Geometric-Semantical Consistency Validation of CityGML Models

Wagner, Detlev; Wewetzer, M.; Bogdahn, Jürgen; Alam, Nazmul; Pries, M.; Coors, Volker

doi:10.1007/978-3-642-29793-9_10

Cited by 32 publications

(27 citation statements)

References 14 publications

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“…There is also a need in future standards to explicitly define the consistent handling of shared building parts and the subsequent assignment of the parent building identifiers. This is a practical demonstration of the requirement for semantic checks on the relationship between building and building parts as described by Wagner et al (2013b). In summary, the metric is useful in revealing the minimum dimensions of a modelled feature if the data is relatively clean and consistent, but by assessing the frequency distribution, it is useful for identifying inconsistencies and errors derived from the modelling process.…”

Section: Minimum Size Metricsmentioning

confidence: 98%

Using Geometry-Based Metrics as Part of Fitness-for-Purpose Evaluations of 3d City Models

Wong

Ellul

2016

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Three-dimensional geospatial information is being increasingly used in a range of tasks beyond visualisation. 3D datasets, however, are often being produced without exact specifications and at mixed levels of geometric complexity. This leads to variations within the models' geometric and semantic complexity as well as the degree of deviation from the corresponding real world objects. Existing descriptors and measures of 3D data such as CityGML's level of detail are perhaps only partially sufficient in communicating data quality and fitness-for-purpose. This study investigates whether alternative, automated, geometry-based metrics describing the variation of complexity within 3D datasets could provide additional relevant information as part of a process of fitness-for-purpose evaluation. The metrics include: mean vertex/edge/face counts per building; vertex/face ratio; minimum 2D footprint area and; minimum feature length. Each metric was tested on six 3D city models from international locations. The results show that geometry-based metrics can provide additional information on 3D city models as part of fitness-for-purpose evaluations. The metrics, while they cannot be used in isolation, may provide a complement to enhance existing data descriptors if backed up with local knowledge, where possible.

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Section: Minimum Size Metricsmentioning

confidence: 98%

Using Geometry-Based Metrics as Part of Fitness-for-Purpose Evaluations of 3d City Models

Wong

Ellul

2016

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…data types) These tools include FZK Viewer (http://iaitypo3.iai.fzk.de/www-extern/index.php?id=1931), Val3dity (Biljecki, et. al, 2016), 3D CityDB Importer/Exporter (http://www.3dcitydb.org/), CityDoctor (Wagner, et. al, 2013) and FME.…”

Section: D Vegetationmentioning

confidence: 99%

Citygml Modelling for Singapore 3d National Mapping

Soon

Khoo

2017

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Commission VI, WG VI/4 KEY WORDS: CityGML, 3D Mapping, Nation-wide ABSTRACT:Since 2014, the Land Survey Division of Singapore Land Authority (SLA) has spearheaded a Whole-of-Government (WOG) 3D mapping project to create and maintain a 3D national map for Singapore. The implementation of the project is divided into two phases. The first phase of the project, which was based on airborne data collection, has produced 3D models for Relief, Building, Vegetation and Waterbody. This part of the work was completed in 2016. To complement the first phase, the second phase used mobile imaging and scanning technique. This phase is targeted to be completed by the mid of 2017 and is creating 3D models for Transportation, CityFurniture, Bridge and Tunnel. The project has extensively adopted the Open Geospatial Consortium (OGC)'s CityGML standard. Out of 10 currently supported thematic modules in CityGML 2.0, the project has implemented 8.

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“…One is to repair the given geometry by applying topological reasoning (cf. (Zhao et al, 2014), (Wagner et al, 2013), (Bogdahn and Coors, 2010)). Due to the complexity of the objects, this problem still exists; the problem of reconstructing the missing surfaces in a fully automatic way is not completely solved yet.…”

Section: Introductionmentioning

confidence: 99%

VOLUMINATOR 2.0 – SPEEDING UP THE APPROXIMATION OF THE VOLUME OF DEFECTIVE 3D BUILDING MODELS

Sindram¹,

Machl²,

Steuer³

et al. 2016

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Semantic 3D city models are increasingly used as a data source in planning and analyzing processes of cities. They represent a virtual copy of the reality and are a common information base and source of information for examining urban questions. A significant advantage of virtual city models is that important indicators such as the volume of buildings, topological relationships between objects and other geometric as well as thematic information can be derived. Knowledge about the exact building volume is an essential base for estimating the building energy demand. In order to determine the volume of buildings with conventional algorithms and tools, the buildings may not contain any topological and geometrical errors. The reality, however, shows that city models very often contain errors such as missing surfaces, duplicated faces and misclosures. To overcome these errors (Steuer et al., 2015) have presented a robust method for approximating the volume of building models. For this purpose, a bounding box of the building is divided into a regular grid of voxels and it is determined which voxels are inside the building. The regular arrangement of the voxels leads to a high number of topological tests and prevents the application of this method using very high resolutions. In this paper we present an extension of the algorithm using an octree approach limiting the subdivision of space to regions around surfaces of the building models and to regions where, in the case of defective models, the topological tests are inconclusive. We show that the computation time can be significantly reduced, while preserving the robustness against geometrical and topological errors.

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Geometric-Semantical Consistency Validation of CityGML Models

Cited by 32 publications

References 14 publications

Using Geometry-Based Metrics as Part of Fitness-for-Purpose Evaluations of 3d City Models

Using Geometry-Based Metrics as Part of Fitness-for-Purpose Evaluations of 3d City Models

Citygml Modelling for Singapore 3d National Mapping

VOLUMINATOR 2.0 – SPEEDING UP THE APPROXIMATION OF THE VOLUME OF DEFECTIVE 3D BUILDING MODELS

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Geometric-Semantical Consistency Validation of CityGML Models

Cited by 32 publications

References 14 publications

Using Geometry-Based Metrics as Part of Fitness-for-Purpose Evaluations of 3d City Models

Using Geometry-Based Metrics as Part of Fitness-for-Purpose Evaluations of 3d City Models

Citygml Modelling for Singapore 3d National Mapping

VOLUMINATOR 2.0 &ndash; SPEEDING UP THE APPROXIMATION OF THE VOLUME OF DEFECTIVE 3D BUILDING MODELS

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Product

Resources

About

VOLUMINATOR 2.0 – SPEEDING UP THE APPROXIMATION OF THE VOLUME OF DEFECTIVE 3D BUILDING MODELS