Studies of periglacial regions confirm their importance in the global carbon (C) cycle, but estimates of ecosystem C storage or green-house gas fluxes from these remote areas are generally poorly constrained and quantitative estimates of upscaling uncertainties are lacking. In this study, a regional database describing soil organic carbon (SOC) storage in periglacial terrain (European Russian Arctic) was used to evaluate spatial upscaling from point measurements using thematic maps. The selection of classes for upscaling and the need for replication in soil sampling were statistically evaluated. Upscaling using a land cover classification and a soil map estimated SOC storage to 48.5 and 47.0 kg C m−2, respectively with 95% confidence intervals (CI) within ±8%. When corrected for spatial errors in the LCC upscaling proxy, SOC was estimated to 46.5 kg C m−2 with a 95% CI reflecting propagated variance from both natural variability and spatial errors of ±11%. Artificially decreasing the size of the database used for upscaling showed that relatively stable results could be achieved with lower replication in some upscaling classes. Decreased spatial resolution for upscaling from 30 m to 1 km had little impact on SOC estimates in this region, but classification accuracy was dramatically reduced and land cover classes show different, sometimes nonlinear, responses to scale. The methods and recommendations presented here can provide guidelines for any future study where point observations of a variable are upscaled using remotely sensed thematic maps or classifications and potential applications for circum-arctic studies are discussed. For future upscaling studies at large geographic scales, a priori determination of sample sizes and tests to insure unimodal and statistically independent samples are recommended. If these prerequisites are not fulfilled, classes may be merged or subdivided prior to upscaling.