methods to assess the probability of
future landslide occurrence.

These methods can be divided into two main distinct
categories: the deterministic and the statistical methods. The former base their predictions
on empirical geotechnical laws that require the collection of geotechnical parameters. The
extreme variability in three dimensional space of geotechnical characteristics means that
their application to wide areas tends to be expensive and so this kind of analysis is usually
limited to small areas and, more often than not, to single slopes. The statistical methods,
on the other hand, and especially the multivariate ones, appear to be better suited for
assessing landsliding probability on a regional scale.

In recent decades a remarkable leap
forward has been made with these methods because of the diffusion of progressively
more efficient and cheaper GISs. Since the early 1970s, dozens of papers proposing many
different GIS based procedures for the assessment of future landslide probability have
been published. A thorough examination of the methodological aspects, together with
examples and exhaustive reference lists, can be found in Carrara et al .

[1], Soeters and
van Westen [2] and Guzzetti et al. [3] to quote just the most recent works. All the
proposed methods are based on the assumption that ‘slope-failure in the future will be
more likely to occur under those conditions which led to past and present instability’ [1].
In other words, landslide prediction for areas currently free of landslides is effected by
evaluating the similarity between the conditions in such areas and those conditions that
have led to landslides in the past. Therefore the conceptual model consists in:

1) The mapping of the landslides.
2) The mapping of a set of environmental factors which are supposed to be directly or
indirectly correlated with slope instability.
3) The classification of the land surface according to the degree of landslide susceptibility
on the basis of the detected statistical relationships between instability factors and
instability phenomena.


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