This study investigated the mechanisms underlying the scaling effects that apply to a fraction of vegetation cover (FVC) estimates derived using two-band spectral vegetation index (VI) isoline-based linear mixture models (VI isoline-based LMM). The VIs included the normalized difference vegetation index, a soil-adjusted vegetation index, and a two-band enhanced vegetation index (EVI2). This study focused in part on the monotonicity of an area-averaged FVC estimate as a function of spatial resolution. The proof of monotonicity yielded measures of the intrinsic area-averaged FVC uncertainties due to scaling effects. The derived results demonstrate that a factor , which was defined as a function of “true” and “estimated” endmember spectra of the vegetated and nonvegetated surfaces, was responsible for conveying monotonicity or nonmonotonicity. The monotonic FVC values displayed a uniform increasing or decreasing trend that was independent of the choice of the two-band VI. Conditions under which scaling effects were eliminated from the FVC were identified. Numerical simulations verifying the monotonicity and the practical utility of the scaling theory were evaluated using numerical experiments applied to Landsat7-Enhanced Thematic Mapper Plus (ETM+) data. The findings contribute to developing scale-invariant FVC estimation algorithms for multisensor and data continuity.