Incremental urban and community expansion in rural heritage landscapes often produces cumulative visual impacts, yet planning rarely specifies a clear endpoint for acceptable change. This paper proposes an integrated Visual Impact Assessment (VIA) framework, aligned with SDG 11, to determine “when to stop” using stage-comparable evidence across past, present, and future conditions. The framework is organized in three modules. First, a point cloud-enhanced GIS module quantifies visibility and spatial change across development stages. Second, an enhanced Key Observation Point (KOP) module derives matched eye-level evidence from multi-temporal street-level panoramas and scenario visualizations, for example using Street View Imagery (SVI) time series and 3D Gaussian Splatting (3DGS) rendering. Third, a decision layer integrates structured public acceptability from a questionnaire covering different respondent groups with in-depth expert interviews and synthesis, with virtual reality (VR) eye- and head-tracking used as supportive behavioral evidence. Applied to the Middenbeemster expansion in the Beemster Polder, the Netherlands, the framework yields a case-calibrated reference package for decision support: KOP-based construction intensity serves as the primary reference line for review, perception indicators serve as supporting guardrails, spatial character metrics act as case-specific reference checks to protect the polder framework, and visibility diagnostics remain a necessary screening layer. More broadly, the framework provides a transparent and replicable procedure that can be transferred and locally recalibrated for heritage-sensitive rural-urban fringes where change is incremental and cumulative, supporting a stage-comparable VIA approach.

Districts face dual pressures: reducing carbon emissions while managing surging electricity demand from electrification and urban growth. Traditional grid expansion cannot match the speed and complexity required for modern energy transitions. District energy transitions require connecting different scales, from individual buildings to grid networks, and different timeframes, from daily operations to long-term planning. Despite growing interest in Digital Twin (DT) for energy management, their application to integrated district-level energy transitions remains poorly understood. This review investigates how DTs can enable district energy transitions by examining their applications in built environment and energy infrastructure at district level, analyzing implementations across Positive Energy Districts (PEDs), microgrids (MGs), and related district energy paradigms. DT components (physical models, core capabilities, data infrastructure, and functional evolution) are investigated to assess their integrative potential. The analysis reveals three disconnects: building and grid systems are modeled separately despite inherent interdependencies; operational insights rarely inform infrastructure planning; and intervention strategies overlook sequential dependencies. To address these gaps, we propose an integrated framework advancing DTs toward district energy planning. The framework bridges semantic, temporal, and sequential planning through: knowledge graph architectures enabling cross-domain data integration, coupled simulation pipelines capturing building-grid interactions, and reinforcement learning optimizing intervention sequences. Unlike optimization that fixes strategies upfront, sequential planning accommodates technology emergence and regulatory shifts inherent to multi-decade transitions. This integrated approach transforms DTs from domain-specific monitoring tools into strategic planning platforms where coordinated building improvements and distributed energy resources defer costly grid expansions while accelerating district decarbonization.

This special issue on the Land Administration Domain Model (LADM) and 3D Land Administration (3D LA) containsthe eight best, updated papers from the FIG’s (International Federation of Surveyors) 12th International Workshop onLADM & 3D LA. The 3DLA2024 Workshop is one of the activities of the LADM & 3D LA Working Group (WG), a joint initiat-ive of FIG Commission 3 (Spatial Information Management) and Commission 7 (Cadastre and Land Management). [...]

Point cloud data contains abundant information besides XYZ, such as Level of Importance (LoI) and intensity. These non-spatial dimensions are also frequently used and queried. Therefore, developing an efficient nD solution for managing and querying point clouds is imperative. Previous researchers have developed PlainSFC that maps both nD points and queries into a one-dimensional Space Filling Curve (SFC) space and uses B+-tree for indexing. However, when computing SFC ranges for selection, PlainSFC subdivides the nD space mechanically to approach the query window without considering the point distribution. Then, excessive ranges are generated in vacant areas, and ranges generated in dense point areas are coarse. Consequently, a large number of false positives are selected, slowing down the whole querying process. This paper develops a new solution called HistSFC to resolve the issue. HistSFC builds an nD-histogram which records point data distribution, and uses it to compute ranges for selecting data. Also, this paper discovers a novel statistical metric, Cumulative Hypercubic Coverage (CHC), to measure the uniformity of the point cloud data. Theory is established and it indicates that the nD-histogram is more beneficial when CHC is smaller. Thus, CHC can be used to guide the building of HistSFC. In addition, the paper conducts simulations and benchmark tests to examine the improvement on PlainSFC. It turns out that using the nD-histogram can decrease the false positive rate by orders of magnitude. HistSFC is also evaluated against state-of-the-art solutions. The result shows that HistSFC leads the performance in nearly all the tests.

This paper enhances the Sarawak LADM Country Profile by proposing a structured workflow for mapping IFC elements (e.g. IfcSpace, IfcWall, IfcSlab) to LADM classes to improve the representation of legal space boundaries. The methodology focuses on extracting legal space information from IFC models, mapping it to LADM using Enterprise Architect, and structuring the data for future integration with PostgreSQL. The mapping framework supports strata title management and 3D cadastral in Sarawak. Additionally, this study outlines a conceptual workflow for visualising legal space boundaries using CesiumJS. The proposed approach enhances data interoperability between BIM and land administration, advancing BIM-driven cadastral systems.

Over the past fifteen years, LGAF, GLII, and SDGs frameworks have jointly shaped a complementary global land governance monitoring system. However, challenges remain in data fragmentation and standardised indicator computation. This study explores how ISO 19152 LADM provides a unified technical foundation to model and monitor global land indicators. It develops a standardised conceptual model with UML-based implementation and proposes a modular indicator computation architecture based on interface classes and reusable logic components. The proposed approach supports scalable reporting, enhances indicator operationalisation, and bridges the gap between global policy frameworks and practical land administration systems at the national level.

3D Gaussian Splatting (3DGS) is an advanced 3D representation method that enhances point clouds by incorporating spectral image content, enabling high-fidelity heritage documentation. A 3DGS visualization presents these enriched Gaussians, ensuring high geometric accuracy, detailed texture representation, and efficient spatial reconstruction, thereby enhancing both precision and efficiency in digital heritage preservation. This paper applies 3DGS to modern architectural heritage, combining UAV-based data acquisition with advanced rendering techniques. Using the Delft University of Technology Aula and Library buildings as case study, the research establishes a workflow for efficient heritage documentation and visualization.

This paper investigates the role of 3D Gaussian Splatting (3DGS) within point cloud–dominated workflows for modern architectural heritage digitization. While 3DGS enables real-time, photorealistic visualization, its integration into LiDAR-based documentation pipelines remains underexplored. Using Bouwpub, a modern heritage building in the Netherlands, as a case study, the paper compares 3DGS and LiDAR across data acquisition and preservation, visualization, semantic segmentation, and dissemination. Results show that 3DGS offers superior visual expressiveness and user responsiveness, whereas LiDAR provides greater structural accuracy and segmentation reliability. Based on these findings, two integration strategies are proposed: a Blender-based multi-angle rendering workflow and a Level of Detail 3DGS (LOD3DGS) pipeline. Moving from isolated assessment to applied integration, the study positions 3DGS as a complementary visualization and dissemination module rather than a replacement. This hybrid approach supports immersive, scalable, and semantically enriched digital heritage systems, offering new directions for enhancing both expert documentation and public engagement.

As urban environments become increasingly vertical, Land Administration Systems (LAS) must support complex 3D spatial representations. While Building Information Models (BIM) offer such capabilities, they are not always available. This paper investigates an alternative approach using point clouds for 3D LAS, focusing on the integration of scanned cadastral floor plans and airborne LiDAR from the Actueel Hoogtebestand Nederland (AHN). We present a semi-automated pipeline that extracts floorplan geometries, segments and enhances AHN data, and synthesizes room-level point clouds. Results from a case study in Rotterdam demonstrate the potential of this approach in the absence of BIM, supporting legal space definition and public visualization. However, challenges such as misalignment due to occlusion in AHN data and inconsistent quality in older floor plan drawings affect the accuracy and automation of the process. The synthetic point clouds include room-level attributes, enabling a seamless integration with AHN, offering a representation of real-world features such as building facades, walls, and fences, which often delineate cadastral boundaries.

Estimating the losses in the immediate aftermath of an earthquake is a key component of seismic response. Seismic rapid-loss estimates provide first responders with a prediction of where and what to prepare for. Improving the precision of quick loss estimates requires an estimate of how a buildings in the affected zone may have reacted to an event. Structural response prediction models are a novel approach to estimating building response from the observed displacement of instrumented buildings. Current SRPMs are built on relatively small databases but offer potential for expansion. There exists no robust building-specific database which could facilitate the construction of these models. As a reaction to this gap, this study applies, abstractly and concretely, the OGC SensorThings data model to building seismograph records. The harmonized records form part of a proposed abstract and concrete Structural Response Prediction Model to make estimates of building-response on other un-instrumented buildings. The utility of a abstracted observation data-model and pipeline is shown, with the potential for unifying existing data-sources. The work shall show that the OGC SensorThings integrates generally well, with some limitations, with the requirements of seismic observation record keeping.

This research explores the automation of compliance checks in the early stages ofspatial planning by integrating Industry Foundation Classes (ISO 16739) withthe Land Administration Domain Model (LADM) Part 5: Spatial Plan Information (ISO 19152-5). Traditional planning processes rely on manual assessments,making them time-consuming, prone to errors, and inefficient. While recentresearch has focused primarily on automating the permitting phase, this studyaddresses an earlier step: verifying spatial plans against regulatoryframeworks. By introducing a standardized approach, the research aims toenhance data management, improve interoperability, and ensure adherence tointernational standards. Automating early compliance checks – such as verifyingbuilding height restrictions or required distances between structures – helpsstreamline the planning process, ensuring that only plans meeting regulatoryrequirements advance to the design approval phase. Estonia is selected as acase study due to its highly developed digital infrastructure and commitment toimproving e-government services.

In 2022, the Netherlands introduced ‘water and soil’ as a guiding principle for spatial planning, aiding the country's goal for climate resilience by 2050. Applying it requires integrating subsurface data, spatial planning, and climate adaptation. Despite existing subsurface models, no cohesive approach links them to spatial planning. This paper assesses current models and identifies data requirements. Key barriers include data accessibility and standardization. To address this, plan information was standardized using a proposed Land Administration Domain Model (LADM) Part 5 climate adaptation profile. Additionally, a digital tool, CLIMACAT, was developed to make relevant subsurface data accessible for climate adaptation design.

Efficient vario-scale representation is important in Geographic Information Systems (GIS) and cartographic generalization, particularly when transitioning 2D features into 1D or 0D representations. Traditional approaches often introduce topological inconsistencies and abrupt transitions between scales. This paper presents a novel method for vario-scale representation by integrating the Straight Skeleton Network (SSN), Dual Half-Edge (DHE) structure, and Space-Scale Cube (SSC). The straight skeleton enables hierarchical polygon decomposition, ensuring smooth feature transitions across scales. The DHE structure maintains topological consistency, supports dynamic updates, and allows structured connectivity between spatial features. The SSC framework organizes these transformations within a volumetric model, ensuring seamless scale transitions. The proposed approach is tested on various polygonal configurations, demonstrating its effectiveness in preserving spatial coherence, feature continuity, and structural integrity. This research contributes to multi-scale GIS modeling, automated map generalization, and spatial data structuring.

This systematic literature review critically examines the application of digital technologies in architectural heritage risk management from 2014 to 2024, focusing exclusively on English-language publications. As the significance of architectural heritage continues to be recognized globally, there is an increasing shift towards integrating digital solutions to ensure its preservation and management. This paper explores the evolution and application of digital technologies such as Building Information Modeling (BIM), Geographic Information Systems (GIS), and advanced imaging techniques within the field. It highlights how these technologies have facilitated the non-destructive evaluation of heritage sites and enhanced accessibility and interaction through virtual and augmented reality applications. By synthesizing data from various case studies and scholarly articles, the review identifies current trends and the expanding scope of digital interventions in heritage conservation. It discusses the interplay between traditional conservation approaches and modern technological solutions, providing insights into their complementary roles. The analysis also addresses the challenges and limitations encountered in the digital preservation of architectural heritage, such as data integration, the compatibility of different technologies, and the need for more comprehensive frameworks to guide the implementation of digital tools in heritage conservation practices. Ultimately, this review underscores the transformative impact of digital technology in managing architectural heritage risks, suggesting directions for future research and the potential for innovative applications in the field.

The need for 3D Land Administration Systems (LAS) is growing. In this respect, research is carried out in the field of 3D LAS with respect to data sources, registration of 3D Rights, Restrictions and Responsibilities and dissemination services. Within this context, BIM/IFC models are considered promising sources for 3D LAS, even though the reuse of such models from practice has not yet been examined adequately. Evaluating BIM/IFC-models from practice is crucial, since they are created for different purposes, fulfilling various design criteria. This paper investigates the technical challenges encountered when using real-world BIM/IFC-models for apartment rights’ registration in a 3D LAS. It addresses the validation of five Dutch real-world BIM/IFC-models against four technical criteria, namely: existence of IfcSpace; geometric validity; no overlap and georeferencing. The results of the validation show that the collected BIM/IFC-models lack georeference, IfcSpace and a reference to attributes related to the respective legal units in the Dutch 3D LAS. After validation the models are stored in a 3D LAS Database management system (DBMS), in which the legal spaces are enriched with information of the Rights, Restrictions and Responsibilities (RRR’s) in line with the Land Administration Domain Model (LADM - ISO 19152:2012). The contents of the 3D LAS DBMS are visualised in a web viewer. Additionally, the design for a webservice is introduced, aiming to automate the process of validation, conversion and visualisation. The paper concludes with recommendations and guidelines for creators of BIM/IFC-models based on the outcome of the validation, as well as challenges and recommendations for implementing a validation webservice.

This paper discusses the representation of the scale dimension using tGAP/SSC-DHE, emphasizing its role in creating vario-scale representations. It outlines the process of integrating the scale dimension as the third dimension in a 2D map before transitioning to 3D or 4D maps. DHE is introduced as an effective data structure for this approach, maintaining crucial connections across different levels of detail and offering enhanced topology. Its strength lies in the ability to modify specific parts of the model while retaining a clear structure, thanks to well-defined operators such as Euler operators. This method provides a versatile framework for representing complex spatial data, allowing for detailed analysis while preserving overall coherence and it updates the shape and structure of the model at the same time through local modifications. Through practical implementation, it demonstrates the potential for improved visualization and understanding of multi-dimensional spatial relationships. Also, the DHE data structure supports slicing by either a horizontal plane to produce a map at a specific scale (depending on the height of the horizontal plane) and tilted planes to produce perspective views with mixed scales.

Evaluating the performance of a land administration system (LAS) is a critical task as it can provide input for improving the operational system. Through such an evaluation, the strengths and weaknesses of the existing system can be identified, and actions can be taken to improve it. Efforts have been made to develop frameworks and best practices for the assessment and comparison of the performance of LASs. Amongst the most prominent are the ‘Land Governance Assessment Framework’ (LGAF) of the World Bank and the ‘Global Land Indicators’ proposed by the Global Land Tool Network (GLTN) and the United Nations Human Settlements Programme (UN-Habitat) in its Global Land Indicators Initiative (GLII). The GLII indicators are closely related to the UN-Sustainable Development Goals (SDGs) indicators on land tenure security, namely SDGs 1.4.2 (%adults with secure tenure rights), 5.a.1 (%agricultural population with secure rights over agricultural land), and 5.a.2 (women's equal rights to land ownership).

The Land Administration Domain Model (LADM), an International Standard (ISO, 2012), can be used to monitor global indicators proposed by various international organizations and to evaluate the performance of LADM-based LASs, as LADM Edition II now provides full support for all land administration (LA) functions including marine georegulation, valuation information and spatial plan information. Interface classes to the LADM are designed to support the generation and management of products and services, such as the monitoring of global performance indicators for LASs.

This paper is a follow-up on Chen et al. (2024), which was focusing on formalizing SDG land related indicator using LADM. The objective of this study is to explore the extent to which LADM can be used to also monitor the indicators of LGAF and GLII. To this end, the indicators are categorized according to their degree of association with LADM (i.e. full computational association, partial computational association, indirect association, association with other standards and non-association), and interface classes are created based on the results. The results show that LADM can be used to monitor a significant portion of the indicators of LGAF and GLII, although most of the indicators are related to a country's national legislation, its implementation and organizational decisions and capability.

This study illustrates the linkages between the ISO’s Land Administration Domain Model (LADM) and the UN’s sustainable development goals (SDGs), highlighting the role of the LADM in promoting effective land administration suitable for efficient computation of land/water (space)-related SDG indicators. The main contribution of this study is the formalization of SDG indicators by using the ISO standard LADM. This paper proposes several SDG-indicator-related extensions to the multi-part LADM standard that is currently under revision. These extensions encompass the introduction of new procedures for calculating indicators, the integration of blueprints for external classes to fulfil additional information needs and the design of interface classes for presenting indicator values across specific countries and reporting years. In an innovative approach, this paper introduces the Four-Step Method—a powerful framework designed to formalize SDG indicators within the LADM framework. Detailed attention is devoted to specific indicators, including 1.4.2 (secure land rights), 5.a.1 (women’s agricultural land rights), 14.5.1 (protected marine areas) and 11.5.2 (valuation as a basis for direct economic loss). In short, the Four-Step Method is pivotal in eliminating ambiguities, enhancing the efficiency of indicator computation and securing more accurate indicator values that more truly reflect the progress towards SDG realization. This approach is also expected to work with other (ISO) standards for other SDG indicators.

Due to the needs of modern society, cadastral systems should be designed to support three dimensional (3D) spatial data. One of many possible approaches for implementing a 3D cadastre, in countries such as Croatia, is to establish a Building Register as a transitional register between 2D and 3D cadastres, where data about buildings and infrastructure would be collected, gradually adapted to the data model of 3D cadastre, and finally migrated to the 3D cadastre database. Sources for establishing the Building Register can be based on the records of state surveys, the register of administrative units, the land book, data managed by local and regional self-government units, data from construction documentation according to special regulations in the field of spatial planning, data managed by the building and infrastructure managers, as well as from other sources. A significant element of the 3D cadastre would be the inclusion of representations of buildings and units of use, as well as public utility infrastructure and complex spatial real-life entities (e.g., bridges, tunnels, overpasses, underpasses, overlapping of constructed objects with natural facilities, large shopping malls with more underground and overhead floors etc.). This paper presents a conceptual model of a 3D cadastre in Croatia by establishing the Building Register with focus on unit of use of real properties, namely apartments and office spaces. The paper also summarizes the current situation regarding the Croatian Land Administration System (LAS) and proposes a conceptual model for modelling unit of use of real properties. Additionally, a proposal is made herein to assign unique identifiers to buildings and their parts in a logical manner which would be intuitive and clear to citizens of Croatia, citizens of European Union and citizens of Croatia neighboring countries. The proposed methodology of determining unique identifiers could provide the means for easier navigation in 3D space and better understanding of spatial information by lay citizens, by institutions or emergency services.

Change detection in the built environment is essential for sustainable development practices including Urban Planning and Development, Environmental Monitoring, and Conservation. Change detection provides valuable insights into dynamic processes, facilitates informed decision making, and supports sustainable development initiatives. Point clouds serve as foundational data sources for change detection in built environments, enabling analysts to detect, quantify, and interpret spatial changes with unparalleled accuracy and granularity. By leveraging the inherent characteristics of point clouds, researchers and practitioners can gain valuable insights into dynamic processes, inform decision making, and foster sustainable development in an ever-evolving built environment. We present the preliminary results of cloud-to-cloud (c2c) distance calculations for further change detection analysis of the entire Netherlands. This study utilises point cloud data from AHN2, 3, and 4 (Actueel Hoogtebestand Nederland1, The Netherlands). A method based on a 3D space-filling curve (SFC) was developed to calculate the c2c distances between AHN2, 3, and 4. This SFC method will allow change detection analysis to be carried out for the entire Netherlands. The change detection analysis outcomes can be accessed for future analysis in Potree2, a web-based point cloud rendered for large point clouds. The final implementation will allow the visualisation of AHN point clouds and their attributes, among which is the change in detection-related information. This research contributes to sustainable development practices by offering enhanced spatial insights and informed decision-making tools for further analysis and monitoring of the (built) environment in the Netherlands. [...]