The key features of the blockchain databases, such as decentralization, distribution, security, and record of the history of all transactions, create significant prospects for their application in the field of cadastre and real estate registration activities, including creation of the global real estate cadastre infrastructure, which will be able to go beyond national legal systems and jurisdictions. The conceptual approach to registration of land plots as spatial objects using blockchain technology is proposed. The land plot should be considered as a combination of smart contracts between landowners, surveyors, appraisers, notaries and other persons. The subject of such contracts will be the description and establishment of spatial (plot boundaries, territorial zones, etc.) and other (property rights and encumbrances, monetary valuation, soil bonitet, etc.) characteristics of land plots. The classification of such smart contracts reliability is also presented.

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".