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THE SPATIAL DATA INFRASTRUCTURE OF AN URBAN DIGITAL TWIN IN THE BUILDING ENERGY DOMAIN USING OGC STANDARDS.
- Source :
- ISPRS Annals of Photogrammetry, Remote Sensing & Spatial Information Sciences; 2022, Vol. 10 Issue 4/W2, p249-256, 8p
- Publication Year :
- 2022
-
Abstract
- As the world has more urbanized, cities need to assess and manage their building energy performances in order to achieve energy-reduction goals. The urban digital twins (UDT) offer promising solutions to this demand by providing valuable insights with qualitative and quantitative information about the building environment. The urban building energy data is not only measured from the equipped sensor devices but can also be simulated based on the analysis software. In this research, we aim to explore the development of the spatial data infrastructure (SDI) for managing building energy in the UDT application by employing the Open Geospatial Consortium (OGC) standards which increases the data usability and efficiency. In our concept SDI, the big data in the UDT application is managed with the OGC specifications as follows: OGC SensorThings API (STA) for data with Spatio-temporal characteristics, OGC API 3D GeoVolumes for 3D geospatial content delivery, OGC CityGML for virtual 3D city models, OGC API Features, Web Feature Service (WFS), and Web Map Service (WMS) for other 2D geospatial contents. This concept enables broad interoperability between multiple data layers and client applications. As a proof of concept, we developed the UDT application called with a highly visual and intuitive user interface using the proposed SDI concept as a part of the EnSysLE project in the study area of three regions in Germany: Ludwigsburg, Dithmarschen, and Ilm-Kreis. The proposed concept can be expanded to other UDT domains and on a larger scale in future work. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 21949042
- Volume :
- 10
- Issue :
- 4/W2
- Database :
- Complementary Index
- Journal :
- ISPRS Annals of Photogrammetry, Remote Sensing & Spatial Information Sciences
- Publication Type :
- Academic Journal
- Accession number :
- 160091933
- Full Text :
- https://doi.org/10.5194/isprs-annals-X-4-W2-2022-249-2022