The article concentrates on problems of land/real estate degradation in Belarus, as well as on the ways of solving them by means of land management. The analysis of various documents resulted in the conclusion that there is a lack of a unified conceptual and terminological framework with regard to the following terms and concepts: ''degradation'', ''land degradation'', ''degraded lands'', ''land conservation/protection'', ''real estate degradation'' and others. The concepts of ''land parcel'' and ''real estate unit'' are compared. As an effective tool for combating degradation of land and real estate the article offers more efficient use of land management system developed for this purpose, as well as other legislative, institutional, organizational and technological measures.

The study aimed to develop a methodology for determining zones of intra-field heterogeneity for precision farming. In this study, we took into account the Belarussian national land use system which provides for the absence of private ownership of agricultural land. The spatial distribution of intra-field heterogeneity zones within the land use area of 7549.49 thousand hectares was identified using the analytical hierarchy process (AHP). The algorithm for determining zones of spatial heterogeneity provides for: (1) the selection of indicators and their ranking; (2) developing a pairwise comparison matrix, (3) estimating relative weights and (4) assessing matrix consistency. It is recommended to use data from agrochemical soil studies which are conducted centrally every 4 years for each agricultural enterprise as input parameters. These data include the humus content in the soil, the content of available phosphorus and potassium, soil pH, and the content of B, Cu, Zn, Ca, and Mg. The data should be carefully examined using spatial statistics tools to provide a more accurate delineation of the management-zones boundaries. The developed technique makes it possible to determine fertile and marginal areas within each field and differentiate the use of fertilizers, taking into account the presence of intra-field heterogeneity. This will reduce the total cost of purchasing and applying phosphorus fertilizers by 34 $·haE−1 and potash fertilizers by 9 $·haE−1 due to the redistribution of the fertilizer dose calculated for the planned yield, taking into account the identified site-specific management zones. At the same time, the level of chemical pressure per hectare of arable land will decrease by 6.7% without loss of crops productivity.

All land of the Republic of Belarus can be classified by categories (7 categories), types of lands (14 types), land users, forms of ownership and types of rights to land plots. The total area of land in the Republic of Belarus is 20760 thousand hectares, including agricultural land occupies 9103.0 thousand hectares (43.8%) of the total area of the republic; settlements, horticultural associations, dacha cooperatives – 849.0 thousand hectares (4.1%); industry, transport, communications, energy, defence and other purposes – 622.2 thousand hectares (3.0%); environmental, health, recreational, historical and cultural purposes – 868.7 thousand hectares (4.2%); forest fund – 8656.4 thousand hectares (41.7%); water fund – 37.3 thousand hectares (0.2%); reserve land – 623.4 thousand hectares (3.0%). The basis of the land resources used in the agro-industrial complex of the republic is arable land, meadows and land under permanent crops, which in general occupy 8387.1 thousand hectares, or 40.4% of the total area of land. The state owns 20683.6 thousand hectares (99.63%) of land, private property – 76.4 thousand hectares (0.37%) of the total area of all lands of the republic. In terms of environmental stability, the territory of the republic belongs to medium-stable territories, the coefficient of environmental stability is 0.63, and in terms of the degree of anthropogenic load – to territories with a relatively low anthropogenic load, the coefficient of anthropogenic load is 2.79.

One of the most challenging tasks in modelling of house pricing is to take into account the location factors. Geographically Weighted Regression (GWR) as a local regression model is an extremely effective instrument for spatial data analysis. The aim of the study is to model the relationships between a residential real estate price (per sq.m) and both building and location characteristics for Gomel using GWR. The data of the Belarus’ National Cadastral Agency on real estate transactions (apartments) in Gomel in 2019 are used as initial. The global Moran I index has been used to estimate a spatial autocorrelation of the dependent variable (price per square meter of residential real estate). Several factors having the impact on the apartment sale prices have been determined. Independent variables having been used in analysis can be divided into building characteristics and spatial characteristics. The building characteristics section includes the number of rooms within the property, property area (square meters), building age, number of floors in the building, floor of the property. The spatial characteristics group contains proximity to city centre, recreation areas, supermarkets, bus stops, healthcare and educational facilities. A regression model of housing price in Gomel has been developed. Mapping variable regression coefficients allows exploring spatial features of the impact of the different explanatory variables on the property price. Geographically weighted regression modelling has revealed the pricing peculiarities inherent for certain areas of the city.

The main objective of this study is to review and evaluate three common interpolation methods namely: Inverse Distance Weighting (IDW), Radial Basis Function (RBF) and Ordinary Kriging (OK), and generate maps of soil pH using these methods. The accuracy and efficiency of the generated maps have been examined as well as the most fitting technique for estimating spatial distribution of soil pH in the study area is identified. Studies were 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 is 3197.89 hectares. For the analysis data is used about pHKCl of soil solution obtained from materials of an agrochemical survey executed in 2014. Forecasting and visualization of the spatial distribution of pH sub(KCl) was carried out using the Geostatistical Analyst module of the ArcGIS software. The experimental anisotropic variograms were calculated to determine the possible spatial structure of soil pH. Based on cross-validation results, a polynomial function was identified as the best variogram model. The model created by the method of radial basis functions turned out to be the most suitable for forecasting purposes (the value of the root-mean-square error was 0.763). In terms of interpolation accuracy, the investigated deterministic and geostatistical methods are located in the next descending row: RBF greater than IDW greater than OK.

Nowadays, surveys using unmanned aerial vehicles are becoming popular. The resulting orthophotomap is the final product for creating digital plans and cardboard. The objectives of the study are to study the possibilities of obtaining orthophotomaps from survey materials using unmanned aerial vehicles based on the results of the experiment. The article describes various types of aerial photography. Some types of unmanned flying vehicles to conduct aerial photography for the purpose of monitoring, engineering surveys, inventory of agricultural land, and crop forecasts are considered. A description of aerial photography surveying is given on the example of the city of Dzerzhinsk, Minsk Region, which is performed taking into account the unmanned flying vehicles of GeoScan 201 and the Republican agricultural aero-geodesic unitary enterprise BelPSHAGI. A description of the GeoScan Planner software and basic pre-flight preparation is given. The stages of the preparatory work before the aerial photography, the creation of the planning and high-altitude geodetic justification, the implementation of aerial photography procedures, the steps of the aerial photograph anchorage procedure are considered. Agisoft Photoscan, which allows to get clouds of points, surfaces, 3D models and orthophotomaps using digital raster images are presented. The map of heights (DEM) of the terrain and the orthophotomap was made on the basis of a dense points cloud. According to the results of the research, a conclusion was made on the possibility of using aerial photography materials obtained using unmanned flying vehicles to get orthophotomaps of the required accuracy.

The issue of the study of the problem of determining the geoid and quasi-geoid models is considered. Development of methods for constructing an exact geoid model using different dimensions. Analysis of the calculation of normal heights using satellite measurements, construction of geoid and quasi-geoid models by different methods is performed. Based on the results of the analytical review of existing methods for determining the geoid, it was proposed to use various data (geodetic heights, mixed gravity anomalies, anomalous potential) to construct this model, which allows building a model of a geoid with millimetre accuracy. The possibility of using the collocation method is considered. The task is to develop a methodology for constructing a geoid model using a network of low density gravity points and using pure and mixed gravity anomalies, which allows us to solve the problem of finding potential by solving the Laplace equation or using wavelets.

The aim of the study was to develop a methodology for determining homogeneous territorial zones for precision farming. In this study we took into account the national land use system which provides for the absence of private ownership of agricultural land. The algorithm for determining management-zones provides for: establishing zones of spatial heterogeneity; determining the presence of clusters and emissions; modelling the spatial distribution of soil quality indicators. It is recommended to use data from agrochemical soil studies which are conducted centrally every 4 years for each agricultural enterprise as input parameters. These data include: the humus content in the soil, the content of available phosphorus and potassium and soil pH. The data should be carefully examined using spatial statistics tools to provide a more accurate delineation of the management-zones boundaries. The developed technique makes it possible to determine fertile and marginal areas within each individual field and differentiate the use of fertilizers, taking into account the presence of intra-field heterogeneity. This will save from 2.5 to 21.8 kg P haE−1 and from 0.9 to 26.7 kg K haE−1 due to the redistribution of the fertilizer dose calculated for the planned yield, taking into account the identified site-specific management zones. The differentiated use of mineral fertilizers will increase the profitability of growing winter cereals by 2.2%, sugar beets by 1.3%, rapeseed by 1.1%, and malting barley by 0.8%.

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".

Scientific and technological progress does not bypass any industry, including the agro-industrial complex. With the development of technologies for remote sensing of the Earth, obtaining relevant information about the availability of objects of their condition and use, the introduction of advanced technologies and modern equipment in agriculture, the automation of land management processes, including land management, becomes urgent. Analysis of existing geoinformation systems allows us to conclude that the task of geoinformation support of land management in full in the form of an independent geoinformation system is absent. At the same time, in the considered complexes, there is a solution to certain land management tasks, such as the creation of digital maps of fields, anti-erosion organization of the territory, the construction of digital relief models, correction of soil maps based on satellite images, etc. The purpose of the article is to analyze information sources in the field of geoinformation support of the land management process in the Republic of Belarus, to identify tasks for the development of a comprehensive methodology for the implementation of digital land management in the Republic of Belarus.