2020
DOI: 10.3390/ijgi9090521
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CityJSON Building Generation from Airborne LiDAR 3D Point Clouds

Abstract: 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 exce… Show more

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Cited by 37 publications
(24 citation statements)
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“…In these models CD is applied, through Visual Programming Languages (VPL), to link, sort and merge metadata between models and environments but not for modeling purposes. The top-down procedures deal mainly with long-range remote sensing techniques (e.g., Airborne LiDAR data) and geodata (coming from online open-data sources or datasets held by local institutions) which are further developed inside GIS-based procedural modeling digital environment (Biljecki et al, 2015;Nys et al, 2020;Wang et al, 2018, Pârvu et al, 2018. Top-down models usually don't need any further integration (unlike bottomup models) with exception for indoor data that are inserted via the conversion of IFC files into CityGML objects (Biljecki et al, 2021).…”
Section: City Information Modelingmentioning
confidence: 99%
“…In these models CD is applied, through Visual Programming Languages (VPL), to link, sort and merge metadata between models and environments but not for modeling purposes. The top-down procedures deal mainly with long-range remote sensing techniques (e.g., Airborne LiDAR data) and geodata (coming from online open-data sources or datasets held by local institutions) which are further developed inside GIS-based procedural modeling digital environment (Biljecki et al, 2015;Nys et al, 2020;Wang et al, 2018, Pârvu et al, 2018. Top-down models usually don't need any further integration (unlike bottomup models) with exception for indoor data that are inserted via the conversion of IFC files into CityGML objects (Biljecki et al, 2021).…”
Section: City Information Modelingmentioning
confidence: 99%
“…Furthermore, most of the programming languages are able to produce the required structures by combining two basic data structures, namely ordered lists and key-value pairs [19]. In addition to the development of the encoding format itself, various tools for producing CityJSON data have been developed and reported [20,21]. However, as the CityJSON is still a fairly new development, its use has not been extensively discussed in the literature yet, apart from few data integration applications [22].…”
Section: D City Model Encoding Format Cityjsonmentioning
confidence: 99%
“…However, for several reasons, among which the fact that such models are intended for a very wide scope, they are very complex and quite difficult to be implemented [45], also for being based on the Geography Markup Language (GML) format. Recently, CityJSON 12 was proposed as an alternative solution and approved by OGC, starting from a different implementation of the CityGML v.2.0 schema [46] and was proved to be very effective from an implementation point of view [47,48,49,50,51].…”
Section: Geoinformation and Related Open Standardsmentioning
confidence: 99%