Semantic-assisted CityGML model consistency checking method

doi:10.11947/j.AGCS.2021.20190474

Acta Geodaetica et Cartographica Sinica ›› 2021, Vol. 50 ›› Issue (5): 664-674.doi: 10.11947/j.AGCS.2021.20190474

• Cartography and Geoinformation • Previous Articles Next Articles

Semantic-assisted CityGML model consistency checking method

WANG Yongjun^1,2,3, CHEN Qingyan⁴, YANG Yujiao^1,2,3, CHEN Xueye⁵, SUN Jian^1,2,3

1. Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China;
2. Key Laboratory of Virtual Geographic Environment, Ministry of Education, Nanjing Normal University, Nanjing 210023, China;
3. State Key Laboratory Cultivation Base of Geographical Environment Evolution, Nanjing Normal University, Nanjing 210023, China;
4. Shanghai Shurong Data Technology Co. Ltd., Shanghai 200082, China;
5. Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Natural Resources, Shenzhen 518034, China

Received:2019-11-13 Revised:2020-08-30 Published:2021-06-03
Supported by:
The Open Fund of Key Laboratory of Urban Land Resources Monitoring and Simulation of Ministry of Natural Resources (No. KF-2018-03-070);The National Natural Science Foundation of China (No. 41771439);The National Key Research and Development Program of China (No. 2016YFB0502300)

Abstract

Abstract: The inconsistency of model geometry, topology and semantics of CityGML data caused by the modeling method, model optimization and data conversion are widespread, which affects its further application. A rule set for CityGML building models was proposed and constructed in this paper which takes semantic constraints into account. Relevant algorithms for automatic detection and restoring of CityGML LOD2/LOD3/LOD4 multi-level-of-detail building model data are designed. Open data downloaded from OGC website was used to verify the rules and algorithms. Experimental results demonstrate that the constructed consistency rule set was complete and self-consistent, and proposed corresponding algorithms can detect most of the topology inconsistencies in CityGML building model data, and can automatically repair some of the topological and geometric errors.

Key words: CityGML, building model, semantic rules, topology consistency, topology validation

CLC Number:

P208

WANG Yongjun, CHEN Qingyan, YANG Yujiao, CHEN Xueye, SUN Jian. Semantic-assisted CityGML model consistency checking method[J]. Acta Geodaetica et Cartographica Sinica, 2021, 50(5): 664-674.

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Semantic-assisted CityGML model consistency checking method

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