Geostatistics provides a set of statistical tools for incorporation the spatial and temporal coordinates of observations in data processing. This course will introduce the main geostatistical tools for description and modeling of spatial variability, and interpolation of environmental attributes (e.g., pollutant concentrations) at unsampled locations. Important topics such as sampling design or the incorporation of different types of information (continuous categorical)in prediction will also be addressed. Homework will consist of small problems to get familiar with the theoretical part of the class, and assignments dealing with the analysis and interpretation of various data sets (soil, water pollution, remote sensing) using the geostatistical software GSLIB. moreover, each student will be asked to read a scientific publication in the field of applied geostatistics and asked to give a short presentation at the end of the term. emphasizing the objectives, methodology, and main findings (merits, drawbacks) of the paper. This course is a prerequisite to a more advanced course CEE 625 on the geostatistical modeling of uncertainty through stochastic simulation and its incorporation of decision making.