Stochastic geometry deals with models for random geometric structures.
Its early beginnings are found in playful geometric probability
questions, and it has vigorously developed during recent decades, when
an increasing number of real-world applications in various sciences
required solid mathematical foundations. Integral geometry studies
geometric mean values with respect to invariant measures and is,
therefore, the appropriate tool for the investigation of random
geometric structures that exhibit invariance under translations or
motions. Stochastic and Integral Geometry provides the mathematically
oriented reader with a rigorous and detailed introduction to the basic
stationary models used in stochastic geometry - random sets, point
processes, random mosaics - and to the integral geometry that is needed
for their investigation. The interplay between both disciplines is
demonstrated by various fundamental results. A chapter on selected
problems about geometric probabilities and an outlook to non-stationary
models are included, and much additional information is given in the
section notes.