The goal of this study is to analyse the predictive performance of the random forest machine learning technique in comparison to commonly used hedonic models based on multiple regression for the ...prediction of apartment prices. A data set that includes 7407 records of apartment transactions referring to real estate sales from 2008–2013 in the city of Ljubljana, the capital of Slovenia, was used in order to test and compare the predictive performances of both models. Apparent challenges faced during modelling included (1) the non-linear nature of the prediction assignment task; (2) input data being based on transactions occurring over a period of great price changes in Ljubljana whereby a 28% decline was noted in six consecutive testing years; and (3) the complex urban form of the case study area. Available explanatory variables, organised as a Geographic Information Systems (GIS) ready dataset, including the structural and age characteristics of the apartments as well as environmental and neighbourhood information were considered in the modelling procedure. All performance measures (R2 values, sales ratios, mean average percentage error (MAPE), coefficient of dispersion (COD)) revealed significantly better results for predictions obtained by the random forest method, which confirms the prospective of this machine learning technique on apartment price prediction.
This research focuses on a systematic literature review of the geospatial Linked Data (LD) publication at National Mapping and Cadastral Agencies in Europe (NMCA) responsible for land administration. ...We analysed scientific studies published from 2014 to 2023. Our research aimed to find out the reasons for the relatively slow adoption of geospatial data publication as LD. Therefore, we searched for the most common problems, solutions, and challenges for publishing prioritised data themes in NMCAs. Applied research methodology relies on well-established approaches such as analysing Population Problems, Intervention, Comparison, Outcomes, and Circumstances (PICOC) and backward snowballing. The eligibility process is presented by Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines. We analysed nineteen extracted papers and identified twelve key issues from full-text reading. Frequency analyses resulted in the overview of the most frequently published geospatial themes as LD in several European countries. We addressed five research questions and concluded that in addition to systematic support for developing vocabularies and ontologies, trust, awareness, and knowledge about best practices could influence the success of LD publication at NMCAs.
This paper presents a 3D cadastral data model for buildings. A review of the relevant research shows that a common concept in the 3D cadastre domain is using the legal building unit, i.e. real ...property unit, as the core modelling unit. Alternatively, this study proposes using indoor space as a core modelling unit. The main reason is to enable the efficient integration of cadastral data with the data from other domains. On the conceptual level, the model is linked to the Land Administration Domain Model (LADM). The integration options are studied for three international standards: IFC, CityGML and IndoorGML.
The main purpose of this research is to evaluate the improvement in positional accuracy (PAI) of cadastral boundary points’ coordinates through the adjustment of a large set of digital cadastral ...index maps of rural regions based on traditional Franciscan-origin maps of heterogeneous geometric quality. The distribution of residuals of local coordinates of reference points onto the as yet unconnected neighboring points is researched. In this article, we use the adjustment method based on neighborhood transformation with a mechanical membrane model deriving from Hooke’s Law and consider a general case study of a Slovenian traditional cadastral graphic database of various historical origins. The number of geometric errors in fieldbook information from outdated measurement technologies and inappropriate implementations of cadastral index map geometric maintenance reduces the number of complying datasets of relative geometry by 50%. Previous experiments in traditional cadastral index maps of rural regions, with triangle-based piecewise affine plane transformation (RMSE = 2.4 m), have been improved by the membrane method (RMSE = 1.0 m), based on tests at 623 control points. Positional accuracy improvement of cadastral geospatial data and the integration of geometric subsystems provided recognizable benefits for the future maintenance of a unique, integrated, centralized graphical cadastral subsystem, which is in the testing phase in Slovenia.
This paper presents the process of real estate reallocation as a mass cadastral subdivision process of agrarian communities’ customary rights. The agricultural communities have existed for centuries ...and have been jointly owning and using the common land. Such gatherings were developed mainly due to the unique requirements deriving from land use and relief characteristics, such as joint forest management on mountain slopes. The main objective of this research has been to analyse the process of real estate subdivision, which has its legal background in Slovenian legislation. In this paper, the process of cadastral subdivision of land owned by agricultural communities is presented as a mass cadastral land subdivision process: from preparatory work to the new geometric structure of the common land. The cadastral, organisational, and engineering role of the chartered surveying engineer and the surveying company is examined. An aim of the paper is, inter alia, to develop a conceptual model of the process that will serve as a basis for optimisation, for a more just and more efficient distribution of assets among community members. The course of the individual steps of the community established land subdivision is shown with unified modelling language (UML) activity diagrams. As a case study, we have considered the subdivision of the property of the agricultural community of Zgornja Sorica in Slovenia.
Establishing a multi-purpose cadastre, especially in terms of upgrading cadastral contents with the various spatial data, such as land use, is a challenge in Slovenia and internationally. Land use ...strongly affects spatial planning, development, and management, so high-quality spatial integration of the land cadastre with spatial plans data is crucial for effective land management. In the first part of the article, we reviewed the literature and documents that prescribe guidelines for the development of the land cadastre; we use these guidelines as a basis for developing a proposed method of linking and harmonising the data of the land cadastre with the spatial plan data. Land use is specified in spatial plans, and we linked it to the graphical and attribute land cadastre data layer. We tested the method in selected study areas in Prekmurje with a high-quality cadastre in the municipalities of Kramarovci and Nemčavci. As a result, we presented land use data directly in the land cadastre database, which requires simultaneous land use and cadastre maintenance. Based on the results for selected cadastral municipalities, we critically evaluated the proposed method.
Geographic information systems have been applied on the World Wide Web with different approaches and there is a need to recognize how different groups of users conceptualize the domain of geographic ...space. In the authors research, they present an attempt to model a semantic reference system in a semantic web by the concept of global geo-ontology. Taxonomy is based on general knowledge representation as physical and conceptual shapes, simultaneously with basic and advanced human activities. Developed ontology includes 588 concepts on five levels and is extendable. Within such a structure, the rules as independence of location, time frame and culture are respected.
Spatial Data Infrastructures (SDIs) are a key asset for Europe. This paper concentrates on unsolved issues in SDIs in Europe related to the management of semantic heterogeneities. It studies ...contributions and competences from two communities in this field: cartographers, authoritative data providers, and geographic information scientists on the one hand, and computer scientists working on the Web of Data on the other. During several workshops organized by the EuroSDR and Eurogeographics organizations, the authors analyzed their complementarity and discovered reasons for the difficult collaboration between these communities. They have different and sometimes conflicting perspectives on what successful SDIs should look like, as well as on priorities. We developed a proposal to integrate both perspectives, which is centered on the elaboration of an open European Geographical Knowledge Graph. Its structure reuses results from the literature on geographical information ontologies. It is associated with a multifaceted roadmap addressing interrelated aspects of SDIs.
The study attempts to identify and estimate the office rents of submarkets in the Helsinki metropolitan area. We applied a non-parametric empirical approach called the CAE method to identify six ...parameters: highway APD (access point distance), car traffic density, light rail APD, main retail distance, office building density and effective age. Our results suggest that car traffic density is the single most influential parameter. Office rent decreases with effective age and increases with the density of office buildings. Longer distances to highway access points and to the main retail centres decrease office rents, while shorter distances to the light rail access points increase office rents in general and particularly for locations close to highway access points. We identified local peaks by inspecting multiple graphs. The local peaks were considered evidence for the existence of commercial office submarkets within the Helsinki metropolitan area. We identified seven submarkets at different rent levels. Interpreting submarkets from the CAE graphs allowed us to recognise particular business districts in the Helsinki metropolitan area. In addition, it is of great significance that the roles of the given and estimated variables can be exchanged. The method is directly applicable in real estate studies using adapted database and prescribed smoothing parameters.
In this article we analyze a well-known and extensively researched problem: how to find all datasets, on the one hand, and on the other hand only those that are of value to the user when dealing with ...a specific spatially oriented task. In analogy with existing approaches to a similar problem from other fields of human endeavor, we call this software solution 'a spatial data recommendation service.' In its final version, this service should be capable of matching requests created in the user's mind with the content of the existing datasets, while taking into account the user's preferences obtained from the user's previous use of the service. As a result, the service should recommend a list of datasets best suited to the user's needs. In this regard, we consider metadata, particularly natural language definitions of spatial entities, a crucial piece of the solution. To be able to use this information in the process of matching the user's request with the dataset content, this information must be semantically preprocessed. To automate this task we have applied a machine learning approach. With inductive logic programming (ILP) our system learns rules that identify and extract values for the five most frequent relations/properties found in Slovene natural language definitions of spatial entities. The initially established quality criterion for identifying and extracting information was met in three out of five examples. Therefore we conclude that ILP offers a promising approach to developing an information extraction component of a spatial data recommendation service.
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