cjdb

A Simple, Fast, and Lean Database Solution for the CityGML Data Model

Conference Paper (2024)
Author(s)

Leon Powałka (Student TU Delft)

Chris Poon (Student TU Delft)

Yitong Xia (Student TU Delft)

Siebren Meines (Student TU Delft)

Lan Yan (Student TU Delft)

Yuduan Cai (Student TU Delft)

G. Stavropoulou (TU Delft - Urban Data Science)

B. Dukai (3DGI)

Hugo Ledoux (TU Delft - Urban Data Science)

Research Group
Urban Data Science
Copyright
© 2024 Leon Powałka, Chris Poon, Yitong Xia, Siebren Meines, Lan Yan, Yuduan Cai, G. Stavropoulou, B. Dukai, H. Ledoux
DOI related publication
https://doi.org/10.1007/978-3-031-43699-4_47
More Info
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Publication Year
2024
Language
English
Copyright
© 2024 Leon Powałka, Chris Poon, Yitong Xia, Siebren Meines, Lan Yan, Yuduan Cai, G. Stavropoulou, B. Dukai, H. Ledoux
Research Group
Urban Data Science
Bibliographical Note
Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.@en
Pages (from-to)
781-796
ISBN (print)
['978-3-031-43698-7', '978-3-031-43701-4']
ISBN (electronic)
978-3-031-43699-4
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

When it comes to storing 3D city models in a database, the implementation of the CityGML data model can be quite demanding and often results in complicated schemas. As an example, 3DCityDB, a widely used solution, depends on a schema having 66 tables, mapping closely the CityGML architecture. In this paper, we propose an alternative (called ‘cjdb’) for storing CityGML models efficiently in PostgreSQL with a much simpler table structure and data model design (only 3 tables are necessary). This is achieved by storing the attributes and geometries of the objects directly in JSON. In the case of the geometries we thus adopt the Simple Feature paradigm and we use the structure of CityJSON. We compare our solution against 3DCityDB with large real-world 3D city models, and we find that cjdb has significantly lower demands in storage space (around a factor of 10), allows for faster import/export of data, and has a comparable data retrieval speed with some queries being faster and some slower. The accompanying software (importer and exporter) is available at https://github.com/cityjson/cjdb/ under a permissive open-source license.

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