Lakes and drained lake basins (DLBs) are dominant landforms across Arctic lowland regions. The long-term dynamics of lake formation and drainage is evident in the abundance of lakes and DLBs covering as much as 80% of the landscape in various regions of Arctic Alaska, Russia, and Canada. Lake drainage can be triggered through different mechanisms such as lake tapping by an adjacent stream, bank overflow or ice wedge degradation. Following drainage, DLBs can become valuable grazing land for caribou and reindeer as well as usable land for infrastructure development due to low ground ice content in recent DLBs. In addition, DLBs can be sites for soil organic carbon accumulation in the form of peat which also play a role for carbon cycling. Comprehensive and accurate mapping of DLB distribution, age and drainage mechanism, will further inform our understanding of their role in permafrost landscape evolution across varying timescales. DLBs differ from the surrounding terrain in vegetation structure and composition, soil moisture, elevation, size and types of ice-wedge polygons and other parameters that make them an identifiable target based on remote sensing data. Here, we present a novel approach to map DLBs in permafrost landscapes with a specific focus on the North Slope of Alaska as well as select areas in Siberia and northwestern Canada. To map DLBs, we combined multispectral satellite imagery (Landsat-8 and Sentinel-2), Synthetic Aperture Radar (SAR) acquisitions (Sentinel-1), and DEM data (ArcticDEM). To cover the entire study area in each region, we included Landsat-8 acquisitions from all available years and Sentinel-2 for 2016 and 2018 to create cloud-free mosaics. The classification combines methodologies from pixel-based and object-based image analysis. To allow for processing of these large datasets that cover more than 200.000 km2, a classification workflow was developed in Google Earth Engine. Preliminary results show good agreement of our classification with previously published data sets for subsets of our North Slope study area. This work marks the first attempt to map DLBs at the pan-Arctic scale. Our results highlight the importance of treating areas of different surficial geology and vegetation communities separately in the classification process to ensure higher classification accuracy.