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Sökning: AMNE:(NATURVETENSKAP Data- och informationsvetenskap Datorseende och robotik) > (2020-2024) > Towards Urban Digit...

Towards Urban Digital Twins: A Workflow for Procedural Visualization Using Geospatial Data

Somanath, Sanjay, 1994 (författare)
Chalmers tekniska högskola,Chalmers University of Technology
Naserentin, Vasilis, 1981 (författare)
Aristotelio Panepistimio Thessalonikis,Aristotle University of Thessaloniki,Chalmers tekniska högskola,Chalmers University of Technology
Eleftheriou, Orfeas, 1994 (författare)
Aristotelio Panepistimio Thessalonikis,Aristotle University of Thessaloniki,Chalmers tekniska högskola,Chalmers University of Technology
visa fler...
Sjölie, Daniel, 1977 (författare)
Högskolan Väst,University West,Chalmers tekniska högskola,Chalmers University of Technology
Stahre Wästberg, Beata, 1974 (författare)
Chalmers tekniska högskola,Chalmers University of Technology
Logg, Anders, 1976 (författare)
Chalmers tekniska högskola,Chalmers University of Technology
visa färre...
 (creator_code:org_t)
2024
2024
Engelska.
Ingår i: Remote Sensing. - 2072-4292. ; 16:11
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
Stäng  
  • A key feature for urban digital twins (DTs) is an automatically generated detailed 3D representation of the built and unbuilt environment from aerial imagery, footprints, LiDAR, or a fusion of these. Such 3D models have applications in architecture, civil engineering, urban planning, construction, real estate, Geographical Information Systems (GIS), and many other areas. While the visualization of large-scale data in conjunction with the generated 3D models is often a recurring and resource-intensive task, an automated workflow is complex, requiring many steps to achieve a high-quality visualization. Methods for building reconstruction approaches have come a long way, from previously manual approaches to semi-automatic or automatic approaches. This paper aims to complement existing methods of 3D building generation. First, we present a literature review covering different options for procedural context generation and visualization methods, focusing on workflows and data pipelines. Next, we present a semi-automated workflow that extends the building reconstruction pipeline to include procedural context generation using Python and Unreal Engine. Finally, we propose a workflow for integrating various types of large-scale urban analysis data for visualization. We conclude with a series of challenges faced in achieving such pipelines and the limitations of the current approach. However, the steps for a complete, end-to-end solution involve further developing robust systems for building detection, rooftop recognition, and geometry generation and importing and visualizing data in the same 3D environment, highlighting a need for further research and development in this field.

Ämnesord

NATURVETENSKAP  -- Data- och informationsvetenskap -- Annan data- och informationsvetenskap (hsv//swe)
NATURAL SCIENCES  -- Computer and Information Sciences -- Other Computer and Information Science (hsv//eng)
NATURVETENSKAP  -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
NATURAL SCIENCES  -- Computer and Information Sciences -- Computer Sciences (hsv//eng)
NATURVETENSKAP  -- Data- och informationsvetenskap -- Datorseende och robotik (hsv//swe)
NATURAL SCIENCES  -- Computer and Information Sciences -- Computer Vision and Robotics (hsv//eng)
NATURVETENSKAP  -- Data- och informationsvetenskap (hsv//swe)
NATURAL SCIENCES  -- Computer and Information Sciences (hsv//eng)

Nyckelord

urban simulation
spatial data analysis
LiDAR integration
geospatial visualization
3D reconstruction
digital twin
procedural generation

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