Using environmental, population and built environment data to understand climate-related health vulnerability in greening cities

Abstract

ABSTRACT To tackle the negative health impacts that rising urban temperatures can have on residents, cities are increasingly prioritising the greening of urban areas. However, with limited funds, time, and other resources available to city authorities and urban planners there is a need to better understand where this urban greening investment should be targeted. Current strategies often rely on proximity-based measures to understand accessibility of greenspace. These measures, however, do not account for other types of greening that can bring a range of benefits to residents or consider other factors alongside proximity, such as population characteristics that may increase vulnerability to climate-related health risks. To address these challenges, this study constructs a granular classification based on the characteristics that influence heat-related climate vulnerability. Metrics that capture the socioeconomic, demographic, environmental, and built environment factors that can impact vulnerability are constructed at a building-block level. A k-means clustering approach is then employed to classify building-blocks based on these metrics, resulting in seven clusters that each exhibit distinct characteristics and varying degrees of vulnerability. This study demonstrates how combining environmental, population, and built environment data at a granular scale can aid decision-making and improve the targeting of urban greening investment.