Accuracy assessment of Landsat-derived continuous fields of tree cover products using airborne Lidar data in the eastern United States

Abstract

Knowing the detailed error structure of a land cover map is crucial for area estimation. Facilitated by the opening of the Landsat archive, global land cover mapping at 30-m resolution has become possible in recent years. Two global Landsat-based continuous fields of tree cover maps have been generated by Sexton et al. (2013) and Hansen et al. (2013) but the accuracy of which have not been comprehensively evaluated. Here we used canopy cover derived from airborne small-footprint Lidar data as a reference to evaluate the accuracy of these two datasets as well as the National Land Cover Database 2001 canopy cover layer (Homer et al. 2004) in two entire counties in Maryland, United States. Our results showed that all three Landsat datasets captured well the spatial variations of tree cover in the study area with an r2 ranging between 0.54 and 0.58, a mean bias error ranging between-15% and 5% tree cover, and a root mean square error ranging between 27% and 29% tree cover. When the continuous tree cover maps were converted to binary forest/nonforest maps, all three products were proved to have an overall accuracy >= 80% but with significant differences in producer's accuracy and user's accuracy. Data users are thus suggested to beware of these accuracy patterns when selecting the most appropriate dataset for their specific applications.