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As cities face growing pressure from climate change, biodiversity loss, and urbanization, there is an urgent need for data-driven tools to support the planning and resilience of green infrastructure. This paper presents a methodology for developing Urban Digital Twins (UDTs) focused on green space planning, monitoring, and regeneration. The process begins with the identification of Key Performance Indicators (KPIs) across five thematic areas: pollution and climate, natural environment, ecosystems, human perception, and public awareness. Based on these KPIs, a set of enabling digital technologies is evaluated through expert ranking, using Kendall’s W concordance coefficient to assess consensus on their relevance. The results highlight strong agreement among experts, with IoT, GIS, and BIM emerging as the most suitable technologies due to their capacity for real-time sensing, semantic integration, and spatial representation. Drawing from these insights, the paper proposes a five-layer reference architecture for UDTs designed to support adaptive, inclusive, and data-driven urban greening efforts. The findings offer guidance for cities and stakeholders aiming to implement UDTs for urban resilience.

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Urban Digital Twin Data Requirements and Reference Architecture for Green Spaces and Ecosystems

  • 会议论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年

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  • Lina Morkunaite,
  • Darius Pupeikis,
  • Vytautas Bocullo,
  • Egle Klumbyte,
  • Andrea Conserva,
  • Chiara Farinea,
  • Alice Bazzica,
  • Peter Barmann,
  • Fruzsina Csala

摘要

As cities face growing pressure from climate change, biodiversity loss, and urbanization, there is an urgent need for data-driven tools to support the planning and resilience of green infrastructure. This paper presents a methodology for developing Urban Digital Twins (UDTs) focused on green space planning, monitoring, and regeneration. The process begins with the identification of Key Performance Indicators (KPIs) across five thematic areas: pollution and climate, natural environment, ecosystems, human perception, and public awareness. Based on these KPIs, a set of enabling digital technologies is evaluated through expert ranking, using Kendall’s W concordance coefficient to assess consensus on their relevance. The results highlight strong agreement among experts, with IoT, GIS, and BIM emerging as the most suitable technologies due to their capacity for real-time sensing, semantic integration, and spatial representation. Drawing from these insights, the paper proposes a five-layer reference architecture for UDTs designed to support adaptive, inclusive, and data-driven urban greening efforts. The findings offer guidance for cities and stakeholders aiming to implement UDTs for urban resilience.