Reimagining climate networking between cities: clustering cities based on a large dataset of mitigation actions

Abstract The existing networking dynamics in climate city networks are hierarchical as a few global cities are viewed as the leaders to be followed by other cities due to their higher visibility. Achieving ambitious climate goals requires expanding the knowledge of a diverse range of cities and networking opportunities. To expand knowledge of diverse cities, we provide evidence of cities’ similarity patterns based on their mitigation actions by a large-scale clustering method. Applying K-means clustering to Carbon Disclosure Project’s mitigation data, we find five clusters of cities based on two measures. Nature of actions indicates cities’ similarity based on their actions’ sectoral combinations, and finance profile indicates the commonality of their actions’ financial arrangements. Using these measures, we present a novel way to render socio-spatially diverse cities similar. Intersecting these two measures in a matrix, we offer ways to reimagine networking between cities and illuminate the complexity of cities’ climate actions.