Thermal Intelligence
The Thermal Impacts of Urban Densification : Using Deep Learning for climate assessments of urban development scenarios in Rotterdam
Y. Yang (TU Delft - Architecture and the Built Environment)
D. Maiullari – Mentor (TU Delft - Architecture and the Built Environment)
A. Ersoy – Mentor (TU Delft - Architecture and the Built Environment)
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Abstract
Faced with a growing population, the Dutch government is promoting development plans to increase built density and accommodate the demand of new homes within existing urban areas. However, high-density developments are widely considered to exacerbate heat risks, causing health risks for vulnerable populations. Despite the known heat-related impacts on urban livability, effective methods are currently lacking at the municipal level for adopting heat-sensitive densification strategies while the high computational cost of existing simulation tools makes rapid assessment of multiple planning scenarios difficult. To address these challenges, the study addresses a densification case in Rotterdam and develops an AI-based methodology to quantify the thermal impact of increasing density within an existing urban area. The U-Net approach is used to estimate Tmrt and PET at a resolution of 1 m based on SOLWEIG-calculated data. This model reaches very high levels of precision (R2 ≈ 0.95). It also allows rapid assessment of different scenarios while maintaining high resolution.
Nine densification scenarios with different floor space index and morphological configurations were tested through the U-Net model, showing that it can generate high speed prediction with high accuracy. The modelling results show that the morphological characteristics of the new buildings and street canyons, and the distribution of building masses lead to different levels of diurnal and nocturnal increase of temperature and thermal stress. On wider streets, densification through horizontal development contributes to higher Tmrt and PET compared to vertical development, as high-rise buildings cast more shade especially during the day. Besides, vertical development also exhibits less heat retention and foster better ventilation than horizontal development. In narrow streets, horizontal development has better shading and ventilation performance compared to vertical development. Although horizontal development slightly increases heat retention, the effect is minimal and can be reduced by the guiding airflow movements.