Improving spatial distribution estimation of forest biomass with geostatistics: A case study for Rondą onia, Brazil
Mapping aboveground forest biomass is of fundamental importance for estimating CO2emissions due to land use and land cover changes in the Brazilian Amazon. However,existing biomass maps for this region diverge in terms of the total biomass estimatesderived, as well as in the spatial patterns of mapped biomass. In addition, no regionalor location-specific measure of reliability accompanies most of these maps. In this study,330 one-hectare plots from the RADAMBRASIL survey, acquired over and along areas adjacentto the state of Rondą onia, were used to generate a biomass map over the entire regionusing geostatistics. The RADAMBRASIL sampleswere used to generate a biomass map, alongwith a measure of reliability for each biomass estimate at each location, using kriging withexternal drift with elevation, vegetation type and soil texture considered as biomass predictorvariables. Cross-validation was performed using the sample plots to compare theperformance of kriging against a simple biomass estimation using the sample mean. Overall,biomass varied from 225 to 486Mgha.1, with a local standard deviation ranging from62 to 202Mgha.1. Large uncertainty values were obtained for regions with low samplingdensity, in particular in savanna areas. The geostatistical method adopted in this paperhas the potential to be applied over the entire Brazilian Amazon region to provide moreaccurate local estimates of biomass, which would aid carbon flux estimation, along withmeasures of their reliability, and to identify areas where more sampling efforts should beconcentrated.