NDLI: CityJSON Building Generation from Airborne LiDAR 3D Point Clouds

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CityJSON Building Generation from Airborne LiDAR 3D Point Clouds

Content Provider	MDPI
Author	Nys, Gilles-Antoine Poux, Florent Billen, Roland
Copyright Year	2020
Description	The relevant insights provided by 3D City models greatly improve Smart Cities and their management policies. In the urban built environment, buildings frequently represent the most studied and modeled features. CityJSON format proposes a lightweight and developer-friendly alternative to CityGML. This paper proposes an improvement to the usability of 3D models providing an automatic generation method in CityJSON, to ensure compactness, expressivity, and interoperability. In addition to a compliance rate in excess of 92% for geometry and topology, the generated model allows the handling of contextual information, such as metadata and refined levels of details (LoD), in a built-in manner. By breaking down the building-generation process, it creates consistent building objects from the unique source of Light Detection and Ranging (LiDAR) point clouds.
Starting Page	521
e-ISSN	22209964
DOI	10.3390/ijgi9090521
Journal	ISPRS International Journal of Geo-Information
Issue Number	9
Volume Number	9
Language	English
Publisher	MDPI
Publisher Date	2020-08-31
Access Restriction	Open
Subject Keyword	ISPRS International Journal of Geo-Information Isprs International Journal of Geo-information Imaging Science Remote Sensing Lidar 3d City Models Cityjson Smart Cities Point Cloud Segmentation 3d Modeling
Content Type	Text
Resource Type	Article

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