ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences

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EISSN : 21949034
Current Publisher: Copernicus GmbH (10.5194)
Total articles ≅ 10,785
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H. Tauscher
ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences pp 151-158; doi:10.5194/isprs-archives-xliv-4-w1-2020-151-2020

Much work has been carried out on the topic of BIM-GIS integration. As a technical challenge in particular, research and development tackle the standard data formats of the two areas and aim for the conversion between, linking of or overarching querying over data sources of these formats. Usually, these operational cases (conversion, linking, querying) are examined in isolation or even treated as mutually exclusive and competing approaches. With Triple Graph Grammars, we propose to apply a method that allows to derive solutions for these operational cases from a common generic ruleset. We demonstrate this approach in a proof-of-concept implementation using eMoflon. Our work focusses on IFC and CityGML and we present and discuss a first end-to-end demonstration of integrating these standards with the proposed method. Going forward such representation of the correlation between IFC and CityGML, declarative, independent of particular operational implementations, can serve as a vehicle to capture and document acknowledged integration schemes for IFC and CityGML, complementing these two standards with a specification of their correlation.
F. Poux, C. Mattes, L. Kobbelt
ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences pp 111-118; doi:10.5194/isprs-archives-xliv-4-w1-2020-111-2020

Point cloud data of indoor scenes is primarily composed of planar-dominant elements. Automatic shape segmentation is thus valuable to avoid labour intensive labelling. This paper provides a fully unsupervised region growing segmentation approach for efficient clustering of massive 3D point clouds. Our contribution targets a low-level grouping beneficial to object-based classification. We argue that the use of relevant segments for object-based classification has the potential to perform better in terms of recognition accuracy, computing time and lowers the manual labelling time needed. However, fully unsupervised approaches are rare due to a lack of proper generalisation of user-defined parameters. We propose a self-learning heuristic process to define optimal parameters, and we validate our method on a large and richly annotated dataset (S3DIS) yielding 88.1% average F1-score for object-based classification. It permits to automatically segment indoor point clouds with no prior knowledge at commercially viable performance and is the foundation for efficient indoor 3D modelling in cluttered point clouds.
A. Koukofikis, V. Coors
ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences pp 71-74; doi:10.5194/isprs-archives-xliv-4-w1-2020-71-2020

We propose a server-client web architecture identifying areas with high wind energy potential by employing 3D technologies and OGC standards. The assessment of a whole city or sub-regions will be supported by integrating Computational Fluid Dynamics (CFD) with historical wind sensor readings. The results, in 3D space, of such analysis could be used for locating installation points of small-scale vertical axis wind turbines in an urban area.
M. Koehl, G. Piasny, V. Thomine, P.-A. Garambois, P. Finaud-Guyot, S. Guillemin, L. Schmitt
ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences pp 63-70; doi:10.5194/isprs-archives-xliv-4-w1-2020-63-2020

The "Wild Moselle" regional nature reserve extends over 13 km at the western foothills of the Vosges Mountains (France). The hydrological regime of the river is characterized by high flow in winter and spring and low flow in summer. Its average slope is 0.12 % and its average bankfull width is 60 m. The coarse sediment load comes mainly from bank erosion. Although this sector is relatively less affected by past or present human activities, the propagation of morphodynamic adjustments initiated by actions carried out both upstream and downstream of this sector impacts the current functioning of the river. These erosion waves converge today towards the central part of the reserve, which led to the collapse of the central pier of the Bainville-aux-Miroirs bridge during a 2-year flood in 2011, and could induce potential risks of defluviation which may destabilize infrastructures. In this context, the study carried out aims to characterize and anticipate the morphodynamic evolutions of the Moselle to be able to propose scenarios of management and restoration of the lateral mobility of the river. For this purpose, a 2D hydro-sedimentary model is being built over the entire reserve, combined with a detailed morpho-sedimentary monitoring. In order to improve the understanding of the lateral migration of the Moselle River, a photogrammetric monitoring was carried out along the concave bank of the most active meander of the studied sector. To follow this morphological evolution more closely, it was decided to establish a 4D GIS. The objective of this monitoring is to compare the rate of bank retreat with hydrodynamic parameters in order to estimate the geotechnical properties of the bank. Comparison of the observed and modelled bank retreat must thus allow these different parameters to be calibrated in the hydro-sedimentary model. As part of this work, this paper aims to highlight the use of 4D GIS to monitor bank retreat at the scale of a meander bend and is divided into three different parts: (i) a state of art to situate the study into the current knowledge and technologies, (ii) a presentation of the study area and the measurements carried out and (iii) a description of the different 3D or 4D data produced and the consequent spatial analyses.
N. Salheb, K. Arroyo Ohori, J. Stoter
ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences pp 127-134; doi:10.5194/isprs-archives-xliv-4-w1-2020-127-2020

The trend of increased usage of both BIM and 3D GIS and the similarity between the two has led to an increase in the overlap between them. A key application of such overlap is providing geospatial context data for BIM models through importing 3D GIS-data to BIM software to help in different design-related issues. However, this is currently difficult because of the lack of support in BIM software for the formats and data models of 3D Geo-information. This paper deals with this issue by developing and implementing a methodology to convert the common open 3D city model data model into the most common open BIM data format, namely CityGML (Gröger et al., 2012) to IFC (buildingsmart, 2019b). For the aim of this study, the two standards are divided into 5 comparable subparts: Semantics, Geometry, Geographical coordinates, Topology, and Encoding. The characteristics of each of these subparts are studied and a conversion method is proposed for each of them from the former standard to the latter. This is done by performing a semantic and geometrical mapping between the two standards, converting the georeferencing from global to local, converting the encoding that the two standards use from XML to STEP, and deciding which topological relations are to be retained. A prototype implementation has been created using Python to combine the above tasks. The work presented in this paper can provide a foundation for future work in converting CityGML to IFC. It provides an insight into the relationship between the two standards and a methodology for the conversion from one to the other, and the process of developing software to perform such conversion. This is done in a way that can be extended for future specific needs.
C. Morbidoni, R. Pierdicca, R. Quattrini, E. Frontoni
ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences pp 95-102; doi:10.5194/isprs-archives-xliv-4-w1-2020-95-2020

Point clouds obtained via Terrestrial Laser Scanning (TLS) surveys of historical buildings are generally transformed into semantically structured 3D models with manual and time-consuming workflows. The importance of automatizing this process is widely recognized within the research community. Recently, deep neural architectures have been applied for semantic segmentation of point clouds, but few studies have evaluated them in the Cultural Heritage domain, where complex shapes and mouldings make this task challenging. In this paper, we describe our experiments with the DGCNN architecture to semantically segment historical buildings point clouds, acquired with TLS. We propose a variation of the original approach where a radius distance based technique is used instead of K-Nearest Neighbors (KNN) to represent the neighborhood of points. We show that our approach provides better results by evaluating it on two real TLS point clouds, representing two Italian historical buildings: the Ducal Palace in Urbino and the Palazzo Ferretti in Ancona.
C. Métral, V. Daponte, A. Caselli, G. Di Marzo, G. Falquet
ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences pp 91-94; doi:10.5194/isprs-archives-xliv-4-w1-2020-91-2020

This paper presents a model for representing compliance rules related to subsurface objects. Rules expressed in this model can be automatically evaluated (using SHACL or SPARQL) on existing 3D city models expressed in RDF. The main characteristics of the proposed model are (1) its expressiveness, that comes from the use of formal ontologies for representing the rules and the objects they refer to, (2) its integrative nature, given by the interconnection among the proposed ontologies and the connection of these ontologies with CityGML and IFC (in an ontological form), and (3) its multi-geometry aspect. Preliminary results allow to automatically evaluate formally expressed compliance rules for underground objects in a 3D city model, that will considerably ease the task of professionals of the field.
L. Corniello
ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences pp 11-18; doi:10.5194/isprs-archives-xliv-4-w1-2020-11-2020

The research on 3D photogrammetric information systems, for the management of digital models of Cultural Heritage, addresses several objectives in the field of digitization and three-dimensional modeling of heritage. The study is conducted through detailed and accurate photographic and iconographic documentation, survey and digital documentation with accessible models. The present work, therefore, proposes to document and reconstruct graphically, the historical evolution of the Hvar Tvrdalj Fortress in Croatia through a series of digital drawings, but especially 3d photogrammetric modeling systems of outdoor spaces. Particular attention was paid to the digital modeling activities of the fishpond, located inside the fortified structure. The activity of representation of the Fortress of Hvar Tvrdalj was set up by providing, in an initial phase, the execution of a basic survey extended to the architectural organisms and the surrounding green space in order to define a first two-dimensional geometric model; then, in a second phase, were made the survey graphs and the consequent graphic restitution with the measurements of architectural details and the complete survey of the inner tank. The research, therefore, presents for the first time, a scientific study of photogrammetric digital survey developed through the creation of 3D digital models on a structure of great architectural and landscape interest, as well as a cornerstone of the island of Hvar for local tourism.
C. Ioannidis, A.-M. Boutsi
ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences pp 57-62; doi:10.5194/isprs-archives-xliv-4-w1-2020-57-2020

The visualization of large-sized 3D geospatial models is a graphics intensive task. With ever increasing size and complexity, more computing resources are needed to attain speed and visual quality. Exploiting the parallelism and the multi-core performance of the Graphics Processing Unit (GPU), a cross-platform 3D viewer is developed based on the Vulkan API and modern C++. The proposed prototype aims at the visualization of a textured 3D mesh of the Cultural Heritage by enabling a multi-threaded rendering pipeline. The rendering workload is distributed across many CPU threads by recording multiple command buffers in parallel and coordinating the host and the GPU rendering phases. To ensure efficient multi-threading behavior and a minimum overhead, synchronization primitives are exploiting for ordering the execution of queues and command buffers. Furthermore, push-constants are used to send uniform data to the GPU and render passes to adapt to the tile-based rendering of the mobile devices. The proposed methodology and technical solution are designed, implemented and tested for Windows, MacOS and Android on Vulkan-compatible GPU hardware by compiling the same codebase. The benchmarking on multiple hardware, architectures and platforms explores the performance improvement for the different approaches compared to one-thread and showcase the potential of the 3D viewer to handle large datasets at no expense of visual quality and geometric fidelity in the absence of high-end technological resources.
E. Frías, J. Balado, L. Díaz-Vilariño, H. Lorenzo
ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences pp 49-55; doi:10.5194/isprs-archives-xliv-4-w1-2020-49-2020

Room segmentation is a matter of ongoing interesting for indoor navigation and reconstruction in robotics and AEC. While in robotics field, the problem room segmentation has been typically addressed on 2D floorplan, interest in enrichment 3D models providing more detailed representation of indoors has been growing in the AEC. Point clouds make available more realistic and update but room segmentation from point clouds is still a challenging topic. This work presents a method to carried out point cloud segmentation into rooms based on 3D mathematical morphological operations. First, the input point cloud is voxelized and indoor empty voxels are extracted by CropHull algorithm. Then, a morphological erosion is performed on the 3D image of indoor empty voxels in order to break connectivity between voxels belonging to adjacent rooms. Remaining voxels after erosion are clustered by a 3D connected components algorithm so that each room is individualized. Room morphology is retrieved by individual 3D morphological dilation on clustered voxels. Finally, unlabelled occupied voxels are classified according proximity to labelled empty voxels after dilation operation. The method was tested in two real cases and segmentation performance was evaluated with encouraging results.
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