Quantifying scaling effects on satellite-derived forest area estimates for the conterminous USA

We quantified the scaling effects on forest area estimates for the conterminous USA using regression analysis and the National Land Cover Dataset 30 m satellite-derived maps in 2001 and 1992. The original data were aggregated to: (1) broad cover types (forest vs. non-forest); and (2) coarser resolutions (1 km and 10 km). Standard errors of the model estimates were 2.3% and 4.9% at 1 km and 10 km resolutions, respectively. Our model improved the accuracies for 1 km by 0.6% (12 556 km2) in 2001 and 1.9% (43 198 km2) in 1992, compared to the forest estimates before the adjustments. Forest area observed from Moderate Resolution Imaging Spectroradiometer (MODIS) 2001 1 km land-cover map for the conterminous USA might differ by 80 811 km2 from what would be observed if MODIS was available at 30 m. Of this difference, 58% (46 870 km2) could be a relatively small net improvement, equivalent to 1444 Tg (or 1.5%) of total non-soil forest CO2 stocks. With increasing attention to accurate monitoring and evaluation of forest area changes for different regions of the globe, our results could facilitate the removal of bias from large-scale estimates based on remote sensors with coarse resolutions.