Module contributed by Paolo Cavallini - Faunalia

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This chapter shows how to create an oversimplified model to predict the probability of landslides.

First, we calculate slope (choose among various backends; the interested reader can calculate the difference between the outputs):

*GRASS ‣ r.slope**SAGA ‣ Slope, Aspect, Curvature**GDAL Slope*

Then we create a model of predicted rainfall, based on the interpolation of rainfall values at meteo stations:

*GRASS ‣ v.surf.rst*(resolution: 500 m)

The probability of a landslide will be very roughly related to both rainfall and slope (of course a real model will use more layers, and appropriate parameters), let’s say `(rainfall * slope )/100`:

*SAGA ‣ Raster calculator*rain, slope:`(a*b)/100`(or:*GRASS ‣ r.mapcalc*)- then let’s calculate what are the municipalities with the greates predicted risk of rainfall:
*SAGA ‣ Grid statistics with polygons*(the parameters of interest are*Maximum*and*Mean*)