Shadowing Calculation on Urban Areas from Semantic 3D City Models

Conference Paper (2024)
Authors

Longxiang Xu (Student TU Delft)

Camilo A. León Sánchez (TU Delft - Urban Data Science)

G. Agugiaro (TU Delft - Urban Data Science)

JE Stoter (TU Delft - Urban Data Science)

Research Group
Urban Data Science
Copyright
© 2024 Longxiang Xu, C.A. León Sánchez, G. Agugiaro, J.E. Stoter
To reference this document use:
https://doi.org/10.1007/978-3-031-43699-4_2
More Info
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Publication Year
2024
Language
English
Copyright
© 2024 Longxiang Xu, C.A. León Sánchez, G. Agugiaro, J.E. Stoter
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)
31-47
ISBN (print)
['978-3-031-43698-7', '978-3-031-43701-4']
ISBN (electronic)
978-3-031-43699-4
DOI:
https://doi.org/10.1007/978-3-031-43699-4_2
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

Nowadays, our society is in the transit to adopt more sustainable energy sources to reduce our impact on the environment; one alternative is solar energy. However, this is highly affected by the surroundings, which might cause shadowing effects. In this paper, we present our method to perform shadowing calculations in urban areas using semantic 3D city models, which is split into five sections: Point Grid Generation, Sun-Ray Generation, Nightside Filtering, Bounding Volume Hierarchy and the intersection between the sun rays and the BVH to identify which locations are shadowed at a given moment (epoch). Our tests are performed in Rotterdam’s city center, a dense urban area in The Netherlands. Our initial results indicate that the computational time per 100 k grid points fluctuates within 0.2–0.7s.

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