Abstract. Urban digital twins increasingly require pedestrian-scale three-dimensional (3D) representations to support accessibility and inclusiveness assessment. However, existing approaches typically emphasize either geometric accuracy or visual realism, while lacking an integrated framework for analysing pedestrian-level conditions. This study proposes a hybrid workflow integrating handheld LiDAR and 3D Gaussian Splatting (3DGS) within a CityGML-based semantic framework for accessibility assessment. Handheld LiDAR provides centimetre-level geometric measurements, enabling the extraction of key indicators such as slope, surface roughness, and obstacle presence. In parallel, 3DGS reconstruction from 360° video imagery enhances visual realism and perceptual understanding. Both datasets are co-registered and structured within the CityGML 3.0 Transportation model to represent pedestrian environments in a unified spatial and semantic framework. Accessibility assessment was conducted using three approaches: LiDAR-based analysis, field survey observations, and immersive evaluation in a Virtual Reality (VR) environment. The LiDAR-based results were used as reference. Comparative analysis shows that field survey assessment achieves an agreement of approximately 85.7%, while VR-based assessment reaches approximately 75.4%. The results indicate that while VR does not replace metric-based analysis, it enables perception-driven and participatory evaluation. In particular, VR-based assessment shows potential to involve users, including people with disabilities, in accessibility evaluation through immersive and remote interaction. The proposed approach contributes to the development of human-scale urban digital twins by integrating metric accuracy, semantic structure, and participatory evaluation for more inclusive accessibility analysis.
D. Suwardhi, Wahyunan Andika, R. Widyastuti et al.· The International Archives o...· 0 citations
Abstract. 3D Gaussian Splatting (3DGS) has emerged as a promising method for photorealistic scene reconstructions, yet its application to semantic segmentation in real-world heritage documentation remains underexplored. This study proposes and evaluates an automated semantic 3DGS segmentation pipeline integrating the Segment Anything Model 3 (SAM 3) with per-class prompting for Gaussian reconstruction, applied to a nadiral UAV dataset of the Siti Inggil heritage complex in Cirebon, Indonesia. Segmentation performance of four semantic classes (ground, roofs, vegetations, and water bodies) were assessed against manually segmented 2D and 3D reference data, supplemented by geometric accuracy assessment via the M3C2 analysis. Results reveal both the promise and the inherent challenges of applying 3DGS segmentation to complex real-world heritage scenes, where acquisition geometry, surface characteristics, and foundational model limitations can be observed.
W. A. Fadilah, Virgile Gauthier, Arnadi Murtiyoso et al.· The International Archives o...· 0 citations
Abstract. Urban digital twin systems require 3D city representations that reconcile semantic structure, geometric reliability, simulation capability, and photorealistic real-time rendering. Existing approaches usually prioritize a single modelling paradigm, limiting their ability to support both analytical and visualization needs. CityGML provides standardized semantics and topology but often lacks surface realism. Semantic mesh models preserve geometric detail suitable for environmental simulations but provide limited hierarchical semantics. In contrast, neural radiance-field approaches such as 3D Gaussian Splatting (3DGS) enable photorealistic rendering at interactive frame rates but do not explicitly encode topology or structured semantics. This study establishes a comparative framework linking LiDAR-derived CityGML, semantic mesh, 3D Gaussian Splatting, and Triangle Splatting within a unified urban modelling workflow. UAV data acquired using a DJI ZENMUSE L2 sensor serve as the geometric backbone for reconstructing CityGML LoD1–LoD2 models. The semantic model is transformed into a textured triangular mesh, while radiance-based models are generated from the same imagery using multiple 3DGS implementations and a triangle splatting framework. Comparative evaluation investigates geometric coherence, semantic preservation, and radiance consistency to identify structural correspondences across the representations. The results reveal complementary modelling layers that can be systematically mapped rather than treated as competing alternatives. Based on these findings, the paper proposes a conceptual foundation for a unified 3D urban model capable of transforming consistently into semantic, surface-based, and radiance-based representations for adaptive urban digital twin systems. Data are freely accessible for research purposes at https://github.com/3DOM-FBK/urban-representation-fusion/.
D. Suwardhi, Muhammad Arif Sudibyo, Agus Ambarwari et al.· The International Archives o...· 0 citations
Abstract. This study investigates the use of synthetic images generated within Blender for reconstruction via 3D Gaussian Splatting (3DGS). These synthetic images are derived from a 4D parametric model of a Rhenish castle, incorporating its surroundings and distant environment. While such parametric models offer high-fidelity data, they are computationally intensive for real-time applications. 3DGS is therefore employed to produce high-quality visualisations from images with known spatial orientations. Two reconstruction methods are compared in this study: the open-source native code and the commercial Postshot solution with its Splat3 model. The primary objective is to demonstrate the applicability of this method using synthetic imagery to create lightweight visualisations of digital twins of theoretical 4D states. The underlying parametric model, comprising numerous distinct objects and procedural textures, achieves high photorealism at the expense of substantial computational resources. Consequently, the reconstruction of this dataset via 3DGS facilitates the export and online dissemination of the complex model, decoupling visualisation quality from geometric complexity. The approach is quantitatively validated by comparing the 3DGS output against the original ground truth. Results demonstrate that the Splat3 model outperforms the native open-source approach in visual fidelity, processing speed, and geometric accuracy when handling high-resolution datasets. Both reconstruction methods achieve rendering performances well above 100 frames per second. This confirms that 3DGS can successfully be used with synthetic images to transform computationally heavy parametric models into highly optimised digital representations, ensuring near real-time visualisation suitable for immersive virtual reality and public dissemination.
E. Sommer, Arnadi Murtiyoso, M. Koehl et al.· The International Archives o...· 0 citations
Abstract. This study empirically evaluates the geometric accuracy of point cloud data acquired using an underwater lidar (ULi) system in a tropical shallow water environment. The field test was conducted in the tropical waters of the Seribu Islands, Indonesia, characterised by relatively low turbidity. Terrestrial laser scanning (TLS) and close-range photogrammetry were employed as independent reference datasets. Geometric discrepancies between datasets were quantified using the multiscale model-to-model cloud comparison (M3C2) algorithm, and errors were statistically characterised using the median and median absolute deviation (MAD) to ensure robustness under non-normal distributions. The results indicate that the error of ULi relative to TLS is 0.008 ± 0.012 m, while the error relative to photogrammetry is 0.006 ± 0.013 m. In comparison, the discrepancy between photogrammetry and TLS is smaller, at 0.002 ± 0.004 m. Dimensional analysis of an acoustic Doppler current profiler (ADCP) frame further shows that ULi agrees with TLS and photogrammetry within the millimetre to centimetre range (0.000–0.015 m). Larger deviations in specific segments are attributed to local effects, including edge-related artefacts. Overall, the results demonstrate that ULi provides reliable geometric measurements in shallow-water conditions with low turbidity. Despite slightly lower accuracy compared to terrestrial methods, the system shows potential for underwater mapping applications, particularly in shallow water environments.
Mentari K. Azzahra, F. Muhammad, Arnadi Murtiyoso et al.· The International Archives o...· 0 citations
Three Gaussian splatting methods as implemented in the Postshot commercial software were tested and show that MILo shows very promising results in terms of detail reconstruction, while standard Gaussian splatting excels in visualisation but is still plagued by a high rate of noise especially when converted into a geometric point cloud form.
Sara Gonizzi Barsanti, D. Billi, E. Sommer et al.· The International Archives o...· 0 citations
A complete pipeline for in-situ 3D thermal mesh visualization of urban trees in Augmented Reality (AR), combining Thermal InfraRed image acquisition, Gaussian Splatting-based mesh reconstruction, quantitative validation, and mobile AR deployment is presented.
Chaimaa Delasse, D. Billi, I. Gede Mahendra Darmawiguna et al.· The International Archives o...· 0 citations
This work investigates the potential of Mesh-In-the-Loop Gaussian Splatting (MILo), a recent extension of 3D Gaussian Splatting (3DGS) that integrates differentiable mesh extraction directly within the optimization process, enabling bidirectional consistency between volumetric and surface representations.
D. Billi, Chaimaa Delasse, Arnadi Murtiyoso et al.· The International Archives o...· 0 citations
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