The deformation of sea ice is an important component of sea ice dynamics and the interaction between atmosphere, ice, ocean, and land. An inhomogeneous drift of sea ice creates opening or closing of leads, and results in the formation of pressure ridges and local changes of the ice thickness. The motion of sea ice can be observed from space by synthetic aperture radar (SAR) and quantified by drift-detection algorithms. A general problem of quantifying deformation or strain rates is that the magnitudes are dependent on the spatial and temporal scales. Previous analyses, primarily on RGPS-data, have revealed the strong heterogeneous and intermittent character of sea ice deformation. By analyzing the distribution of strain rates a scaling effect, both temporally and spatially, could be demonstrated (Hutchings et al. 2011; Marsan et al. 2004; Rampal et al. 2008; Stern and Lindsay 2009). Thus, the distribution of strain rates at some (arbitrary) scale is not sufficient to characterize sea ice deformation (Weiss 2013). The objective of our study is to extent the analysis of strain fields towards smaller spatial scales, which are not included in previous studies. By using sequential SAR images and a pattern-matching approach for the retrieval of the drift field it is possible to downsize the spatial scale from several kilometers to a few 100 meters. To identify the effect of spatial scaling we perform a statistical analysis of strain rates. We calculate the statistical moments of the strain rate distribution for different spatial scales and describe their dependence on spatial resolution using a power law. The results obtained hitherto reveal the scale-dependence of strain rates. The found relations are consistent with similar analyses on larger scale ranges. In addition and for the first time for sea ice we perform the analysis independently for shear strain and divergence. Again, scaling behavior is observed, but differently pronounced. Our result strengthened the assumption that scaling properties extend down to very fine scales and thus an extrapolation to laboratory scales (~1m) may be feasible. If scaling behavior of strain rates is known, the comparability of sea ice deformation derived from different methods at different spatial scales, e.g. modelling , buoys or SAR-data, is significantly improved. In addition, conclusions about the mechanical properties of the sea ice can be made. After the statistic analysis is performed we link the manifestation (magnitude or spatial extent of deformation) and nature of the scaling effect (mono- or multifractal) with the existing sea ice classes/conditions. The ice classes/conditions are derived directly from the SAR images and are compared with the prevailing scaling behavior. Thus, scaling effects can be treated separately for certain sea ice classes/conditions and not only as functions of regional and seasonal conditions.