This study investigates the challenges of UAV-based cadastral mapping of boundaries not physically marked in the field, focusing on positional accuracy and on the visibility of different types of boundary markers. Four test fields with different industrial markers and custom-made targets were surveyed using UAV photogrammetry. The results show that custom-made targets provide better visibility and slightly better positional accuracy. At the same time, 157 signalised points achieved a 3D accuracy of 1.1 cm, meeting Slovenian cadastral requirements. The marker's colour, size and background significantly influenced the detection. The findings confirm that UAV photogrammetry is suitable for land boundary data collection when combined with an accurate geodetic framework, appropriate markers, and proper execution.

The increasing occurrence of disasters worldwide has motivated researchers to continuously evaluate potential technological advances to support disaster management (DM) as well as emergency response. The advent of Volunteered Geographic Information (VGI) offers the possibility of near real-time data collection or the possibility of massive disaster and post-disaster data collection. VGI is a type of geographic information provided by volunteers who have no formal training in geoinformatics and geographic information systems (GIS). The objective of this review aimed to examine research publications that address VGI in the context of DM, focusing on VGI data quality. From the collected metadata of publications published in the Web of Science (WoS) on crowdsourcing and VGI in the context of DM, we extracted and processed those articles related to data quality using the text mining method and a bibliometric approach. The research addresses the quality of VGI data and its fit for purpose for DM studies that rely on accurate and reliable geographic information for successful management through identified topics. The article concludes by highlighting the potential of VGI to provide valuable information for DM, while also pointing to the need for further research to identify and improve the quality of VGI data.

Reflecting the importance of cadastral data for land management and spatial development, various initiatives have been launched over the past 20 years. But how have these initiatives enhanced the possibility to build a cadastral map of Europe in terms of promoting the harmonization, integration and interoperability of spatial data across Member States?

The boundary of real property is the fundamental element for securing rights attached to land.Countries, even with a long-standing cadastral tradition, often face the challenge of interpreting the course of a parcel boundary on the ground based on the available evidence, as data quality is very heterogeneous.Various cadastral principles and procedures have been developed for the determination of parcel boundaries in the field, which may also be associated with resolving boundary disputes.This article documents and compares the principles and procedures applied in the determination of property boundaries in selected civil law countries based on a novel conceptual model developed for that purpose.The notion of 'boundary determination' used in this article refers to demarcating and surveying land parcel boundaries during the initial cadastral survey and cadastral update procedures.The selected countries include Denmark and Sweden, which apply Nordic civil law; Slovenia and Turkey, which apply German civil law; and Spain, which applies Napoleonic civil law.The demarcation principles and processes applied in the different cadastral systems, the parties involved, and the evidence taken into consideration in these processes are described and compared.The main aim is to contribute to the documentation of the reasoning applied to the property boundary determination in the selected civil law countries.

Digital cadastral maps with accompanying land-related attributes have become a fundamental dataset for many application fields, e.g., spatial planning and development, protecting state lands, securing of land tenure, facilitating land reforms, agriculture, forestry, land management, taxation, etc. In order to fulfil its main objectives, cadastral data needs to be available and accessible, which is, among the others, emphasized also within the United Nations Framework for Effective Land Administration (FELA). This is not only important on the national level but also beyond, including at the European level where use cases and consequently demand for pan-European data sets have evolved in recent years. In order to satisfy these needs, several initiatives regarding cadastral and other geospatial data have been launched in the last 20 years. It started with the Permanent Committee on Cadastre in the European Union, the European Land Information Service, INSPIRE, UN-GGIM Europe and recent European policies on open data and high-value datasets. Our main question is, did those initiatives result in the possibility of building a cadastral map of Europe or not? Is it possible to create a cadastral map of Europe on the desktop or an open online GIS application? Within the paper, we take the opportunity to reflect on the development and implementation of European spatial data infrastructure (INSPIRE) with the main focus on the availability and accessibility of cadastral data. We also take into consideration other European initiatives related to cadastral data. The overall findings show that there is still work to be carried out. Technological developments and recent policy initiatives will certainly be drivers for future improvement.

One of the main concerns of land administration in developed countries is to keep the cadastral system up to date. The goal of this research was to develop an approach to detect visible land boundaries and revise existing cadastral data using deep learning. The convolutional neural network (CNN), based on a modified architecture, was trained using the Berkeley segmentation data set 500 (BSDS500) available online. This dataset is known for edge and boundary detection. The model was tested in two rural areas in Slovenia. The results were evaluated using recall, precision, and the F1 score-as a more appropriate method for unbalanced classes. In terms of detection quality, balanced recall and precision resulted in F1 scores of 0.60 and 0.54 for Ponova vas and Odranci, respectively. With lower recall (completeness), the model was able to predict the boundaries with a precision (correctness) of 0.71 and 0.61. When the cadastral data were revised, the low values were interpreted to mean that the lower the recall, the greater the need to update the existing cadastral data. In the case of Ponova vas, the recall value was less than 0.1, which means that the boundaries did not overlap. In Odranci, 21% of the predicted and cadastral boundaries overlapped. Since the direction of the lines was not a problem, the low recall value (0.21) was mainly due to overly fragmented plots. Overall, the automatic methods are faster (once the model is trained) but less accurate than the manual methods. For a rapid revision of existing cadastral boundaries, an automatic approach is certainly desirable for many national mapping and cadastral agencies, especially in developed countries.

Most cadastral systems today are coordinate-based and contain only a weak or no reference to measurements or the origin of the information. In some contexts, this is largely due to the transition of land data management and maintenance from an analogue to a digital environment. This study focuses on analysing the importance of the measurement-based cadastre and the digitisation process in North Macedonia and Slovenia. The survey-based boundary data and their integration into the digital environment were not considered in either case study. The positional differences between the survey-based boundary coordinates and the graphical coordinates of the boundaries are significant. The RMSE(2D) for Trebosh was 48 cm, and the RMSE(2D) for Ivanjševci was 56 cm. Consequently, the differences in location affected the areas of the cadastral parcels, resulting in an RMSE of 26 m2 and 23 m2 for Trebosh and Ivanjševci, respectively. These differences can be considered as differences within the cadastral boundary data. Therefore, before harmonising the data between the cadastre and the land register, the inconsistencies within the cadastral data should be eliminated first. The differences in the location of cadastral boundaries and parcel area create new challenges in cadastral procedures (formatting of parcels), conflicts in the relocation of boundaries, and impacts on the land market. The solution lies in the way data is maintained, avoiding duplication of attributes or eliminating inconsistencies (after duplication). Both solutions require further modifications of the legal framework for cadastral procedures related to boundary adjustments and data compliance. This study provides a basis for evaluating inconsistencies in cadastral data and highlights the importance of proper source data selection in the digitization process.

The purpose of this research was to theoretically and empirically explore the success factors in cadastral parcel boundary settlements. Our focus was to study the role of landowners in boundary settlements and dispute management. The issue of landowners' involvement is highly topical and complex, as the number of disputes stemming from indeterminate landowners' roles in managing cadastral boundaries and indeterminate roles of the land surveyor as the mediator are considerable. These disputes can be a heavy burden for the country and society as a whole. Our basic research question was very widely set so that the model of success factors of boundary settlements following land cadastre data would go beyond the geodetic and legal framework and would also cover socio-psychological factors. In the literature, this topic is still not addressed, although there are several scientific questions related to it, the focus being on the integration of sociological and psychological factors into the field of spatial management. Based on the opinions of authorised land surveyors, we found for the case of Slovenia that the success of boundary settlement is, along with engineering and property aspects, also influenced by socio-psychological factors. The following factors were found to be essential: previously marked boundaries, preliminary analysis, clear explanation, surveyor's expertise and communication skills, neighbourly relations between landowners, (psychological) attachment to land, and other personality traits of landowners. Generally, it was found that the surveying procedure and the land surveyor are the most important factors of success in boundary settlements, closely followed by the landowner, while the land data (cadastral data) is the least important factor. We also found that the land surveyor influences the landowner and how the factors related to the landowner will reflect upon the success of the boundary settlement; this confirmed that the land surveyor and the landowner are the most important factors of success in cadastral parcel boundary settlements.

Current efforts aim to accelerate cadastral mapping through innovative and automated approaches and can be used to both create and update cadastral maps. This research aims to automate the detection of visible land boundaries from unmanned aerial vehicle (UAV) imagery using deep learning. In addition, we wanted to evaluate the advantages and disadvantages of programming-based deep learning compared to commercial software-based deep learning. For the first case, we used the convolutional neural network U-Net, implemented in Keras, written in Python using the TensorFlow library. For commercial software-based deep learning, we used ENVINet5. UAV imageries from different areas were used to train the U-Net model, which was performed in Google Collaboratory and tested in the study area in Odranci, Slovenia. The results were compared with the results of ENVINet5 using the same datasets. The results showed that both models achieved an overall accuracy of over 95%. The high accuracy is due to the problem of unbalanced classes, which is usually present in boundary detection tasks. U-Net provided a recall of 0.35 and a precision of 0.68 when the threshold was set to 0.5. A threshold can be viewed as a tool for filtering predicted boundary maps and balancing recall and precision. For equitable comparison with ENVINet5, the threshold was increased. U-Net provided more balanced results, a recall of 0.65 and a precision of 0.41, compared to ENVINet5 recall of 0.84 and a precision of 0.35. Programming-based deep learning provides a more flexible yet complex approach to boundary mapping than software-based, which is rigid and does not require programming. The predicted visible land boundaries can be used both to speed up the creation of cadastral maps and to automate the revision of existing cadastral maps and define areas where updates are needed. The predicted boundaries cannot be considered final at this stage but can be used as preliminary cadastral boundaries.

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.

At present, the implementation of cadastral registration of transport investments (such as railway lines on bridges and on viaducts, roads on viaducts, etc.) is performed in the so-called layer system. This means that many objects are constructed at different levels (layers) within the space of a given parcel. Several parties may be interested in developing certain fragments of the parcel space; each of them is interested in acquiring rights only to a specified part of the parcel (its specified layer), in which given investment is implemented by that party. The legal conditions binding in many countries do not allow for implementation of such type investments within the space of a someone else's cadastral parcels, based on the ownership right. This is due to the fact, in accordance with the superficies solo cedit rule applicable in many EU countries, the ownership right extends above and below the parcel space and cadastral systems do not allow for vertical division of a real property. The conventional 2D cadastre, which does not allow vertical division of the parcel space, forces an investor to buy a whole parcel or to get other rights which allows using a specified space of someone else's parcel, such as easiment rights. Buying of an entire parcel in which space bridges and road viaducts investments will be performed and not being able to divide the land space vertically makes it practically impossible to sell the parcel under a viaduct because following the rule above the viaduct is part of the land parcel. Therefore, the space is not optimally utilised. The easement right has some disadvantages, as it cannot be encumbered with a mortgage; therefore it is not the basis of crediting a given investment. The 3D cadastre allows delineating 3D parcels (from the space of existing 2D parcels) that cover specified fragments of the space and to relate ownership rights to those delineated fragments. Within a 3D cadastre system, such objects can be registered as separate cadastral objects. This allows for the implementation of a line investment in the above-ground space in a flexible way, i.e. it is possible to get financing of an investment based on the mortgage charge of a 3D property and market transactions of the remaining space after delineation of the 3D parcel, covering the bridge or viaduct. This paper focuses on approaches to registration of real property rights in the case of engineering objects, such as bridges and road viaducts, in different EU countries: Austria, Bulgaria, Czech Republic, Croatia, Greece, Poland, Slovenia and Sweden.The authors review the current solutions for the registration of engineering objects in the cadastre, including its effectiveness in ensuring appropriate property rights to construct and exploit such objects, and make a comparison between the countries.

This paper presents a study on transforming social media posts into Volunteered Geographic Information (VGI). Social media posts are user-generated data that can be a valuable source of data, but contain unstructured text and need to be processed to be used efficiently. Volunteered Geographic Information refers to user-generated information with some degree of structure, specifically geographic metadata. We describe the process of transforming social media data into valuable geospatial information using text mining and geocoding methods. We analysed about 5000 posts about wildfires from a fan page with about 90,000 members, mostly firefighters or interested volunteers. This data was georeferenced using two systems, ESRI and Nominatim. We also combine social media with other external data sources (interviews with experts) to establish geographic relationships between wildfire phenomena and social media messages. This process demonstrates a smooth conversion of data from the text of published posts on social media, from fire posts to georeferenced data ready for further geospatial analysis. We show that converting unstructured data into VGI can help experts identify areas where emergency situations have occurred without the need for further content analysis. In this paper, we present the information retrieval process where existing geocoding batch methods could assist Smart Enviroment.

The present paper discusses the heterogeneity of the apartment market. For this purpose, we have developed the model for the mass valuation of apartments in the Republic of Slovenia. The construction of the mass valuation model is based on the generalised additive model approach. In this paper, the development of the model is presented. In the experimental part, the analysis of the results of the two models is performed. The dependent variable (the price of an apartment) is distributed according to the Gaussian and the gamma distributions. Particular attention has been paid to the impact of the transaction time on the apartments' transaction value. The results of the model are also compared with the results of the mass valuation model in the Republic of Slovenia, which is carried out cyclically and iteratively, the results of which depend on the results (and mass valuation models) of previous cycles.

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.

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.

Recently, building outline extraction from point cloud has gained momentum in particular in the context of 3D building modelling based on a data-driven approach, which has also been our motivation. For an accurate building outline extraction from a point cloud, various factors affecting the quality should be considered. In this research, we analysed the influence of point cloud density on the quality of the extracted building outlines. The input data was a classified photogrammetric point cloud, obtained from the dense image matching of images acquired by an optical sensor mounted on the unmanned aerial vehicle (UAV). For outline extraction, we selected two procedures, namely the direct approach and the raster approach. In the direct approach, building outlines are extracted directly from the points that have been classified as buildings. First, a convex hull with the alpha algorithm is estimated, which is further generalised with the Douglas-Peucker algorithm. This is followed by the shape regularisation to ensure perpendicular angles of the outline. In the raster approach, we first rasterised the building points and then extracted the building outlines using the Hough transform. In both approaches, the result is a roof outline in a 2D plane representing the maximum extent of the building above the surface. The building outlines were extracted from point clouds with five different densities. For both approaches, the quality assessment has shown that point cloud density has an impact on the building outline extraction, especially on the completeness of the outlines.