Fine-scale, spatially explicit forest attribute maps are essential for guiding forest management and policy decisions. Such maps, based on the combination of National Forest Inventory (NFI) and remote sensing datasets, have a long tradition in the Nordic countries. Harmonizing the pixel size among national forest attribute maps would considerably improve the utility of the maps for users. However, national forest attribute maps are often aligned with the NFI plot size, and the influence of creating these maps at different spatial resolutions is little studied. We assess the stand-level uncertainty of biomass, volume, basal area, and Lorey’s height estimates resulting from the aggregation of maps across varying spatial resolutions. Models fit at 16 m native resolution were applied for predictions at pixels sizes (side lengths) of 1, 5, 10, 16, and 30 m. For validation, we use 65 independent stands that cover a total area of 24 ha. The stands are widely distributed over a large spatial and ecological extent in Norway. For all attributes, the lowest uncertainties, ranging from 6.86 % for Lorey’s height to 13.86 % for volume, were observed for predictions at pixel sizes of 5 m to 16 m. The uncertainty changes across resolutions were generally small (< 5 %) for biomass, volume, and basal area. For Lorey’s height, changing the spatial resolution resulted in large errors of up to 25 %. Overall, our findings suggest that the main forest attributes can be mapped at a finer scale without complex adjustments. Large-scale validation of forest attribute maps across different spatial resolutions. Koma, Z., & Breidenbach, J. (2025).