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Using Geometry-based Metrics As Part Of Fitness-for-purpose Evaluations Of 3D City Models

Wong, K; Ellul, C; (2016) Using Geometry-based Metrics As Part Of Fitness-for-purpose Evaluations Of 3D City Models. In: Dimopoulou, E and van Oosterom, P, (eds.) (Proceedings) 11th 3D Geoinfo Conference. (pp. pp. 129-136). International Society for Photogrammetry and Remote Sensing Green open access

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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.

Type: Proceedings paper
Title: Using Geometry-based Metrics As Part Of Fitness-for-purpose Evaluations Of 3D City Models
Event: 11th 3D Geoinfo Conference
Location: Athens, Greece
Dates: 20–21 October 2016
Open access status: An open access version is available from UCL Discovery
DOI: 10.5194/isprs-annals-IV-2-W1-129-2016
Publisher version: http://www.isprs-ann-photogramm-remote-sens-spatia...
Language: English
Additional information: Copyright © 2017 The Author(s). All rights reserved. This work is licensed under a Creative Commons Attribution 3.0 License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/3.0/
Keywords: 3D GIS; 3D geoinformation; geometric complexity; 3D data quality; 3D fitness-for-purpose; 3D city models
UCL classification: UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Civil, Environ and Geomatic Eng
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/1514303
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