To ensure viable species populations in fragmented landscapes, individuals must be able to move between suitable habitat patches. Despite the increased interest in biodiversity assessment in urban environments, the ecological relevance of habitat connectivity in highly fragmented landscapes remains largely unknown. The first step to understanding the role of habitat connectivity in urban ecology is the challenging task of assessing connectivity in the complex patchwork of contrasting habitats that is found in cities. We developed a data-based framework, minimizing the use of subjective assumptions, to assess habitat connectivity that consists of the following sequential steps: (1) identification of habitat preference based on empirical habitat-use data; (2) derivation of habitat resistance surfaces evaluating various transformation functions; (3) modeling of different connectivity maps with electrical circuit theory (Circuitscape), a method considering all possible pathways across the landscape simultaneously; and (4) identification of the best connectivity map with information-theoretic model selection. We applied this analytical framework to assess habitat connectivity for the European hedgehog Erinaceus europaeus, a model species for ground-dwelling animals, in the city of Zurich, Switzerland, using GPS track points from 40 individuals. The best model revealed spatially explicit connectivity “pinch points,” as well as multiple habitat connections. Cross-validation indicated the general validity of the selected connectivity model. The results show that both habitat connectivity and habitat quality affect the movement of urban hedgehogs (relative importance of the two variables was 19.2% and 80.8%, respectively), and are thus both relevant for predicting urban animal movements. Our study demonstrates that even in the complex habitat patchwork of cities, habitat connectivity plays a major role for ground-dwelling animal movement. Data-based habitat connectivity maps can thus serve as an important tool for city planners to identify habitat corridors and plan appropriate management and conservation measures for urban animals. The analytical framework we describe to model such connectivity maps is generally applicable to different types of habitat-use data and can be adapted to the movement scale of the focal species. It also allows evaluation of the impact of future landscape changes or management scenarios on habitat connectivity in urban landscapes.