# 18.34. Predicting landslides¶

Paolo Cavallini’nin kattığı modül - Faunalia <https://www.faunalia.eu> _

Not

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 greatest predicted risk of rainfall: SAGA ‣ Raster statistics with polygons (the parameters of interest are Maximum and Mean)