At the moment all three Baltic countries – Estonia, Latvia and Lithuania – use Baltic Normal Height System 1977 as a national height system. But the European Union regulations declared the European Vertical Reference System as a national height system. For height transformation there is a transformation formula for each European country. After calculations it is seen that height difference between Baltic Normal Height System 1977 and the European Vertical Reference System depends on point location in the territory (coordinates). This unequal height difference between both height systems will cause unequal height values on border connection points between the Baltic countries.

Geoportal.lt is a Lithuanian state information system whose scope is to allow all data users to freely access geographic data, maps and e-services. The portal also allows drawing relief altitude profile and set the altitude of point on location. It is performed by applying the tool “Set altitude of point on location”. It is one of the newest tools of geoportal.lt website, whose accuracy has not been analysed, and which, according to the information provided by GIS Centre, complies with the requirements set for 1:50000 scale maps. This tool is selected as an object of research, while the aim of the research is to analyse the accuracy of data provided by Lithuanian spatial information portal tool “Set altitude of point on location” in case of different land covers. The following methods of investigation have been employed: literary analysis; the analysis of cartographic material; field measurements and data processing; comparative analysis of data. The data is processed using Geomap and Microsoft Excel programmes. After the analysis has been carried out, it was established that the most common errors in all types of land covers are from 0.5 m to 1.5 m. Such errors comprise 70 per cent in forest areas, 35 per cent in built-up territory, and 53 per cent in thin land cover. Taking into consideration that the website geoportal.lt operates on the basis of orthographic map whose accuracy is 1 meter and the discussed tool shows the altitude of the nearest known point, it can be stated that the obtained presumptions are permissible. To summarise the obtained data, the tool is reliable. The reliability of the data is 91 per cent in thin land cover, 86 per cent in forest area, 75 per cent in built-up area. To compare it with topographic maps of analogous format, where the errors of altitudes may reach up to 10 meters, the tool is reliable even in case of major errors.

Land cover objects are reflected in a set of georeferential data and are constantly changing. These changes can be accurately examined by computer and interactive information systems. One of the main advantages of computer information systems is the fact that their maps can be constantly improved and updated. The update of georeferential data was conducted in a selected area using the ArcGIS software. After the analysis of the Lithuanian land cover data, the area meeting the following criteria was selected: a diverse landscape, the abundance of different objects (built-up areas, forests, bodies of water), an adjacent city and good access to major metropolitan areas. The article presents the updated georeferential data and tracks changes in the updated data of built-up areas, areas overgrown with trees and shrubs, dams, swimming pools, lakes, ponds and roads in the selected area within the period from 2008 to 2015. The results revealed that changes occurred in all analysed layers. It proves that land cover objects are constantly changing. The greatest change was observed in the data of built-up areas. In comparison with 2008, in 2015 even 41% of built-up areas was changed (i.e. the old boundaries were revised, new and defunct built-up areas were discovered), 125 new areas have overgrown with trees and bushes and 46 changes were observed in ponds and pools.

Global Navigation Satellite System (GNSS) services in Latvia nowadays provide not only for a variety of navigation and surveying needs, but also they are used in agricultural production. The time period when satellite navigation systems equipment and services in agricultural businesses appeared in Latvia and were treated as objects of interest and research has passed. GNSS equipment and enabling modules are purchased, installed and used in agricultural equipment extending their capabilities. A growing number of entrepreneurs provide for this service segment. In the publication of 2014, the authors pointed out that a preparatory and investigation phase in using precision farming systems (including GNSS technology related to them) in Latvia has come to an end transforming into massive practical implementation in the process of agricultural business. The analysis of the obtained information confirmed that during the last year further satellite navigation technology usage in agricultural machinery has grown from simple and approximate level usage to high accuracy and stability navigation services. Growth dynamics and its further development forecasted earlier by the authors coincided with the last year’s actual development indicators of a stable and growing demand for global navigation system services for farming machinery and technical solutions for their user segment. The aim of the article is to justify the forecast expressed in the last year’s publication regarding the increase of the use of precision farming systems thus confirming the fact that their application has moved from a research phase to massive practical implementation and operation in agricultural production.

The possibilities of using the geospatial analysis methods for visualizing land monitoring data and modelling the spatial distribution of the main agrochemical soil indicators are discussed in the article. The research was conducted within the limits of land use of RUP “Uchkhoz BGSHA” (Republic of Belarus, Mogilev region, Goretsky district). The total area of the surveyed territory was 3187.0 hectares. The geospatial analysis of the spatial distribution of humus, mobile phosphorus, mobile potassium and pHKCl was carried out using the Geostatistical Analyst module of the ArcGIS software. Semivariograms were used as the main tool for studying the structure of the spatial distribution of agrochemical indicators. The exponential function was identified as the best variogram model, the type of the circle was standard, the type and the number of sectors was 4 with a displacement of 450, and the lag was 200 metres. The interpolation accuracy was determined from the mean error (ME), mean square error (RMSE) and standard error (RMSS). The universal kriging method was used to perform the forecast and visualize the spatial distribution of agrochemical indicators. The multivariate analysis was performed using the functionality of the Raster Calculator tool, Principal Component analysis and Maximum Likelihood Classification. The search and determination of areas of sites with the most optimal agrochemical indicators were carried out by the multifactor analysis in the GIS environment. Calculation of the area of each circuit within the limits of working parcels was carried out using the utility "Zone Statistics".