Cities are facing unprecedented challenges to their environments and residents due to continuous growth, including urban overheating, daylight accessibility, noise, and air pollution. This requires a holistic approach to the research and implementation of mitigation strategies, aiming at improving overall multidomain environmental quality. This study aims to develop a method for classifying neighbourhoods into identifiable types accounting for their distinctive multidomain environmental characteristics. The method uses a data-driven approach based on parameters describing urban morphology, land cover, and road network. A K-means algorithm was used to cluster 1583 neighbourhood units at the resolution of 250 m × 250 m in Geneva and Zurich, Switzerland. Performance-based comparisons were conducted to determine the optimal k-value and the most suitable clustering approach, evaluating separate versus combined clustering. Fifteen distinct neighbourhood types emerged from the analysis, spanning from high-density urban centres with extensive primary road networks to low-density suburban residential areas. These neighbourhood types exhibited distinctive environmental characteristics in the domains of thermal environment, air quality, daylight and acoustics (Kruskal-Wallis tests, p < 0.001 for all indicators). The Multidomain Neighbourhood Typology supports research on effective mitigation strategies by considering the broader multidomain environmental context to maximise co-benefits and minimise trade-offs. It also serves as a framework for context-specific implementations of mitigation measures, addressing the intrinsic multidomain environmental challenges of each neighbourhood type to enhance overall environmental quality.