They also considered the changes in various factors and their relationship to TCE across different global regions over the period. Using meteorological data from the European Centre for Medium-Range Weather Forecasts, the researchers ran a machine learning model to determine the relative importance of potential key factors in determining TCE.

TCE is defined as the reduction in temperature that is achieved by increasing tree cover by 1%, measured in degrees Celsius per percent (☌/%). The researchers used satellite data on tree cover and land temperature from the NASA Landsat programme to model the ‘tree cooling efficiency’ (TCE) of 806 cities around the world between 20. This study aimed to use big data to reveal some of the main factors that could inform decisions about urban tree planting programmes. However, the specific conditions which determine the relative effectiveness of this strategy across contexts is not fully understood.

Planting trees in urban areas is a popular strategy (both in Europe and worldwide) for reducing temperatures in cities under global warming.

Global city regions: