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Keywords = refined line/body topological relationship

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13 pages, 1845 KiB  
Article
Refinement and Computation Method for Line/Body Topological Relationships
by Xiaoguang Zhou, Xiaohan Wang, Dongyang Hou, Qiankun Kang and Nawaz Ali
Appl. Sci. 2024, 14(8), 3474; https://doi.org/10.3390/app14083474 - 20 Apr 2024
Viewed by 1326
Abstract
Three-dimensional topological relationships serve as a theoretical foundation for quality control, update processing, and spatial analysis of three-dimensional spatial data in real-world three-dimensional GIS. The existing 3D topological relationship models are all basic relationship models that cannot distinguish the refined topological relationship between [...] Read more.
Three-dimensional topological relationships serve as a theoretical foundation for quality control, update processing, and spatial analysis of three-dimensional spatial data in real-world three-dimensional GIS. The existing 3D topological relationship models are all basic relationship models that cannot distinguish the refined topological relationship between the line and the body with multiple intersections. In this study, we develop a 3D refined topological relationship description framework that draws from the two-dimensional refined topological relationship model, defines the unit intersection between the line and the body based on manifold topology, and proposes a method for describing the unit intersections between the line and the body considering Euler numbers and adjacency types. In total, 23 basic types between the line and the body are deduced. An example is provided to illustrate the distinguished refined topological relationship between the line and the body with multiple intersections. Subsequently, an algorithm for determining the basic type of line/body is developed. Finally, a line/body refined topological relationship computation prototype system is developed using the Nef polyhedron model, C++ language, and an open-source geometric algorithm library, and the effectiveness of our method is verified using actual building and pedestrian data. Full article
(This article belongs to the Special Issue Recent Advances in Geospatial Big Data Mining)
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