INTEGRATION OF 3D OBJECTS AND TERRAIN FOR 3D MODELLING SUPPORTING THE DIGITAL TWIN

19 citations as recorded by crossref.

1. Modeling Buildings in CityGML LOD1: Building Parts, Terrain Intersection Curve, and Address Features E. Shirinyan & D. Petrova-Antonova
2. BIM-Based Digital Twin and XR Devices to Improve Maintenance Procedures in Smart Buildings: A Literature Review C. Coupry et al.
3. Smart City Digital Twin Framework for Real-Time Multi-Data Integration and Wide Public Distribution L. Adreani et al.
4. Digital twin and its applications: A survey R. Zhang et al.
5. A framework supporting green stormwater management for urban designers J. Jia et al.
6. Segment Anything Model-Based Building Footprint Extraction for Residential Complex Spatial Assessment Using LiDAR Data and Very High-Resolution Imagery Y. Ji et al.
7. The Digital Landscape of Smart Cities and Digital Twins: A Systematic Literature Review of Digital Terrain and 3D City Models in Enhancing Decision-Making S. Syed Abdul Rahman et al.
8. Urban Echoes: Exploring the Dynamic Realities of Cities through Digital Twins P. Boccardo et al.
9. Spaces in Spatial Science and Urban Applications—State of the Art Review S. Zlatanova et al.
10. Finding outdoor boundaries for 3D space‐based navigation J. Yan et al.
11. Digital twin modeling F. Tao et al.
12. Efficient Procedure of Building University Campus Models for Digital Twin Simulation T. Azfar et al.
13. A design-support framework to assess urban green spaces for human wellbeing J. Jia et al.
14. City Digital Twin Potentials: A Review and Research Agenda E. Shahat et al.
15. A Prior Level Fusion Approach for the Semantic Segmentation of 3D Point Clouds Using Deep Learning Z. Ballouch et al.
16. Digital twin-supported smart city: Status, challenges and future research directions H. Wang et al.
17. A framework for extracting and characterizing landform structures under buildings using elevation thresholds and K-means algorithm S. Syed Abdul Rahman et al.
18. A Passive Radar for Urban Ubiquitous Sensing: Building Facade Ranging With GNSS-IR M. Ye & G. Zhang
19. Revolutionizing urban mapping: deep learning and data fusion strategies for accurate building footprint segmentation P. Dabove et al.