Decision makers, planners and actors in cities design policies, plan, invest money and build infrastructure, and consumers buy houses and use transport infrastructure without sound information about the environmental consequences of many of those decisions. Decisions, however, that have a lasting impact on sustainable development outcomes. In this study, we employ novel analytical techniques to align the spatial characteristics of the built urban environment with information for building materials and GHG embodiment to inform planning and investment decisions at the district, suburb and city scale. We represent a three-dimensional model of a suburb established from remotely sensed data and use algorithms to identify building types and align those with their typical material composition. We analyse the urban development of the modelled suburb in three historical time steps – 1955, 1981 and 2015 – and establish the consequence of urban planning decisions on material use and GHG embodiment. We test the new methodology for its applicability for a whole of city analysis and discuss the benefit for environmentally sustainable urban planning and design.