Next Article in Journal
Spatiotemporal Evolution of Urban Expansion Using Landsat Time Series Data and Assessment of Its Influences on Forests
Previous Article in Journal
Conciliating Perspectives from Mapping Agencies and Web of Data on Successful European SDIs: Toward a European Geographic Knowledge Graph
Open AccessArticle

Towards Integrating Heterogeneous Data: A Spatial DBMS Solution from a CRC-LCL Project in Australia

Faculty of the Built Environment, The University of New South Wales, Kensington 2052, Australia
*
Author to whom correspondence should be addressed.
This Paper Is an Extended Version of Our Paper Published in GI4SDG 2019.
ISPRS Int. J. Geo-Inf. 2020, 9(2), 63; https://doi.org/10.3390/ijgi9020063
Received: 30 December 2019 / Revised: 13 January 2020 / Accepted: 19 January 2020 / Published: 21 January 2020
Over recent decades, more and more cities worldwide have created semantic 3D city models of their built environments based on standards across multiple domains. 3D city models, which are often employed for a large range of tasks, go far beyond pure visualization. Due to different spatial scale requirements for planning and managing various built environments, integration of Geographic Information Systems (GIS) and Building Information Modeling (BIM) has emerged in recent years. Focus is now shifting to Precinct Information Modeling (PIM) which is in a more general sense to built-environment modeling. As scales change so do options to perform information modeling for different applications. How to implement data interoperability across these digital representations, therefore, becomes an emerging challenge. Moreover, with the growth of multi-source heterogeneous data consisting of semantic and varying 2D/3D spatial representations, data management becomes feasible for facilitating the development and deployment of PIM applications. How to use heterogeneous data in an integrating manner to further express PIM is an open and comprehensive topic. In this paper, we develop a semantic PIM based on multi-source heterogeneous data. Then, we tackle spatial data management problems in a Spatial Database Management System (SDBMS) solution for our defined unified model. Case studies on the University of New South Wales (UNSW) campus demonstrate the efficiency of our solution. View Full-Text
Keywords: SDBMS; built environment; PIM; 3D city model; CityGML; IFC SDBMS; built environment; PIM; 3D city model; CityGML; IFC
Show Figures

Figure 1

MDPI and ACS Style

Li, W.; Zlatanova, S.; Diakite, A.A.; Aleksandrov, M.; Yan, J. Towards Integrating Heterogeneous Data: A Spatial DBMS Solution from a CRC-LCL Project in Australia. ISPRS Int. J. Geo-Inf. 2020, 9, 63.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop