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. ... Read more

Urban analysis often relies on separate geospatial mapping, street-level image analysis, point-cloud analysis and 3D urban modeling workflows, which can lead to semantic and spatial inconsistencies when structural, visual and volumetric results are interpreted together. This paper develops an SPC-guided Smart 3D Gaussian Splatting (S3DGS) analytical framework to address this fragmentation. Using the Aula–library block in Delft as a case study, we construct a CityGML-inspired Smart Point Cloud from laser-scanning data, generate street-level and aerial 3DGS components from multi-view imagery, align and fuse them into a common coordinate frame, and propagate SPC-derived semantics to Gaussian primitives. The resulting S3DGS base supports projection-based semantic composition, observer-centered visual exposure, volumetric spatial-presence aggregation and layered scene typing within the same reference. Cross-layer interpretation links volumetric and visual-exposure types in the same spatial units, revealing conditions such as physically present but visually recessive building mass. This layered reading allows surface composition, visual experience and three-dimensional spatial presence to be traced within the same urban unit. Evaluation results indicate a stable workflow, with an alignment RMSE of 0.0439 m and a kNN label consistency of 92.24%. By turning Gaussian scenes into semantically traceable and spatially co-referenced analytical bases, S3DGS offers a practical pathway from isolated urban measurements toward integrated, viewpoint-aware and three-dimensional interpretation of the built environment. ... Read more

This paper presents the Architectural Heritage Information Infrastructure (AHII), a standards-operational framework for maintaining identity, semantics, and traceability across three complementary representations used in heritage workflows: Smart Point Clouds (SPC), HBIM/IFC, and Smart 3D Gaussian Splatting (S3DGS). AHII is centered on a compact UML information model and governed code lists, and it operationalizes cross-representation continuity through a shared alignment transform and an explicit identifier crosswalk. This design supports task-driven switching between evidence-grade inspection (SPC), standards-based querying and exchange (IFC), and lightweight photorealistic dissemination (S3DGS), while maintaining auditable correspondence across iterative updates. We validate AHII on two Dutch case studies using a reproducible protocol with fixed evaluation splits and independent checkpoints, complemented by an online, task-anchored user study (N = 200). Results provide evidence of cross-representation interoperability, together with task-appropriate technical performance: intrinsic SPC segmentation reaches macro-mIoU ≈ 0.88, cross-representation co-location achieves 3D RMSE on the order of 1–3 cm, and IFC4 round-trip checks preserve GUIDs with near-lossless property-set retention. Together, these findings show that AHII can be implemented in practice as a traceable information infrastructure linking documentation, modeling, standards-based data and semantic exchange, and dissemination across heterogeneous representations. ... Read more

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. ... Read more

Understanding public experiences in urban greenspace is essential for supporting more human-centric design and management. While traditional survey methods are often time- and labor-intensive, user-generated content (UGC) offers a rapid and scalable alternative for capturing public experiential insights. However, extracting detailed user experience information from this data remains methodologically challenging. This study proposes a novel multimodal analytical framework based on online review data and natural language processing techniques, combining LoRA fine-tuned RoBERTa language model with CLIP vision-language model to analyze multidimensional ecosystem service experience patterns in urban greenspace from user-generated text and image reviews. Results demonstrate that the proposed approach achieves more robust extraction and analysis of user experience insights compared to conventional deep learning and lexicon-based methods, exhibiting greater capacity to process contextually embedded experiential information. The multimodal framework enables more comprehensive capture of user experiences than either text or image data alone, with particular gains on dimensions that are difficult to represent through a single modality. Applying the analytical framework to Amsterdam and Rotterdam as case studies, statistical and spatial analysis reveals heterogeneity in user urban greenspace experiences and identifies key experiential bundles alongside their associated synergies and trade-offs. This study offers a novel approach to quantifying urban greenspace experiences from a user perspective, and provides insights for evidence-based urban greening practices. ... Read more

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. ... Read more

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. ... Read more

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. ... Read more

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. ... Read more

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. ... Read more

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. ... Read more

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. ... Read more

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. ... Read more

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. ... Read more

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. ... Read more

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. ... Read more

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. ... Read more

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). [...] ... Read more

This paper expands the Land Administration Domain Model (LADM) Sarawak Country Profile by incorporating legal space details from Building Information Modelling (BIM). Sarawak, located on Borneo Island, practices a distinct land administration system compared to Peninsular Malaysia. While Peninsular Malaysia follows the National Land Code of 1965, Sarawak adheres to the Sarawak Land Code 1958, which includes provisions for indigenous customary land rights. The Malaysia country profile has been developed based on the LADM standard, considering the 3D situation. Since both regions (Peninsular Malaysia and Sarawak) are under different legal frameworks, this study attempts to further develop the Sarawak country profile based on its current land administration system, including adopting some classes and attributes from the existing Malaysia country profile. The study investigates the potential of incorporating legal space details from the BIM/Industry Foundation Class (IFC) model into the Sarawak country profile. The conceptual model details the fundamental LADM components (Party, Administrative, and Spatial Unit), along with details on the legal space sourced from BIM/IFC. This mapping process requires BIM/IFC data to contain sufficient information for distinguishing property spaces and their boundaries. ... Read more

This research explores the integration of IFC with LADM Part 5 Spatial Plan Information (ISO DIS 19152-5) to standardize BIM-based permit checking processes, focusing on a case study from Estonia. Land Administration Systems (LAS) are crucial in spatial development, managing land-related information. Rapid urbanization necessitates efficient space management, promoting the adoption of digital technologies in the Architectural, Engineering, and Construction (AEC) sector. The integration of Geographic Information Systems (GIS) and Building Information Modelling (BIM) presents opportunities for enhanced collaboration and data management. The main aim is to enhance efficiency, interoperability, and standardization in the compliance checks between different plan levels (e.g., Detailed Plan vs Mater Plan) by incorporating LADM Part 5 into digital frameworks. Traditional permit processes are often manual, time-consuming, and prone to errors. By integrating LADM Part 5 with IFC data, this research aims to create a standardized approach that not only improves data management and facilitates seamless information exchange but also maximizes industry and technical support to ensure compliance with international standards.

The methodology involves several key steps. First, a country profile for Estonia using LADM Part 5 is developed, tailored to the specific needs of the Estonian LAS. This profile integrates with PLANK, the Estonian spatial plan database, incorporating how Estonia acquires, stores, and requires data in their spatial plans. Next, a PostgreSQL database is created to store this profile. Pilot Detailed Plan datasets encoded in IFC format are then imported into the database using FME scripts, mapping the data to relevant sections. This integrated database supports digital permitting processes, specifically plan compliance checks between different levels of spatial plans. Throughout the research, the country profile is refined based on the optimizations of the database, driven by the specific requirements of the input data processed through FME scripts. Given that LADM is a standardized model, the database enforces specific data structures, ensuring processed data is valuable and relevant. The FME scripts facilitate this process, ensuring the data extracted from the database is standardized and user-friendly. Constraints such as maximum building height restrictions are pre-processed and stored within the database, enabling users to access this information without manually reviewing raw plan data. Later, the database was sampled using pilot datasets, with the tools and scripts made available on the research’s GitHub repository. After storing the spatial plan data in the database, data can be directly accessed by scripts designed to execute compliance checks between Detailed Plans and Master Plans, as shown in the Estonia case study. Although developing these specific checks is beyond this research's scope, the work was structured to integrate smoothly with the processes used in the Estonia case study.

Preliminary findings show that combining LADM with IFC improves data representation, enhances interoperability, and establishes a consistent standard for compliance checks between Master and Detailed Plans. This research contributes to developing standardized, reliable, and efficient permit checking systems, with important implications for urban planning and land management. ... Read more