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<p>Cities are increasingly threatened by the effects of rising temperatures. Due to the heat island effect, cities experience greater heat stress, leading to increased energy demand and reduced quality of life. Vertical greenery systems (VGSs), such as green façades and living walls, offer a spatially efficient strategy to mitigate these impacts. The environmental and social benefits of vertical greenery are well established. However, large-scale implementation is lacking methods that integrate relevant data to compute the variety of factors determining a surface’s suitability. This paper aims to fill this gap by introducing a computational method for evaluating the potential of individual building walls for vertical greening. Using the city of Leipzig as a case study, the approach integrates Level of Detail 2 (LoD2) building data with street view imagery to compute key factors such as orientation or Window-to-Wall Ratio (WWR). These factors are then integrated into a composite index prioritizing walls with high potential for reducing urban heat stress. The study thus provides a practical tool for urban planners and policymakers to support targeted climate adaptation strategies.</p>

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Automated estimation of urban vertical greenery potential

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年6月23日

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  • Aruscha Kramm,
  • Isabel Holler,
  • Eric Peukert,
  • André Ludwig,
  • Bogdan Franczyk

摘要

Cities are increasingly threatened by the effects of rising temperatures. Due to the heat island effect, cities experience greater heat stress, leading to increased energy demand and reduced quality of life. Vertical greenery systems (VGSs), such as green façades and living walls, offer a spatially efficient strategy to mitigate these impacts. The environmental and social benefits of vertical greenery are well established. However, large-scale implementation is lacking methods that integrate relevant data to compute the variety of factors determining a surface’s suitability. This paper aims to fill this gap by introducing a computational method for evaluating the potential of individual building walls for vertical greening. Using the city of Leipzig as a case study, the approach integrates Level of Detail 2 (LoD2) building data with street view imagery to compute key factors such as orientation or Window-to-Wall Ratio (WWR). These factors are then integrated into a composite index prioritizing walls with high potential for reducing urban heat stress. The study thus provides a practical tool for urban planners and policymakers to support targeted climate adaptation strategies.