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.
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.
This study is focused on indoor navigation network extraction for navigation applications based on available 3D building data and using SFCGAL library, e.g. simple features computational geometry ...algorithms library. In this study, special attention is given to 3D cadastre and BIM (building information modelling) datasets, which have been used as data sources for 3D geometric indoor modelling. SFCGAL 3D functions are used for the extraction of an indoor network, which has been modelled in the form of indoor connectivity graphs based on 3D geometries of indoor features. The extraction is performed by the integration of extract transform load (ETL) software and the spatial database to support multiple data sources and provide access to SFCGAL functions. With this integrated approach, the current lack of straightforward software support for complex 3D spatial analyses is addressed. Based on the developed methodology, we perform and discuss the extraction of an indoor navigation network from 3D cadastral and BIM data. The efficiency and performance of the network analyses were evaluated using the processing and query execution times. The results show that the proposed methodology for geometry-based navigation network extraction of buildings is efficient and can be used with various types of 3D geometric indoor data.
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.
In order to transcend the challenge of accelerating the establishment of cadastres and to efficiently maintain them once established, innovative, and automated cadastral mapping techniques are ...needed. The focus of the research is on the use of high-resolution optical sensors on unmanned aerial vehicle (UAV) platforms. More specifically, this study investigates the potential of UAV-based cadastral mapping, where the ENVI feature extraction (FX) module has been used for data processing. The paper describes the workflow, which encompasses image pre-processing, automatic extraction of visible boundaries on the UAV imagery, and data post-processing. It shows that this approach should be applied when the UAV orthoimage is resampled to a larger ground sample distance (GSD). In addition, the findings show that it is important to filter the extracted boundary maps to improve the results. The results of the accuracy assessment showed that almost 80% of the extracted visible boundaries were correct. Based on the automatic extraction method, the proposed workflow has the potential to accelerate and facilitate the creation of cadastral maps, especially for developing countries. In developed countries, the extracted visible boundaries might be used for the revision of existing cadastral maps. However, in both cases, the extracted visible boundaries must be validated by landowners and other beneficiaries.
This paper provides the innovative approach of using a spatial extract, transform, load (ETL) solution for 3D building modelling, based on an unmanned aerial vehicle (UAV) photogrammetric point ...cloud. The main objective of the paper is to present the holistic workflow for 3D building modelling, emphasising the benefits of using spatial ETL solutions for this purpose. Namely, despite the increasing demands for 3D city models and their geospatial applications, the generation of 3D city models is still challenging in the geospatial domain. Advanced geospatial technologies provide various possibilities for the mass acquisition of geospatial data that is further used for 3D city modelling, but there is a huge difference in the cost and quality of input data. While aerial photogrammetry and airborne laser scanning involve high costs, UAV photogrammetry has brought new opportunities, including for small and medium-sized companies, by providing a more flexible and low-cost source of spatial data for 3D modelling. In our data-driven approach, we use a spatial ETL solution to reconstruct a 3D building model from a dense image matching point cloud which was obtained beforehand from UAV imagery. The results are 3D building models in a semantic vector format consistent with the OGC CityGML standard, Level of Detail 2 (LOD2). The approach has been tested on selected buildings in a simple semi-urban area. We conclude that spatial ETL solutions can be efficiently used for 3D building modelling from UAV data, where the data process model developed allows the developer to easily control and manipulate each processing step.
AbstractThe 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.
Geospatial data and information within contemporary land administration systems are fundamental to manage the territory adequately. 3D land administration systems, often addressed as 3D cadastre, ...promise several benefits, particularly in managing today’s complex built environment, but these are currently still non-existent in their full capacity. The development of any complex information and administration system, such as a land administration system, is time-consuming and costly, particularly during the phase of evaluation and testing. In this regard, the process of implementing such systems may benefit from using synthetic data. In this study, the method for simulating the 3D cadastral dataset is presented and discussed. The dataset is generated using a procedural modelling method, referenced to real cadastral data for the Slovenian territory and stored in a spatial database management system (DBMS) that supports storage of 3D spatial data. Spatial queries, related to 3D cadastral data management, are used to evaluate the database performance and storage characteristics, and 3D visualisation options. The results of the study show that the method is feasible for the simulation of large-scale 3D cadastral datasets. Using the developed spatial queries and their performance analysis, we demonstrate the importance of the simulated dataset for developing efficient 3D cadastral data management processes.
The objective of this discussion is the Austrian land cadastre, which forms the basis of the Austrian land information system, together with the land registry. From a data structure perspective, the ...Austrian land cadastre is a traditional parcel-oriented system and includes a geometric description of land plots linked to other records describing the nature of the land plots. The changeable institutional (legal) framework was shaped the continuous development of the Austrian land cadastre since the first systematic land survey and cadastral mapping at the beginning of the 19thcentury. With the progress of information technology in recent decades, it has been developed into a contemporary land information system, which (together with the land registry) provides up-to-date land information. It has to be emphasized that the current land cadastre still contains some data from its very beginning and, for this reason, the historical development of this evidence, including data sources, is of great importance for users of these data. The first part of the article provides an introduction to the historical development of the Austrian land cadastre, followed by the presentation of contents and procedures of the current land cadastre.
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.
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