For the implementation of direct measurements, proper understanding of the existing relationships and spatial variability, and at later stages, for obtaining reliable results of geostatistical analysis, adequate planning network measurement and correct placement of, and/or the evaluation of the number of measurement points in the measurement network are not the only necessary conditions. Another key prerequisite is choosing the right model for creating a DTM, which depends on the shape of the terrain. Correct spatial sampling should provide much information on the spatial distribution of the studied variable in an area, at minimal cost and with minimal effort. Faithful reproduction of the land surface that reflects any of the characteristics of the environment is not possible through DTM, due to a number of restrictions, manifesting themselves in the form and size of the data set; due to time and economic constraints; and also because the full complexity of the terrain’s surface cannot be measured or expressed. The present work undertakes to analyse the density and distribution of measuring points on four areas that have specific characteristics in common, yet they remain different in terms of surfaces, height differences, as well as their complexity. After selecting the research areas, these were designed and laid out in a grid with the shape of rectangles that were similar in structure to the GRID model. The data were analysed using geostatistical interpolation by ordinary kriging, in order to conduct a proper analysis of the distribution and density of the measuring points, to calculate the surface properties of a particular point, and in order to attempt to reduce the workload and cost factor.