This talk presents the marked point processes as a methodological framework for morphological and statistical characterisation of the pattern ``hidden'' in spatial data. Digital images, environmental data in epidemiology or catalogues of celestial bodies in astronomy are some typical examples of spatial data. This methodology is made of four key elements : probabilistic modelling based on marked point processes, Monte Carlo simulation using tailored Metropolis-Hastings dynamics or perfect sampling, statistical inference and results validation. Examples from remote sensing, cosmology and epidemiology are also given. The speaker would like also to start a scientific debate with the public, about the main advantages and drawbacks of this approach.