In the process of development and modernisation or updating lands or buildings register database the knowledge of the accuracy of analytical determination of areas is required. The knowledge of accurately determined areas is also indispensable for other activities, as e.g. in the case of geodetic maintenance of investments or in the process of control of direct subsidies for agriculture, which are performed within the Integrated Administration and Control System (IACS). In the case of double determination of area of an object, basing on co-ordinates of its vertices, determined from two independent measurements of the same accuracy, the results of calculations differ from one another. The value of that difference, generated in the natural way - following the law of error propagation - should be discussed with respect to its permissibility. This paper presents the analysis of technical and legal regulations, which are obligatory in Poland and which concern permissible errors of analytical determination of areas. Then, a method of determination of values of permissible differences of double determination of areas of cadastral (and other) objects basing on co-ordinates of vertices, under the assumption that those areas are determined with obligatory accuracy (i.e. which total error of position of a point does not exceed O. I O m) and with consideration of shapes of a geometrical object and its area is presented. A formula, which defines the maximum value of the permissible difference of double calculation of an area, which is the function of the parcel area, its shape and the accuracy of determination of position of vertices, has been proposed. Results obtained with the use of the proposed formula were then compared with those obtained with the use of the formula, which recently is obligatory in Poland, as well as other formulae acquired from professional literature. It has been proved that in order to record areas of cadastral objects according to existing regulations, the accuracy of determination of position of border points, should be considerably improved.

The paper presents estimation of positional accuracy of digital maps using statistical analysis. Investigations have been performed for four large-scale digital maps made using different methods of producing digital map data: new total station survey (object A), re-calculation of previous direct measurements (orthogonal and polar surveys) (object B), manual vectorisation of a raster orthophotomap image (object C) and graphical-and-digital processing of analogue maps (object D). Analysis has been performed for large statistical samples of sets of vectors of shift t: L of control points and their components, i.e. true errors t: x, t: r of increments of co-ordinates. In the case of a map produced by means of new survey with an electronic tacheometer, the true errors were represented by differences between co-ordinates of control points obtained from two separate set outs. In the case of other methods of data collection for digital map production true errors were represented by differences of co-ordinates acquired from an investigated map and co-ordinates calculated from new direct surveys.

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