Search Results (34)

3D (three-dimensional) property volume is an important data carrier for 3D land administration by using 3D cadastral technology, which can be used to express the legal space (property rights) scope matching with physical entities such as buildings and land. A 3D property volume is represented by a dense set of 3D coordinate points arranged in a predefined order and is displayed alongside the parcel map for reference and utilization by readers. To store a 3D property volume in the database, it is essential to record the connectivity relationships among the original 3D coordinate points, the associations between points and lines for representing boundary lines, and the relationships between lines for defining surfaces. Only by preserving the data structure that represents the relationships among points, lines, and surfaces can the 3D property volume in a parcel map be fully reconstructed. This approach inevitably results in the database storage volume significantly exceeding the original size of the point set, thereby causing storage redundancy. Consequently, this paper introduces a reversible 3D property volume compression coding method (called 3DPV-CC) to address this issue. By analyzing the distribution characteristics of the coordinate points of the 3D property volume, a specific rule for sorting the coordinate points is designed, enabling the database to have the ability of data storage and recovery by merely storing a reordered point set. The experimental results show that the 3DPV-CC method has excellent support capabilities for 3D property volumes of the vertical and slopped types, and can compress and restore the coordinate point set of the 3D property volume for drawing 3D parcel maps. The compression capacity of our method in the test is between 23.66% and 38.42%, higher than the general data compression methods (ZIP/7Z/RAR: 8.37–10.32%). By means of this method, land or real estate administrators from government departments can store 3D property volume data at a lower cost. This is conducive to enhancing the informatization level of land management. Full article

The world is characterised by the growing volumes and flow of goods, which, amid benefits to economic development, result in negative externalities affecting the sustainability of cities. Although numerous studies have analysed the locational patterns of logistics facilities in cities, further research is required to examine their real estate patterns and trends. The aim of the paper is, therefore, to analyse the value of land accommodating logistics facilities in the City of Cape Town municipality, South Africa. Given the lack of dedicated geo-spatial data, logistics firms were searched on Google Maps, utilising a combination of aerial photography and street view imagery. Three main attributes of land parcels hosting logistics facilities were thereafter captured from the municipal cadastral information: property extent, street address, and property number. The latter two were used to extract the 2018 and 2022 property market values from the valuation rolls on the municipal website, followed by statistical, spatial, and geographically weighted regression (GWR) analyses. Zones near the central business district and seaport, as well as areas with prime road-based accessibility, had high market values, while those near the railway stations did not stand out. However, GWR yielded weak relationships between market values and the locational variables analysed, arguably showing a disconnect between spatial planning and logistics planning. Towards augmenting sustainable logistics, it is recommended that relevant stakeholders strategically integrate logistics into spatial planning, and particularly revitalise freight rail to attract investment to logistics hubs with direct railway access. Full article

The possibility of carrying out the cultivation of numerous plant species in vertical farming highlights the need for policy makers to determine the cadastral value of the buildings in which these production activities are carried out. In this regard, estimates of buildings intended to host vertical farming are illustrated according to the procedure established by Italian cadastral legislation, which establishes that the fiscal value of buildings intended for vertical farming must be estimated through their market value. Appraisals is carried out using the direct capitalization method but follow two different approaches. One approach is based on the expertise of the appraiser, who acts by making assessments through subjective and arbitrary choices. The other approach is based on the use of best practices, as indicated by international evaluation standards that follow appropriate methodologies. Our comparison between the two approaches focuses on determining the capitalization rate, which determines the estimated value. The market value estimated using the procedures recognized by the valuation standards appears to be more valid methodologically and more reliable. This is demonstrated by applying yield capitalization to the same income cash flow in both formulations. Additionally, through the identification of the conversion cash flow, useful details on financial flow can be obtained and used to determine the value. The obtained results may be useful for public operators for the purposes of determining the value of assets for tax purposes. More generally, they are also useful from a methodological and application point of view in real estate valuation and support the development of tools for making efficient investment choices. Full article

The preservation of cultural heritage plays a key role in the development of society. To preserve cultural heritage, protection zones are established, which represent an encumbrance on land plots and, therefore, should be taken into account in the valuation process. Currently, there is a problem that mass (cadastral) and individual valuation methods do not necessarily include cultural heritage objects and their zones in cost coefficients. The absence of a mechanism to address their individual characteristics in the real estate valuation system has a significant impact on the value of real estate and leads to unjustifiably inflated market value and, as a consequence, to disputing the results of cadastral valuation. This article is devoted to determining the impact of protection zones of cultural heritage objects on the value of land intended for individual housing construction, using the example of the city of Orenburg. This article considers various methods of identifying patterns of the influence of zones with special conditions of use of the territory on the market value of land and substantiates the use of the method of comparative sales in the conditions of a low-active land market in Orenburg, a statistical analysis of market information, on the basis of which the type of activity of the real estate market in Orenburg was determined. The patterns of the calculation of corrections for the remoteness of the studied land plots from the objects of the transport and social infrastructure of Orenburg were revealed in this work as well. Through the method of paired sales within the framework of an individual assessment of the land plot intended for individual housing construction, the diminishing impact of the zones of protection of cultural heritage objects on the market value of land plots was revealed. This allows for conclusions to be drawn as to whether objects of cultural heritage have an impact on the value of real estate, and as a result, there is a need to modify the applied methods of mass and individual real estate valuation within the boundaries of historical settlements. Full article

States establish ambitious policies and important measures to achieve targets for the energy upgrade of buildings but although some important barriers prevent their implementation in space, they are rather overlooked by research. In this paper, it is argued that extensive multi-ownership (MO) and weak performance of the real estate market in degraded urban areas impede the mass energy retrofitting of multi-owner buildings (MOBs), which are an important part of the urban building stock A deprived area of central Athens (Greece) that serves as a case study. With a pluridisciplinary approach based on extensive field surveys, cadastral data analysis and cases of energy renovation of buildings through a public–private partnership financing scheme as well as ways to overcome the MO issue were explored, according to the provisions of the Greek legal framework. The integrated urban regeneration approach is promoted as a means to encounter the MO issue and enhance the functioning of the real estate market by the generation of surplus values that will render the energy retrofitting of buildings more attractive to investors and thus achieve the deep renovation of MOBs towards the sustainability of the urban environment. This paper ultimately advocates the integration of energy planning with spatial planning. Full article

This article presents a substantiation of methods for assessing the impact of anthropogenic noise pollution for land taxation. Statistical analyses have been carried out in order to establish the dependence of the market value of land plots for residential development in St. Petersburg on noise pollution caused by transport infrastructure facilities. The obtained data allowed us to conclude that in the modern conditions of the imperfect market, the considered factor is externalized. When finding the dependence, it can be included in the economic–mathematical model of cadastral value determination as an internal factor of the market, thus ensuring the principle of fairness of taxation. The lack of market reaction dictates the need to internalize negative environmental externalities through state regulation of land redistribution or redistribution of the tax burden between land rightholders and rightholders of objects that create noise. Full article

The renewal and updating of the cadastre of real estate is a long and tedious task for land administration, especially for rural buildings that lack unified design and planning. In order to retain the required accuracy of all points in the register, huge extensive manual editing is often required. In this work, a precise cadastral survey approach is proposed using Unmanned Aerial Vehicle (UAV) imagery-based stereo point clouds. To ensure the accuracy and uniqueness of building outer walls, the non-maximum suppression of wall points that can separate noise and avoid repeated extraction is proposed. Meanwhile, the multiple cue weighted RANSAC, considering both point-to-line distance and normal consistency, is proposed to reduce the influence of building attachments and avoid spurious edges. For a better description of wall topology, the wall line segment topology graph (WLTG), which can guide the connection of adjacent lines and support the searching of closed boundaries through the minimum graph loop analysis, is also built. Experimental results show that the proposed method can effectively detect the building vector contours with high precision and correct topology, and the detection completeness and correctness of the edge corners can reach 84.9% and 93.2% when the mean square error is below 10 cm. Full article

The urban land administration system (LAS) of any country serves as a key pillar for good governance, resource planning, service delivery, infrastructure development, and revenue collection. To reform their LASs, countries need a thorough understanding of their existing context and global relevance. The goal of this paper is to examine the status and challenges of urban LASs in Pakistan using the United Nations Framework for Effective Land Administration (FELA). The exploratory case study method used in the paper employs a mixed approach, which includes FELA-based questionnaire surveys, group discussions, and desk reviews. A total of 525 urban LAS stakeholders, including owner-buyers, real estate agents, bankers, lawyers, and LAS organizations, participated in the activity. The results show that more than half of the stakeholders are not satisfied with existing urban LASs, their governance and accountability, laws, and policies. Corruption is prevalent mostly in government organizations. Fraud and joint ownership are the most common sources of dispute, with 67 percent of the respondents stating that the cases take more than two years to resolve in court. The financial aspect of urban LASs is suffering due to property undervaluation and low revenue collection. Manual data and record keeping in LASs further complicate the system, with 87 percent of all respondents interested in innovating the urban LAS using modern technologies. Furthermore, 92 percent of all respondents expressed the need to standardize the existing LASs. There is a lack of capacity and skills, and 89 percent of organizations’ respondents believe that human resources skilled in Geographical Information Systems (GIS) and Remote Sensing (RS) can improve the efficiency of urban LASs. There is a lack of partnership among LAS organizations and a gap in the accessibility of LAS-related quality information. The country’s vision of building smart cities can be realized through LAS standardization and 3D and GIS innovation. Full article

Keeping the real estate cadastre’s database up to date is a very important process. The scope of the modernization works includes, among other things, fieldwork and office (chamber) work carried out by surveyors to update information about land and buildings. Therefore, modernization may result in changes to plot areas; changes to the marking of plots and land use (and, consequently, a change in the property tax); and the disclosure or deletion of buildings and premises, as well as changes to their technical data. The research, based on a case study (rural municipality Serniki, Poland), and supported by a literature review, remote sensing, and digital photogrammetry, clearly showed the importance of initiating the cadastre modernization procedure and obtaining funds for this purpose, which will be beneficial for both parties. Landowners will gain by bringing the current image of their real estate closer to the actual state (e.g., by paying taxes for the real utility of the land), while administrative units will become the beneficiaries of higher tax revenues (up to over 500%). Thus, the analysis carried out on the case study shows positive effects for both parties, and justifies the financial outlay incurred by the administrative units for this process. Moreover, the analysis revealed that, due to the possibility of obtaining funding from other sources, the cost to the public administration may be marginal. Thus, the cadastre modernization procedure should be integrated into regional and national policies. Full article

Despite the already advanced work on the construction of jurisdictional 3D cadastre models in many parts of the world and the technical feasibility of building very detailed 3D models of cities, relatively few specialists have focused on the aspects of visualizing property rights in three dimensions. Therefore, to complement the analyses carried out so far in this area, this research aims to investigate the perception of the visualization of multidimensional real estate data using different visual variables and by different audiences. The main contribution of the conducted research to the development of 3D cadastre visualizations is to start a discussion on the differences in their perception among real estate professionals and those who have no experience in this area and may have to use multidimensional property data. The research was conducted using a questionnaire-based survey method with the computer-assisted web interview (CAWI) technique. The questionnaire was completed by students of a course related to real estate law (geodetic science) and those who do not have regular contact with it (environmental engineering, medicine, sports, mechanics, and management). As a result of the survey, it emerged that the group studying geodetic science performed better on average than students in other fields of study. Additionally, the conducted survey confirmed the existing knowledge of the perception of the visualization of property rights in three dimensions. According to it, visualizations of property rights in 3D should use color. The use of transparency helps in visualisations made in grayscale but interferes with more complex colorful objects. Full article

Germany aims to reduce soil sealing to under 30 hectares per day by 2030 to address negative environmental impacts from the expansion of impervious surfaces. As cities adapt to climate change, spatially explicit very high-resolution information about the distribution of impervious surfaces is becoming increasingly important for urban planning and decision-making. This study proposes a method for mapping impervious surfaces in Google Earth Engine (GEE) using a data fusion approach of 0.9 m colour-infrared true orthophotos, digital elevation models, and vector data. We conducted a pixel-based random forest (RF) classification utilizing spectral indices, Grey-Level Co-occurrence Matrix texture features, and topographic features. Impervious surfaces were mapped with 0.9 m precision resulting in an Overall Accuracy of 92.31% and Kappa-Coefficient of 84.62%. To address challenges posed by high-resolution imagery, we superimposed the RF classification results with land use data from Germany’s Authoritative Real Estate Cadastre Information System (ALKIS). The results show that 25.26% of the city of Wuppertal is covered by impervious surfaces coinciding with a government-funded study from 2020 based on Sentinel-2 Copernicus data that defined a proportion of 25.22% as built-up area. This demonstrates the effectiveness of our method for semi-automated mapping of impervious surfaces in GEE to support urban planning on a local to regional scale. Full article

The article compares the effects of crisis on the real estate market in two regions of the Czech Republic that differ from a macroeconomic point of view. The region of Prague represents the rich and developed region while the Karlovy Vary region struggles with many socio-economic and structural problems. An analysis was performed for the time period of 2018 to 2022. It analyzed the development of apartment prices in both regions, the availability of housing, the turnover of the real estate market in terms of the number of apartment sales, the development of liens on real estate, the number of apartment transfers from state property to private ownership, and the development of the number of real estate foreclosures. The basis for creating statistical outputs is the EVAL software, which was developed by one of the co-authors of this article. The EVAL software collects price offers of apartments offered for sale and rent throughout the Czech Republic and collects publicly available data from the cadastral office. The authors found that the real estate market experienced a significant turnaround in the volume of mortgage loans granted in 2022. This decline led to a significant drop in the total volume of real estate transactions. The findings suggest that potential buyers should wait for property prices to drop before buying, while rental property owners and investors can take advantage of the increased demand for properties. Full article

The price of dwellings is determined by a number of attributes among which location factors are usually the most important. Comprehensive analyses of the real estate market should take into account a broad spectrum of attributes including economic factors, physical, neighborhood and environment characteristics. The primary objective of the study was to answer the question of what determinants affect transaction prices within the housing market in Poznań. The analysis was performed on the basis of source data obtained from the Board of Geodesy and Urban Cadastre GEOPOZ in Poznań. In our study, we used two research regression methods: ordinary least squares and geographically weighted regression. The estimated models made it possible to formulate specific conclusions related to the identification of local determinants of housing prices in the Poznań housing market. The results of the study confirmed that the use of the proposed techniques makes it possible to identify attributes relevant to the local market, and, moreover, the use of spatial analysis leads to an increase in the quality of the description of the characteristics of the analyzed phenomenon. Finally, the results obtained indicate the diversity of the analyzed market and highlight its ambiguity and complexity. Full article

Machine learning algorithms are being used for multiple real-life applications and in research. As a consequence of digital technology, large structured and georeferenced datasets are now more widely available, facilitating the use of these algorithms to analyze and identify patterns, as well as to make predictions that help users in decision making. This research aims to identify the best machine learning algorithms to predict house prices, and to quantify the impact of the COVID-19 pandemic on house prices in a Spanish city. The methodology addresses the phases of data preparation, feature engineering, hyperparameter training and optimization, model evaluation and selection, and finally model interpretation. Ensemble learning algorithms based on boosting (Gradient Boosting Regressor, Extreme Gradient Boosting, and Light Gradient Boosting Machine) and bagging (random forest and extra-trees regressor) are used and compared with a linear regression model. A case study is developed with georeferenced microdata of the real estate market in Alicante (Spain), before and after the pandemic declaration derived from COVID-19, together with information from other complementary sources such as the cadastre, socio-demographic and economic indicators, and satellite images. The results show that machine learning algorithms perform better than traditional linear models because they are better adapted to the nonlinearities of complex data such as real estate market data. Algorithms based on bagging show overfitting problems (random forest and extra-trees regressor) and those based on boosting have better performance and lower overfitting. This research contributes to the literature on the Spanish real estate market by being one of the first studies to use machine learning and microdata to explore the incidence of the COVID-19 pandemic on house prices. Full article