The Agricultural Property Agency (APA) was founded on 16 July 2003 pursuant to the provisions of the Act of 11 April 2003 on the establishment of the agricultural system. The APA was established for the purpose of managing the agricultural property of the State Treasury in Poland. Its main tasks included the endorsement of ownership and structural changes relating to agricultural land in rural areas as well as the promotion of social goals. This article focuses on the social aspects of the APA’s operations based on an analysis of the data supplied by the Regional Branch of the APA in Olsztyn. The obtained information and materials were analyzed to identify programs and activities initiated by the Olsztyn branch in pursuit of social goals. The results of the analyses were presented in the table format. Community interviews were conducted and photographs were taken during the field study. The results were used to describe the social aspects of APA’s operations in rural areas.

The purpose of this article is to analyse the rural development land use projects for farmstead site selection prepared in the municipality of Elektrėnai during the period between the years of 2012 and 2016, and to determine their potential impact on the growth of built-up areas and the rational use of land. According to the survey data, it can be stated that drafting rates of rural development land use projects for farmstead site selection tend to grow especially in those municipalities that are close to Vilnius and which have a good geographical position as well as a special landscape and national cultural heritage values (Vilnius district, Trakai district and Elektrėnai district municipalities). Having carried out the agricultural land change analysis, it is noted that during the analysis period (2012 - 2016) in Elektrėnai municipality, similarly to the whole Vilnius county, land utilities structure is dominated by agricultural land, mostly arable land, but the significant trend of agricultural land reduction at the expense of the growth of built-up areas was noticed. During the analysed period the built-up areas in the municipality of Elektrėnai increased even by 6 times, and the area of agricultural land declined on average, by almost 2 percent every year. A detailed analysis of specific projects and information gathered during qualitative research suggest that the prepared rural development land use projects for farmstead site selection are not prepared for the improvement of the actual farming activity conditions in constructing farm and other buildings.

The article presents the comparative analysis of the Kaunas city anthropogenic landscape change during the period between 2006 and 2014. For this analysis the land fund statistics of the Republic of Lithuania were used. The components of anthropogenic landscape change are graphically shown in the figures. During the analysis the Kaunas city statistics were compared with the data of Kaunas County and the Republic of Lithuania. Comparative, analytical as well as statistical and logical analysis methods were used for the investigation. The object of the investigation is anthropogenic components of Kaunas city. The aim of the investigation is to carry out the analysis of the change of Kaunas city anthropogenic components in the period of 2006-2014. The work analyses the change of urban landscape components, the reasons of the established change. The built up territories comprise the majority of anthropogenic landscape of Kaunas city i.e. 90.05 per cent, while the damaged territories make up 0.06 per cent and Kaunas city roads constitute 9.89 per cent of the analysed landscape. It was established that during the analysed period the built-up territories of Kaunas city increased by 312.78 ha i.e. 3.53 per cent. Within 9 years the road area increased by 14.04 ha or 1.44 per cent, while the damaged areas increased by 1.89 ha. Having analysed the statistical data of Kaunas city anthropogenic landscape areas it was estimated that within the period of 2006 -2014 the area of these territories increased by 328.71 ha or 3.34 per cent. e area of these territories increased by 328.71 ha or 3.34 per cent.

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.

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 study aimed at examining the spatial pattern of residential densification in housing submarkets of Bida, an ancient traditional town in Nigeria. The study adopted the 2015 standard residential density of Niger State Urban Development Board to determine the level of residential density and occupancy rates of the various submarkets of the town. The study also adopted primary method of data collection through the use of satellite images, handheld GPS and georeferencing of demarcated areas and the buildings, using point features and vector approach in ArcGIS environment to achieve the area coverage, number of buildings and buildings per hectare (ha) in the housing submarkets. The finding of the study reveals that in 2008 Town housing submarket has the highest area coverage, followed by the Project Quarters and then GRA, but in terms of residential density, four housing submarkets of Town, Rahmatu Dangana, Gbazhi and Wadata have high densities above the other seven submarkets. The study further reveals that in the year 2013, additional eight housing submarkets have high residential densities, GRA medium density while Eyagi and Prject Quarters had low densities respectively. It was therefore recommended that there is the need for rational densification (planned densification) for urban development in order to check the increasing unplanned residential density that reduces the green and open spaces in urban environment.

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%).

Renovation is seen in the context of an urbanist as a form of large-scale dispersed urban space reorganization. To date, in countries with developed economies, the share of renovation works has increased in the structure of construction from 35% to 60%. In this article, the content of the main stages of renovation is detailed: the definition of the scope, planning, financing and implementation. The article reflects the experience and tasks of the Moscow Government on the renovation of the quarters of the existing buildings. Since the city renovation projects are aimed at achieving the optimal combination of social, residential and commercial functions, the complex reconstruction of the city has noneconomic and economic effects. Varying the key parameters influences the calculation of the project economy. The most economical indicators of the project depend on the coefficients of renovation and relocation, the cost of construction and the price of sales. To increase the additions in Moscow budget and other economic effects from the project implementation, it is necessary to increase the renovation ratio and the selling price and/or reduce the construction cost and resettlement ratio.

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.