PARENT SESSION
Oral Session # 85: GIS and Remote Sensing II; Ecological Modeling III.
Presiding: Y Lin
Thursday, August 7. 1:30 PM to 5:00 PM, SITCC Meeting Room 203.
Lidar detected canopy structure for improved model estimates of carbon stocks and fluxes.
Drake, Jason*,1, Hurtt, George2, Dubayah, Ralph3, Fearon, Matthew2, Moorcroft, Paul4, 1 D.B. Warnell School of Forest Resources, Athens, GA2 Department of Natural Resources, Durham, NH3 Department of Geography, College Park, MD4 Department of Organismic and Evolutionary Biology, Cambridge, MA
ABSTRACT- Carbon estimates from terrestrial ecosystem models are currently limited by large uncertainties in the current condition of the land surface. In this study we combine recent developments in remote sensing and ecological modeling in an attempt to improve carbon stock and flux estimates. We used airborne lidar remote sensing, to measure fine-scale heterogeneity in the vertical structure of vegetation. This vertical structure is then used to initialize a new height-structured terrestrial ecosystem model (the Ecosystem Demography model, ED), which is capable of calculating the consequences of fine-scale heterogeneity in vegetation structure in broad-scale analyses of carbon stocks and fluxes. We initially used a simple lidar statistic, mean canopy height within each 1 hectare grid cell, to initialize the ED model. This combined approach produced reliable model estimates of above-ground biomass and provided substantial constraints on model estimates of above-ground carbon fluxes at several study sites in tropical and temperate forests. At our tropical forest study site (La Selva Biological Station) we then evaluated the utility of other lidar statistics (e.g., standard deviation of canopy heights within each grid cell) and lidar waveforms (profiles of lidar energy reflected from the top of the canopy to the ground). We found that these metrics resulted in improvements in model estimates of above-ground biomass (compared to canopy height alone) and further constrained model estimates of above-ground carbon fluxes. The continued development and combination of these two technologies is shown to be a promising approach for improving broad-scale carbon stock and flux estimates.
Key words: carbon, tropical forest, lidar, forest structure