Towards Urban Digital Twins: A Workflow for Procedural Visualization Using Geospatial Data
Artikel i vetenskaplig tidskrift, 2024

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.

urban simulation

geospatial visualization

procedural generation

spatial data analysis

3D reconstruction

digital twin

LiDAR integration

Författare

Sanjay Somanath

Chalmers, Arkitektur och samhällsbyggnadsteknik, Byggnadsteknologi

Vasilis Naserentin

Chalmers, Matematiska vetenskaper, Tillämpad matematik och statistik

Orfeas Eleftheriou

Chalmers, Matematiska vetenskaper, Tillämpad matematik och statistik

Daniel Sjölie

Chalmers, Data- och informationsteknik, Interaktionsdesign och Software Engineering

Beata Stahre Wästberg

Chalmers, Data- och informationsteknik, Interaktionsdesign och Software Engineering

Anders Logg

Chalmers, Matematiska vetenskaper, Tillämpad matematik och statistik

Remote Sensing

20724292 (eISSN)

Vol. 16 11 1939

MiljöVis - Effektiv representation av miljöinformation i infrastrukturmodeller

Trafikverket (TRV 2020/9876), 2020-01-01 -- 2021-04-30.

Ämneskategorier

Annan data- och informationsvetenskap

Data- och informationsvetenskap

Styrkeområden

Informations- och kommunikationsteknik

Building Futures (2010-2018)

Drivkrafter

Hållbar utveckling

Fundament

Grundläggande vetenskaper

DOI

10.3390/rs16111939

Mer information

Senast uppdaterat

2024-06-03