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Spatial Data Fusion Model Design and Research for an Underground Pipeline in Urban Environment Scene Modeling.

Authors :
Shen, Tao
Zhang, Huabin
Huo, Liang
Sun, Di
Source :
Applied Sciences (2076-3417); Aug2024, Vol. 14 Issue 15, p6760, 13p
Publication Year :
2024

Abstract

In the rapid development of urban construction, underground pipelines play a crucial role. However, the current underground pipelines have poor association with relevant management departments, and there are deficiencies in data completeness, accuracy, and information content. Managing and sharing information resources is relatively difficult, transforming the constructed 3D underground pipeline geographic information systems into an 'Information silo'. This results in redundant construction and resource wastage of underground utilities. The complex distribution characteristics of underground utilities make rapid batch modeling and post-model maintenance challenging. Therefore, researching a 3D spatial data fusion model for urban underground utilities becomes particularly important. Given the above problem, this paper proposes a spatial data fusion model for underground pipeline scene modeling. It elaborates on the geometric, semantic, and temporal characteristics of underground pipelines, encapsulating these features. With underground pipeline objects as the core and pipeline characteristics as the foundation, a spatial data fusion model integrating multiple characteristics of underground pipelines has been constructed. Through software development, the data model designed in this paper facilitates rapid construction of underground pipeline scenes. This further enhances the consistency and integrity of underground pipeline data, enabling shared resources and comprehensive supervision of facility operations on a daily basis. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20763417
Volume :
14
Issue :
15
Database :
Complementary Index
Journal :
Applied Sciences (2076-3417)
Publication Type :
Academic Journal
Accession number :
178949733
Full Text :
https://doi.org/10.3390/app14156760