This contribution deals with the problem how
contemporary methods of digital image processing can be applied to remote sensing data and
utilized to efficiently model and simulate the generation and spreading of ozone in an
industrial region. The main points thereby are land use classification and the generation
and computation of adequate elevation models. Based on a survey of the capabilities
offered by modern satellites we also analyze in which way adequate informations concerning
actual air pollution caused by traffic can be automatically obtained using image analysis
and pattern recognition.