The article describes the procedure for transformation between old and new horizontal geodetic datum in Bosnia and Herzegovina. Two triangle-based methods were used for transformation, which are based on irregular and regular triangular network. For development of transformation models two set of points were used, one for developing models (around 1200 points), and other for testing (around 850 points). Prior to development, all points were tested at presence of outliers, and outliers are marked in the points database. Results shows that large part of distortions in old triangulation network can be modeled with used methods. Maximal positional standard deviations with best model are 4.5 and 6.4 cm for two sets of points, respectively, while maximal positional discripencies are 30 and 40 cm for two sets of points. Each method has some advantages and disadvantages which are shown in this article. It is shown that the number, spatial distribution and quality of input data are crucial for development of highly accurate transformation model. Also, as an important contribution of this work, some problematic areas with irregular distortions are identified. Finally, some recommendations are given for improvement of developed models.

: T ime series data of GNSS point positioning are considerably used for the purpose of geophysical research. The velocity estimates and their uncertainties deriv e from time series data of GNSS point positioning affected by seasonal signals and the stochastic noise, contained in the series. D ata cleaning of GNSS time series is a prerequisite for the noise characterization and analysing. In this article one point positioning of time series was analysed in four different periods during the five year interval. The noise characteristics were estimated for all periods. By applying Lomb - Scargle algorithm the comparable results were also provided. Lomb - Scargle algorithm used to estimate the spectral strength density of unequal sampled data is a typical tool for this kind of analysis. S pectral indices have been estimated before cleaning data and after removing linear, annual and semi - annual signals and outliers. T he spectral indices estimated from time series data of GNSS point positioning were located in the area of fractional Gaussian noises , and stationary stochastic process was described for the whole research time period.

Troposphere plays crucial role for geodetic comunity, which can primarly be seen in its influence on GNSS observations. At the same time, troposhpere is the place where almost all hidrometeorological phenomena that effect our everyday life occure. Scientists have found a way to use systematic influence that troposphere has on GNSS signal and turn it into meteorological indicator, water vapor quantity. In this paper term of GNSS meteorology is described, as well as its basic classification and application.