The article shows that the rapid technological changes in the field of topographic, geodetic and cadastral activities that have occurred in recent decades, significantly affect the nature and content of work to be performed by future engineers in the field of geodesy and land surveying. The directions of adaptation of the content of geodetic and land surveying education to the needs of the national and world market of engineering services are considered. Global navigation satellite system (GNSS), laser 3D-scanning and operational mapping using unmanned aerial vehicles will have a decisive impact on the development of the industry in the near future. Paper maps are being replaced by multimedia devices that display dynamic map content tailored to a specific consumer. During the study, the student must get acquainted with all the most advanced technologies that will determine the future of the industry in the medium term to be ready for their practical application. A modern university lecture should be designed so that the student can hear only what he or she cannot find on the Internet. The aim of the article is to try to comprehensively generalize and analyse global trends and prospects for the development of topographic and geodetic, cadastral, registration and evaluation activities, as well as to determine on this basis the adaptation of geodetic and land management education to the needs of national and global engineering services.

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 need for recreational territories in urban areas has recently become increasingly relevant. In order to create and develop an effective urban green space system, it is necessary to study its main structural components. The aim of the research is to perform the analysis and evaluation of recreational territories of Biržai town. During the research, the territory of Biržai town, green spaces were analysed, the main cadastral data of recreational territories as real estate objects were determined: areas, land use purposes, land use types, special land use conditions and easements. The influence of cadastral indicators in adapting objects to recreation and tourism has been determined. Possibilities of recreational activities in Biržai town were evaluated. Following the SWOT, a generalized analysis of the situation was provided. The performed research revealed that the town of Biržai is dominated by built-up and water-occupied territories. The areas of the territories intended for recreation do not correspond to the areas provided for in the Master plan of Biržai town. The green space system is uneven; the recreational territories do not ensure a full life for the townspeople. The town lacks green spaces adapted to various activities, and the integration of water bodies into the urban living environment is moderate. It is proposed to activate communities in the development of living environment in Biržai.

The construction sector is linked to the general development of a country. There is a lot of data scattered and not properly explored in relation to the buildings constructed. However, if these scattered data on the behaviour of the real estate market are organized, combined with knowledge of civil engineering, this merger of information can mitigate some evaluation problems, especially those that are overvalued for unknown or dubious reasons. Thus, there is a need for models capable of working with limited data to analyse the causal relationships between explanatory variables and sales prices and, from there, predict property values. The purpose of this article is the innovative use of simple building inspection strategies to predict the market price for residential apartments. For this, 19 samples of residential apartments are used in the city of Niterói, Rio de Janeiro, Brazil, in February 2021. The methodology uses the results of the survey of civil engineering and converts them into heuristic terms predicting the price of the property. With this, the imprecision, uncertainty, and subjectivity of human expression combined with the knowledge of civil engineering result in a plausible solution and easy application in the market. Finally, the use of fuzzy logic in the evaluation of properties is an adequate unconventional method, in addition to avoiding repetition in regression coefficients in binary logic. To check the reliability of the method, the comparison between the market values of the samples and the values predicted by the fuzzy logic is used. The result according to the mean absolute percentage error (MAPE) can be interpreted as a good result (7%).