Identifying grain-size dependent errors on global forest area estimates and carbon studies

Satellite‐derived coarse‐resolution data are typically used for conducting global analyses. But the forest areas estimated from coarse‐resolution maps (e.g., 1 km) inevitably differ from a corresponding fine‐resolution map (such as a 30‐m map) that would be closer to ground truth. A better understanding of changes in grain size on area estimation will improve our ability to quantify bias and uncertainty, and provide more accurate estimates of forest area and associated carbon stocks and fluxes. We simulated that global forest area estimated from a 1‐km land‐cover map (the most practical and finest resolution currently used for global applications) was 947,573 km2 less than that of its corresponding 30‐m map (excluding Antarctic and Greenland). This amount of forest could produce 0.57 ± 0.01 petagrams of carbon per year (PgC/yr) as NPP or 0.11 ± 0.002 PgC/yr as NEP equivalent to 4% of the 2.9 PgC/yr missing carbon sink in the 1990s. The most significant underestimation of forest area was in the temperate zone (the more uncertain region regarding the “missing carbon sink”) while a relatively small overestimation occurred in the tropic zone as the grain size of satellite‐derived land‐cover maps increases from 30 m to 1 km.