2021
DOI: 10.5194/isprs-annals-viii-4-w2-2021-105-2021
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Integration of 3d Point Clouds With Semantic 3d City Models – Providing Semantic Information Beyond Classification

Abstract: Abstract. A range of different and increasingly accessible acquisition methods, the possibility for frequent data updates of large areas, and a simple data structure are some of the reasons for the popularity of three-dimensional (3D) point cloud data. While there are multiple techniques for segmenting and classifying point clouds, capabilities of common data formats such as LAS for providing semantic information are mostly limited to assigning points to a certain category (classification). However, several fi… Show more

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Cited by 11 publications
(4 citation statements)
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“…This enables modeling of CityGML models at LoD3 (Gröger et al, 2012), or at so-called hybrid LoD with a fac ¸ade at LoD3 and a roof structure at LoD2 (Biljecki et al, 2016). Moreover, this feature can also be used for linking the segmented point clouds to existing building models without explicit reconstruction, as demonstrated by (Beil et al, 2021).…”
Section: Discussionmentioning
confidence: 99%
“…This enables modeling of CityGML models at LoD3 (Gröger et al, 2012), or at so-called hybrid LoD with a fac ¸ade at LoD3 and a roof structure at LoD2 (Biljecki et al, 2016). Moreover, this feature can also be used for linking the segmented point clouds to existing building models without explicit reconstruction, as demonstrated by (Beil et al, 2021).…”
Section: Discussionmentioning
confidence: 99%
“…Semantically segmented point clouds are the foundation for creating 3D city models. The resulting semantic models are used to create DTCs that support a plethora of urban applications [5].…”
Section: Introductionmentioning
confidence: 99%
“…Such models should not only enable rapid visualization of 3D datasets at different scales and with varying complexity, but they should also facilitate data processing during comprehensive analysis [19,21]. In the next stage of designing a smart city, 3D datasets describing individual buildings must be linked with semantic data [22] to create thematic applications [23]. The CityGML 3.0 Transportation Model also requires highly detailed models of street spaces, in particular buildings.…”
Section: Introductionmentioning
confidence: 99%
“…The CityGML 3.0 Transportation Model also requires highly detailed models of street spaces, in particular buildings. These models are utilized in autonomous vehicles [22,24] and other mobile mapping systems.…”
Section: Introductionmentioning
confidence: 99%