High-Precision Optimization of BIM-3D GIS Models for Digital Twins: A Case Study of Santun River Basin
The integration of Building Information Modeling (BIM) and 3D Geographic Information System (3D GIS) models provides high-precision spatial data for digital twin watersheds. To tackle the challenges of large data volumes and rendering latency in integrated models, this study proposes a three-step fr...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-07-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/25/15/4630 |
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| author | Zhengbing Yang Mahemujiang Aihemaiti Beilikezi Abudureheman Hongfei Tao |
| author_facet | Zhengbing Yang Mahemujiang Aihemaiti Beilikezi Abudureheman Hongfei Tao |
| author_sort | Zhengbing Yang |
| collection | DOAJ |
| description | The integration of Building Information Modeling (BIM) and 3D Geographic Information System (3D GIS) models provides high-precision spatial data for digital twin watersheds. To tackle the challenges of large data volumes and rendering latency in integrated models, this study proposes a three-step framework that uses Industry Foundation Classes (IFCs) as the base model and Open Scene Graph Binary (OSGB) as the target model: (1) geometric optimization through an angular weighting (AW)-controlled Quadric Error Metrics (QEM) algorithm; (2) Level of Detail (LOD) hierarchical mapping to establish associations between the IFC and OSGB models, and redesign scene paging logic; (3) coordinate registration by converting the IFC model’s local coordinate system to the global coordinate system and achieving spatial alignment via the seven-parameter method. Applied to the Santun River Basin digital twin project, experiments with 10 water gate models show that the AW-QEM algorithm reduces average loading time by 15% compared to traditional QEM, while maintaining 97% geometric accuracy, demonstrating the method’s efficiency in balancing precision and rendering performance. |
| format | Article |
| id | doaj-art-d1d28c46238b4e56bffdd6e70b2fb0aa |
| institution | DOAJ |
| issn | 1424-8220 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj-art-d1d28c46238b4e56bffdd6e70b2fb0aa2025-08-20T03:04:43ZengMDPI AGSensors1424-82202025-07-012515463010.3390/s25154630High-Precision Optimization of BIM-3D GIS Models for Digital Twins: A Case Study of Santun River BasinZhengbing Yang0Mahemujiang Aihemaiti1Beilikezi Abudureheman2Hongfei Tao3College of Hydraulic and Civil Engineering, Xinjiang Agricultural University, Urumqi 830052, ChinaCollege of Hydraulic and Civil Engineering, Xinjiang Agricultural University, Urumqi 830052, ChinaCollege of Hydraulic and Civil Engineering, Xinjiang Agricultural University, Urumqi 830052, ChinaCollege of Hydraulic and Civil Engineering, Xinjiang Agricultural University, Urumqi 830052, ChinaThe integration of Building Information Modeling (BIM) and 3D Geographic Information System (3D GIS) models provides high-precision spatial data for digital twin watersheds. To tackle the challenges of large data volumes and rendering latency in integrated models, this study proposes a three-step framework that uses Industry Foundation Classes (IFCs) as the base model and Open Scene Graph Binary (OSGB) as the target model: (1) geometric optimization through an angular weighting (AW)-controlled Quadric Error Metrics (QEM) algorithm; (2) Level of Detail (LOD) hierarchical mapping to establish associations between the IFC and OSGB models, and redesign scene paging logic; (3) coordinate registration by converting the IFC model’s local coordinate system to the global coordinate system and achieving spatial alignment via the seven-parameter method. Applied to the Santun River Basin digital twin project, experiments with 10 water gate models show that the AW-QEM algorithm reduces average loading time by 15% compared to traditional QEM, while maintaining 97% geometric accuracy, demonstrating the method’s efficiency in balancing precision and rendering performance.https://www.mdpi.com/1424-8220/25/15/4630IFCOSGBQEM algorithmLOD |
| spellingShingle | Zhengbing Yang Mahemujiang Aihemaiti Beilikezi Abudureheman Hongfei Tao High-Precision Optimization of BIM-3D GIS Models for Digital Twins: A Case Study of Santun River Basin Sensors IFC OSGB QEM algorithm LOD |
| title | High-Precision Optimization of BIM-3D GIS Models for Digital Twins: A Case Study of Santun River Basin |
| title_full | High-Precision Optimization of BIM-3D GIS Models for Digital Twins: A Case Study of Santun River Basin |
| title_fullStr | High-Precision Optimization of BIM-3D GIS Models for Digital Twins: A Case Study of Santun River Basin |
| title_full_unstemmed | High-Precision Optimization of BIM-3D GIS Models for Digital Twins: A Case Study of Santun River Basin |
| title_short | High-Precision Optimization of BIM-3D GIS Models for Digital Twins: A Case Study of Santun River Basin |
| title_sort | high precision optimization of bim 3d gis models for digital twins a case study of santun river basin |
| topic | IFC OSGB QEM algorithm LOD |
| url | https://www.mdpi.com/1424-8220/25/15/4630 |
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