Plausible reasoning from spatial observations
  This article deals with plausible reasoning from incomplete knowledge about
large-scale spatial properties. The availableinformation, consisting of a set
of pointwise observations,is extrapolated to neighbour points. We make use of
belief functions to represent the influence of the knowledge at a given point
to another point; the quantitative strength of this influence decreases when
the distance between both points increases. These influences arethen aggregated
using a variant of Dempster's rule of combination which takes into account the
relative dependence between observations.
