Affiliation:
1. School of Geomatics and Urban Spatial Information, Beijing University of Civil Engineering and Architecture, Beijing 100044, China
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.
Funder
Shanxi Institute of Surveying, Mapping and Geoinformation
Reference32 articles.
1. Chuang, T.Y., and Sung, C.C. (2020). Learning and SLAM based Decision Support Platform for Sewer Inspection. Remote Sens., 12.
2. Menzel, J.R., Middelberg, S., Trettner, P., Jonas, B., and Kobbelt, L. (2016, January 8). City Reconstruction and Visualization from Public Data Sources. Proceedings of the Eurographics Workshop on Urban Data Modelling and Visualisation, Liège, Belgium.
3. Deininger, M.E., von der Grün, M., Piepereit, R., Schneider, S., Santhanavanich, T., Coors, V., and Voß, U. (2020). A Continuous, Semi-Automated Workflow: From 3D City Models with Geometric Optimization and CFD Simulations to Visualization of Wind in an Urban Environment. Int. J. Geo-Inf., 9.
4. Application analysis of geographic information system in the era of big data;Fuling;Sci. Technol. Innov. Appl.,2022
5. A new geospatial overlay method for the analysis and visualization of spatial change patterns using object-oriented data modeling concepts;Tiede;Cartogr. Geogr. Inf. Sci.,2014