Housing type mix as a lever for sustainable urban mobility

Land use-transport interactions are well documented in literature using urban form metrics including density, land–use mix, and destination accessibility, but rarely housing type shares. This study demonstrates the overlooked explanatory and causal relevance of housing typology, specifically the single–family housing share, for four mobility outcomes: car travel, transit travel, car ownership, and CO 2 emissions. Using postcode–level data for 13 cities in Germany and France, we compare the role of urban form metrics across linear regression, gradient–boosted decision trees, artificial neural networks, causal discovery, and double machine learning methods. Single–family share consistently outperforms conventional urban form indicators in explaining each outcome. Given its strong predictive power, causal relevance, and ease of measurement, housing typology offers substantial potential for modelling land use-transport interactions and provides a promising cross–sectoral focus for climate and mobility policy.