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Towards Urban Digit...
Towards Urban Digital Twins: A Workflow for Procedural Visualization Using Geospatial Data
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- Somanath, Sanjay, 1994 (author)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Naserentin, Vasilis, 1981 (author)
- Aristotelio Panepistimio Thessalonikis,Aristotle University of Thessaloniki,Chalmers tekniska högskola,Chalmers University of Technology
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- Eleftheriou, Orfeas, 1994 (author)
- Aristotelio Panepistimio Thessalonikis,Aristotle University of Thessaloniki,Chalmers tekniska högskola,Chalmers University of Technology
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- Sjölie, Daniel, 1977 (author)
- Högskolan Väst,University West,Chalmers tekniska högskola,Chalmers University of Technology
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- Stahre Wästberg, Beata, 1974 (author)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Logg, Anders, 1976 (author)
- Chalmers tekniska högskola,Chalmers University of Technology
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(creator_code:org_t)
- 2024
- 2024
- English.
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In: Remote Sensing. - 2072-4292. ; 16:11
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https://doi.org/10.3...
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Abstract
Subject headings
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- 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.
Subject headings
- 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)
Keyword
- urban simulation
- spatial data analysis
- LiDAR integration
- geospatial visualization
- 3D reconstruction
- digital twin
- procedural generation
Publication and Content Type
- art (subject category)
- ref (subject category)
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