The complexity of the real world leads to a point where the image represented in the conceptual model in the form of spatial data cannot be made with any accuracy adopted. Recipient of knowledge, therefore, is accompanied by a sense of uncertainty, which may be either stochastic, directly related to the accuracy of the measurement described or cognitive, resulting from the incomplete knowledge of recipient of information and limited possibilities of making measurements with the desired accuracy, which may be characteristic for a statistical sample of the larger population of typical and reproducible objects represented in the model. A sense of uncertainty in the reception of geo-information is inextricably linked with the necessity of gradual simplification of representation of different spatial units to a form of image presented in the Geographic Information Systems (GIS). The article presents ways of defining the spatial data in the form of discrete objects and fields, using the vector and raster method, concepts of uncertainty associated with it, its types, methods of estimation, concepts of accuracy and precision of measurement and modeling techniques of described objects and spatial phenomena, referring both to the classical statistical analysis and probabilistic methods using the theory of fuzzy sets.

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