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Abstract <p>Rising global temperatures from climate change have increased the risk of heat-related illnesses and deaths in urban areas. It is crucial to reduce heat stress impacts and enhance thermal comfort by applying practical urban transformation principles. At the same time, urban transformation has become more important due to increasing concerns about the risk of earthquakes in Istanbul. This study aims to develop scenario models to improve thermal comfort in different urban layouts. Thus, the Solar and LongWave Environmental Irradiance Geometry (SOLWEIG) model was used to simulate mean radiant temperature (<InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(T_{\mathrm{mrt}}\)</EquationSource> </InlineEquation>) using Light Detection and Ranging (LiDAR) data. Three urban geometry scenarios were developed depending on several factors, including Sky Visibility Factors (SVFs), Shadow Pattern Maps (SMs), building height, Plan Area Index (PAI), vegetation cover, and canyon width. The results indicate that the second scenario, which includes a more convenient layout, taller buildings, and more green space, is the most effective in improving thermal comfort in building redesign. This research provides a valuable perspective toward more sustainable and thermally comfortable environments, supporting urban transformation efforts.</p>

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Developing Scenario Model to Create Thermal Comfort City Using LiDAR Data

  • 期刊论文

  • 发表日期：

    2025年10月1日

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  • N. Bas

摘要

Abstract

Rising global temperatures from climate change have increased the risk of heat-related illnesses and deaths in urban areas. It is crucial to reduce heat stress impacts and enhance thermal comfort by applying practical urban transformation principles. At the same time, urban transformation has become more important due to increasing concerns about the risk of earthquakes in Istanbul. This study aims to develop scenario models to improve thermal comfort in different urban layouts. Thus, the Solar and LongWave Environmental Irradiance Geometry (SOLWEIG) model was used to simulate mean radiant temperature ( \(T_{\mathrm{mrt}}\) ) using Light Detection and Ranging (LiDAR) data. Three urban geometry scenarios were developed depending on several factors, including Sky Visibility Factors (SVFs), Shadow Pattern Maps (SMs), building height, Plan Area Index (PAI), vegetation cover, and canyon width. The results indicate that the second scenario, which includes a more convenient layout, taller buildings, and more green space, is the most effective in improving thermal comfort in building redesign. This research provides a valuable perspective toward more sustainable and thermally comfortable environments, supporting urban transformation efforts.