  Satellite imagery is now widely used in the defense sector for monitoring
locations of interest. Although the increasing amount of data enables pattern
identification and therefore prediction, carrying this task manually is hardly
feasible. We hereby propose a cased-based reasoning approach for automatic
prediction of rare events on strategic sites. This method allows direct
incorporation of expert knowledge, and is adapted to irregular time series and
small-size datasets. Experiments are carried out on two use-cases using real
satellite images: the prediction of submarines arrivals and departures from a
naval base, and the forecasting of imminent rocket launches on two space bases.
The proposed method significantly outperforms a random selection of reference
cases on these challenging applications, showing its strong potential.
