Detailed calculations of ground-ice volumes in permafrost deposits are necessary to understand and quantify the response of permafrost landscapes to thermal disturbance and thawing. Ice wedges with their polygonal surface expression are a widespread ground-ice component of permafrost lowlands. Therefore, the wedge-ice volume (WIV) is one of the major factors to be considered, both for assessing permafrost vulnerability and for quantifying deep permafrost soil carbon inventories. Here, a straightforward tool for calculating the WIV is presented. This GIS and satellite image-based method provides an interesting approach for various research disciplines where WIV is an important input parameter, including landscape and ecosystem modeling of permafrost thaw or organic carbon assessments in deep permafrost deposits. By using basic data on subsurface ice-wedge geometry, our tool can be applied to other permafrost region where polygonal-patterned ground occurs. One is able to include individual polygon geomorphometry at a specific site and the shape and size of epigenetic and/or syngenetic ice wedges in three dimensions. Exemplarily, the WIV in late Pleistocene Yedoma deposits and Holocene thermokarst deposits is calculated at four case study areas in Siberia and Alaska. Therefore, we mapped ice-wedge polygons and thermokarst mounds (baydzherakhs) patters on different landscape units by using very-high-resolution satellite data. Thiessen polygons were automatically created in a geographic information system (GIS) environment to reconstruct relict ice-wedge polygonal networks from baydzherakh center-point patterns. This information was combined with literature or own field data of individual ice-wedge sizes, to generate three-dimensional subsurface models that distinguish between epi- and syngenetic ice-wedge geometry. We demonstrate that the WIV can vary considerably, not only between different permafrost regions, but also within a certain study site.Detailed information about methods and results can be found in the publication to which this dataset is a supplement (https://doi.org/10.1002/ppp.1810).