The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLIII-B4-2021
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B4-2021, 301–306, 2021
https://doi.org/10.5194/isprs-archives-XLIII-B4-2021-301-2021
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B4-2021, 301–306, 2021
https://doi.org/10.5194/isprs-archives-XLIII-B4-2021-301-2021

  30 Jun 2021

30 Jun 2021

AN EXTENSION OF CITYJSON TO SUPPORT POINT CLOUDS

G.-A. Nys, A. Kharroubi, F. Poux, and R. Billen G.-A. Nys et al.
  • Geomatics Unit, UR SPHERES, University of Liège (ULiège), Allée du six Août, 19, 4000 Liège, Belgium

Keywords: 3D City Models, CityJSON, CityGML, Smart Cities, Point Cloud

Abstract. The combination between dense point clouds and 3D vector objects permits new cartographic representation of urban information. This paper proposes an extension for the CityJSON encoding to support point clouds. Following the 3.0 CityGML specifications, attributes and features are added to the core module of v1.0.1 CityJSON. Two solutions are proposed: inline complex geometries and external link to a remote file. The extended schema can be illustrated in four scenarios: detailed features visualization, fall-back solution in features reconstruction processes, simulating urban climate represented as vector fields, and true-to-life representation solution for complex elements such as solitary vegetation objects. It permits 3D city modelers to handle points clouds in a native way reducing files size and avoiding redundancy. All developments and documentation are available open-source.