Abstract
Extreme heat events, exacerbated by climate change, are intensified in cities by the urban heat island (UHI) effect. A primary cause of UHI is the replacement of natural lands with buildings and roads, trapping heat in the city. Singapore, a high-rise high-density city state in Southeast Asia, has taken actions to mitigate UHI including the expansion of urban green spaces. Increasing urban greenery to mitigate UHI is one of many strategies being tested in the emerging field of climate-responsive city planning. To justify UHI mitigation planning strategies to city stakeholders, however, requires an ability to estimate effectiveness and efficiency in measures. This case study implements a generative urban model to evaluate UHI across a range of urban density scenarios, testing the impacts of both green space and building design strategies in three stages: (i) urban generative modeling, (ii) UHI prediction simulation, and (iii) urban data analysis. The study conducts urban generative modeling for a 100-ha site, using a model created to specifically reflect Singapore's development control guidelines. Across eight selected design parameters, an extensive set of design solutions (9,000) is obtained via a one-factor-at-a-time sampling method. The Urban Weather Generator tool is used to evaluate the UHI performance per solution. Design space exploration of the urban model and analysis of results identify best-performing UHI mitigation strategies, correlation among model parameters, and parameter significance. These results permit discussion of effective city planning and design strategies for UHI mitigation. Readers engaging with this case study will gain an understanding of the application of urban data analytics to climate-resilient city planning supported by generative urban models and UHI performance simulation.