In earth sciences, natural resource development, and environmental studies, probabilistic models are used for the prediction and the quantification of uncertainties due to sparse sampling, measurement error, or indirect observations of the phenomenon under study. As the observations cannot be considered independent in this context, standard statistical or machine learning approches are not well suited while lacking interpretability. This course aims at giving basic elements for the mathematical modeling of regionalized phenomena by probabilistic methods. It thus provides a first introduction to geostatistics and spatial statistics.