Increasing level of detail of buildings for improved simulation of 4D urban digital twin.
Buildings represent a crucial component of urban morphology, and their accurate modelling is essential for a number of applications involving Urban Digital Twins. With respect to thermal simulation aiming to identify Urban Heat Islands, a trade-off between accurate modelling of a single building typ...
| Main Authors: | , , , , , |
|---|---|
| Format: | Conference Paper |
| Language: | English |
| Published: |
University of Strathclyde Publishing
2022
|
| Online Access: | http://hdl.handle.net/20.500.11937/88570 |
| _version_ | 1848765041625530368 |
|---|---|
| author | Bulatov, Dimitri May, Marie Strauss, Eva Mancini, Francesco Kottler, Benedikt Helmholz, Petra |
| author_facet | Bulatov, Dimitri May, Marie Strauss, Eva Mancini, Francesco Kottler, Benedikt Helmholz, Petra |
| author_sort | Bulatov, Dimitri |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Buildings represent a crucial component of urban morphology, and their accurate modelling is essential for a number of applications involving Urban Digital Twins. With respect to thermal simulation aiming to identify Urban Heat Islands, a trade-off between accurate modelling of a single building type and large-scale reconstruction of virtual city models needs to be found. In the proposed paper, we analyzed an Australian suburb containing approximately 1700 residential buildings with challenging roof structures. Building outlines are provided by geo-information data and converted into prismatic models of LOD1. Using airborne sensor data (digital orthophotos, high-resolution images, and digital surface models), we identified two ways to increase the LOD and thus, the accuracy of the simulation. Firstly, we used common Computer-Aided Graphics software to model interactively a few selected buildings, a process denoted as geo-specific modelling. Here, the outlines were used as foundations for constructing the ground-level walls. We relied on airborne data to retrieve building heights and roof structures. A number of floors and positions of façade elements were modelled on standard typological assumptions and building practices. We developed an interface to import automatically LOD1- based data and export LOD3 buildings into the simulation. Secondly, we reproduce these models to model other buildings in the dataset. For this so-called geo-typical modelling, a similarity measure based on the outlines was implemented. The final scene consists of triangles modelling LOD3 buildings, terrain, and trees, retrieved using machine-learning-based methods on land cover classification. Together with the semantic class, we store the geometrical and physical properties of every triangle. The environmental data (e.g., cloud coverage, air temperature) is available by means of the weather services. Surface temperature is modelled by considering conductive, convective, and radiative heat transfer. The simulation of updated LOD3 buildings shows a significantly increased realism of the temperature distribution in an urban area. It can be used to verify the sustainable design of appropriate morpho-typologies for a particular precinct in a given context. |
| first_indexed | 2025-11-14T11:28:57Z |
| format | Conference Paper |
| id | curtin-20.500.11937-88570 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T11:28:57Z |
| publishDate | 2022 |
| publisher | University of Strathclyde Publishing |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-885702022-06-07T03:34:45Z Increasing level of detail of buildings for improved simulation of 4D urban digital twin. Bulatov, Dimitri May, Marie Strauss, Eva Mancini, Francesco Kottler, Benedikt Helmholz, Petra Buildings represent a crucial component of urban morphology, and their accurate modelling is essential for a number of applications involving Urban Digital Twins. With respect to thermal simulation aiming to identify Urban Heat Islands, a trade-off between accurate modelling of a single building type and large-scale reconstruction of virtual city models needs to be found. In the proposed paper, we analyzed an Australian suburb containing approximately 1700 residential buildings with challenging roof structures. Building outlines are provided by geo-information data and converted into prismatic models of LOD1. Using airborne sensor data (digital orthophotos, high-resolution images, and digital surface models), we identified two ways to increase the LOD and thus, the accuracy of the simulation. Firstly, we used common Computer-Aided Graphics software to model interactively a few selected buildings, a process denoted as geo-specific modelling. Here, the outlines were used as foundations for constructing the ground-level walls. We relied on airborne data to retrieve building heights and roof structures. A number of floors and positions of façade elements were modelled on standard typological assumptions and building practices. We developed an interface to import automatically LOD1- based data and export LOD3 buildings into the simulation. Secondly, we reproduce these models to model other buildings in the dataset. For this so-called geo-typical modelling, a similarity measure based on the outlines was implemented. The final scene consists of triangles modelling LOD3 buildings, terrain, and trees, retrieved using machine-learning-based methods on land cover classification. Together with the semantic class, we store the geometrical and physical properties of every triangle. The environmental data (e.g., cloud coverage, air temperature) is available by means of the weather services. Surface temperature is modelled by considering conductive, convective, and radiative heat transfer. The simulation of updated LOD3 buildings shows a significantly increased realism of the temperature distribution in an urban area. It can be used to verify the sustainable design of appropriate morpho-typologies for a particular precinct in a given context. 2022 Conference Paper http://hdl.handle.net/20.500.11937/88570 10.17868/strath.00080499 English http://creativecommons.org/licenses/by/4.0/ University of Strathclyde Publishing fulltext |
| spellingShingle | Bulatov, Dimitri May, Marie Strauss, Eva Mancini, Francesco Kottler, Benedikt Helmholz, Petra Increasing level of detail of buildings for improved simulation of 4D urban digital twin. |
| title | Increasing level of detail of buildings for improved simulation of 4D urban digital twin. |
| title_full | Increasing level of detail of buildings for improved simulation of 4D urban digital twin. |
| title_fullStr | Increasing level of detail of buildings for improved simulation of 4D urban digital twin. |
| title_full_unstemmed | Increasing level of detail of buildings for improved simulation of 4D urban digital twin. |
| title_short | Increasing level of detail of buildings for improved simulation of 4D urban digital twin. |
| title_sort | increasing level of detail of buildings for improved simulation of 4d urban digital twin. |
| url | http://hdl.handle.net/20.500.11937/88570 |