Within sea-ice covered oceans, leads are a major site of energy fluxes and brine releases at the air–ocean interface. Leads develop as elongated cracks of open water in the ice cover in response to sea-ice deformation. Being subject to severe cooling by the atmosphere, these regions refreeze, forming areas of thin ice. The distribution of leads and their orientation are the results of the mechanical properties of sea ice, wind stress and boundary conditions. A method to map leads in sea ice using passive microwave imagery is developed. Thin ice exhibits a characteristic ratio between the channels 89 GHz (V) and 19 Ghz (V) in passive microwave imagery, giving the possibility of distinguishing thin ice, such as pancake ice and nilas, from other ice types. Nilas develops on a calm freezing sea surface as in coastal polynyas and in open leads. A thin-ice concentration is defined analogous to total sea-ice concentration as the area fraction that consists of nilas and pancake ice. Thin-ice concentration maps are generated for the period 2002–2009 on a daily basis except from the three summer months, where the assumption of refreezing openings does not hold. The method to compute thin-ice concentrations including leads is validated using optical satellite images. The algorithm detects leads that are broader than 3 km as well as other thin-ice regions as polynyas and pancake ice. Lead patterns are investigated with respect to sea-ice deformation. Ice deformation parameters are derived from ice-drift products supplied by the Ocean and Sea Ice Satellite Application Facility (OSI SAF) and from a product of the Center for Satellite Exploitation and Research (CERSAT). The ice drift is estimated by finding the maximum cross correlations of subsequent microwave image pairs. The available data frequently show formation of leads after mesoscale divergent ice motion. The distribution of leads and their orientation indicate prevailing tensions in the ice. The new lead detection enables an investigation of sea-ice deformation features on a large scale as the data used cover the entire Arctic.