The media frequently refers to the concept of abandoned land. The reasons for its occurrence are discussed and the ways to diminish the problem are being searched for. Various sources of information were used for the research. They enabled the authors to identify the concept of abandoned lands. In addition, the situation of abandoned lands was analysed and causes of occurrence of such lands in one cadastral area of mid-Lithuania municipality were defined. According to the set of data, concerning abandoned lands (AŽ_DRLT), the data, provided in the mentioned data set and the data obtained during field testing were compared. The survey of the terrain was conducted in the early autumn of 2013 and repeated in the late spring of 2014. In order to find out why the land was abandoned, the surveyor of cadastral area was additionally interviewed. On the basis of the latest data of 2014, 123 spaces of abandoned lands, which occupy 59.74 ha, were found in Sujainai cadastral area. Having analysed the set of abandoned land data, it was identified that boundaries of 95 abandoned plots corresponded to the situation in the area, whereas boundaries of 28 areas should be corrected. Moreover, the abandoned areas that had not been marked were found while the land abandonment in the terrain was obvious. Although the amount of abandoned land is decreasing in both the area analysed and throughout Lithuania, the situation is not favourable. Having conducted the research, it was found that the main reasons for land abandonment in Sujainai cadastral area were as follows: poor fertility in non-productive lands (up to 32 points) and reclamation; no potential land consumers, purchasers or tenants of land areas of high productivity or it is complicated and expensive to pursue agricultural activity there.

Economic and social problems and emerged threat to human life are the main reasons for abandonment of buildings or even the whole cities in different countries. Mainly abandoned buildings are found in the USA and in the countries of the former Soviet Union. Abandoned buildings in Kaunas city are analysed in the article; their condition is assessed and the ways for handling are proposed. The legal status and the purpose of use of abandoned buildings in Kaunas city are also defined. There are 46 abandoned buildings in Kaunas city. The majority of them are located in Šančiai neighbourhood, but the least amount – in Vilijampolė and Gričiupis neighbourhoods. As regards the purpose of the use, 85 percent of abandoned buildings in Kaunas city are attributed to non-residential buildings, and 44 percent of them are former industrial buildings. Due to the condition of constructions, threat to people and environment, as well as visual appearance, the state of 72 percent of abandoned buildings is poor. 52 percent of abandoned buildings are ascribed to be demolished, while the remaining 48 percent of buildings could be repaired or renovated.

Development and management of green area systems is important to both the environment and a person. It bears social, economic, and ecological significance. This system must comply with principles of sustainable spatial development. Therefore, well-developed systems of green areas must become the basic aim of all cities. Marijampolė, the seventh biggest city of Lithuania was selected as the research object. In the article the system of Marijampolė city green areas is analysed. Two surveys, which included questionnaires, were conducted, i.e. city inhabitants and territory-planning and management specialists were interviewed. It was identified that the system of Marijampolė green areas is not balanced and there are enough green areas only in part. However, the current parks, squares and other green spaces do not ensure full-fledged citizens’ life. Marijampolė lacks equipped, applied to various activities local green areas for different age groups of the community, the development and maintenance of which must primarily be the inhabitants’ concern.

Some tasks require identification of landmarks in districts beyond the reach of existing optical observation facilities. The accuracy of their determination significantly affects the effectiveness of the use necessary equipment during the task. In the paper an algorithm to determine the object parameters using a flying platform is offered. An observation point is installed which is equipped with a navigation system to solve this task. This ensures its orientation and positioning. From the observation point an aerial observation point is displayed. It is suggested to use a flying platform. The coordinates of the flying platform are determined relative to the observation point; the coordinates of the landmarks are determined relative to the flying platform. The mathematical model of the estimation error determination of object coordinates with the help of a flying platform is proposed. The analysis of errors in determining the parameters of the object using a flying platform is conducted. Analysis of the results of mathematical modelling is conducted using the package of applications Mathcad. The dependence of these parameters on the relative position of the observation point, platforms and object is examined. It is shown that the main contribution to the error of determining the coordinates of the landmark is given by the errors of determining the observation point location and measuring the range. An analytical correlation is obtained, which allows to estimate the errors of determining the coordinates of the landmark using the flying platform with known errors in determining the observation point coordinates and the range determination of the range finder.

The zones of ecological trouble cover about 15% of the territory of Russia, where the main production capacities and the most productive agricultural lands are concentrated. The Samara region is characterized by a distinct natural zonality from a typical forest-steppe in the North with a forest cover close to 30%, to an open dry steppe in the South with a natural forest cover of only 0.1...0.2%. The article presents an analysis of land use in the Samara region on the example of the Borsky municipal district. Research methods include environmental analysis and statistical data analysis.The article presents an analysis of the land use of the Borskiy municipal district. During zoning, the territory of the district is divided into the northern, central and southern parts. Assessment of environmental and economic parameters showed heterogeneity of the territory and the need for detailed consideration of climatic, soil, economic conditions in the design of landscape optimization systems, even in the municipal area. In general, the district's land fund experiences an average anthropogenic load, the ecological stability of the territory as a whole is characterized as unstable stable. In comparison with other areas of the Central MES, the municipal Borskiy district belongs to the category with an average ecological intensity with a stabilization index of 0.59 units due to the beneficial influence of the Buzuluksky area.

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".