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This paper studies whether the standard deviation (std) of the Baltic Sea ice backscattering coefficient (σ°) depends on the length of measurement (l). For many kinds of surfaces, especially for a fractal one, this is the case. The study was conducted using one-dimensional C-band helicopter-borne scatterometer data and ENVISAT synthetic aperture radar (SAR) images. The results with both data sets indicate mostly a strong linear dependence between ln(l) and ln(std(σ°)) up to a distance of at least a few kilometers. Based on the analysis of empirical and simulated data (fractal and nonfractal profiles), it seems that sea ice σ° as a function of l is not completely described either by fractional Brownian motion or by a process with a single-scale autocorrelation function. Neither can the values of σ° be regarded as samples from only one probability distribution. The regression coefficients describing the dependency of ln(I) versus ln(std(σ°)) do not discriminate various ice types better than just mean and std of σ°. However, the use of regression coefficients instead of mean and std is preferred due to their scale-invariant comparability with the results of other studies. The dependence of std(σ°) on l should also be taken generally into account in the data analysis, e.g., when constructing classifiers for sea ice SAR data. [ABSTRACT FROM AUTHOR]