title: Local discrepancies in continental scale biomass maps: a case study over forested and non-forested landscapes in Maryland, USA.
abstract: BACKGROUND
  Continental-scale aboveground biomass maps are increasingly available, but their estimates vary widely, particularly at high resolution. A comprehensive understanding of map discrepancies is required to improve their effectiveness in carbon accounting and local decision-making. To this end, we compare four continental-scale maps with a recent high-resolution lidar-derived biomass map over Maryland, USA. We conduct detailed comparisons at pixel-, county-, and state-level.
  
  
  RESULTS
  Spatial patterns of biomass are broadly consistent in all maps, but there are large differences at fine scales (RMSD 48.5-92.7 Mg ha-1). Discrepancies reduce with aggregation and the agreement among products improves at the county level. However, continental scale maps exhibit residual negative biases in mean (33.0-54.6 Mg ha-1) and total biomass (3.5-5.8 Tg) when compared to the high-resolution lidar biomass map. Three of the four continental scale maps reach near-perfect agreement at ~4 km and onward but do not converge with the high-resolution biomass map even at county scale. At the State level, these maps underestimate biomass by 30-80 Tg in forested and 40-50 Tg in non-forested areas.
  
  
  CONCLUSIONS
  Local discrepancies in continental scale biomass maps are caused by factors including data inputs, modeling approaches, forest/non-forest definitions and time lags. There is a net underestimation over high biomass forests and non-forested areas that could impact carbon accounting at all levels. Local, high-resolution lidar-derived biomass maps provide a valuable bottom-up reference to improve the analysis and interpretation of large-scale maps produced in carbon monitoring systems.
authors: Department of Geographical Sciences, University of Maryland, College Park, USA.
authors: Wenli
authors: 0000-0001-9608-1690
authors: W
authors: Huang
authors: Department of Geographical Sciences, University of Maryland, College Park, USA.
authors: Anu
authors: A
authors: Swatantran
authors: USDA Forest Service, Northern Research Station, Newtown Square, PA USA.
authors: Kristofer
authors: K
authors: Johnson
authors: Department of Geographical Sciences, University of Maryland, College Park, USA.
authors: Laura
authors: L
authors: Duncanson
authors: Department of Geographical Sciences, University of Maryland, College Park, USA.
authors: Hao
authors: H
authors: Tang
authors: Rubenstein School of the Environment and Natural Resources, University of Vermont, Burlington, USA.
authors: Jarlath
authors: J
authors: O'Neil Dunne
authors: Department of Geographical Sciences, University of Maryland, College Park, USA.
authors: George
authors: G
authors: Hurtt
authors: Department of Geographical Sciences, University of Maryland, College Park, USA.
authors: Ralph
authors: R
authors: Dubayah
keywords: Aboveground biomass; Carbon; Lidar; Temperate deciduous forest