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This paper presents decision-making risk estimation based on planimetric large-scale map data, which are data sets or databases which are useful for creating planimetric maps on scales of 1:5,000 or larger. The studies were conducted on four data sets of large-scale map data. Errors of map data were used for a risk assessment of decision-making about the localization of objects, e.g. for land-use planning in realization of investments. An analysis was performed for a large statistical sample set of shift vectors of control points, which were identified with the position errors of these points (errors of map data). In this paper, empirical cumulative distribution function models for decision-making risk assessment were established. The established models of the empirical cumulative distribution functions of shift vectors of control points involve polynomial equations. An evaluation of the compatibility degree of the polynomial with empirical data was stated by the convergence coefficient and by the indicator of the mean relative compatibility of model. The application of an empirical cumulative distribution function allows an estimation of the probability of the occurrence of position errors of points in a database. The estimated decision-making risk assessment is represented by the probability of the errors of points stored in the database
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