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Good practice Imported

Virtual Singapore — National 3D Digital Twin for Urban Planning

Singapore · Singapore · See the Singapore profile · See the Singapore profile

Evidence: Descriptive / self-reported Top 74% 57/100 · Ask Evidence Copilot about this practice

Singapore's national 3D digital twin, built with Dassault Systèmes from 2014–2022 using 50+ terabytes of geospatial data, lets planners simulate flood risk, AV routes and solar potential — though most cited benefits remain simulated, not independently measured.

50+ terabytes
Geospatial and infrastructure data integrated
Virtual Singapore — National 3D Digital Twin for Urban Planning

Details

Maturity
Established
Promoter
Singapore Land Authority / National Research Foundation / GovTech
Period
2014–2022 (build); ongoing operation
Keywords
digital twin, urban planning, geospatial data, disaster simulation

Context

Announced as part of the Smart Nation initiative on 3 December 2014 and led jointly by the Singapore Land Authority, the National Research Foundation and the Government Technology Agency, Virtual Singapore is a high-resolution 3D digital model of the entire city-state, built on Dassault Systemes' 3DEXPERIENCity platform using laser-scanning aircraft and vehicles.

Activities

The platform integrates more than 50 terabytes of geospatial, infrastructure and environmental data, funded jointly by the national government and partner agencies including the Civil Aviation Authority of Singapore and the Public Utilities Board.

Results

Documented use cases include flood-risk analysis, testing autonomous-vehicle routing without street deployment, assessing solar-panel and green-roof potential on building rooftops, and simulating emergency-response scenarios. The core platform was completed in 2022 after an eight-year build.

Conclusions

Independent reporting documents the platform's use cases and scale in detail but does not report independently measured before/after outcomes -- most cited benefits remain described as anticipated or simulated rather than empirically evaluated.

Implementation
Indicative cost
Very high (> €5M) — National-scale platform; specific cost not disclosed.
Time to results
Long (> 3 years) — Announced December 2014; core platform completed 2022 after an eight-year build.
Staffing & skills
Singapore Land Authority, National Research Foundation, Government Technology Agency

Conditions for success

  • multi-agency co-funding (national government, aviation authority, utilities board)
  • laser-scanning data capture across the entire city-state
  • a shared commercial platform (3DEXPERIENCity) supporting varied use cases

Common failure modes

  • most cited benefits remain anticipated or simulated rather than empirically evaluated

Where it fits

Governance type
national government, multi-agency
Scale
national (entire city-state)
Income level
high income

Commonly funded by

National / regional programmes

Indicative funding routes for practices of this type — always check each programme's current calls and eligibility rules.

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Data sources

Where this practice's information was retrieved from, and when.

Attachments

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