HR: 0800h
AN: B51C-0213    [Abstracts]
TI: Estimation and Validation of Regional Biomass Using Vegetation Structure Measurements from ICESAT and Forest Inventory Analysis Data
AU: * Dubayah, R
EM: dubayah@umd.edu
AF: University of Maryland, Geography Department, College Park, MD 20742 United States
AU: Hurtt, G
EM: george.hurtt@unh.edu
AF: University of New Hampshire, Institute for the Study of Earth, Oceans and Space, Durham, NH 03824 United States
AU: Moorcroft, P
EM: paul_moorcroft@harvard.edu
AF: Harvard University, Department of Organismic & Evolutionary Biology, Cambridge, MA 02138
AU: Hofton, M
EM: mhofton@umd.edu
AF: University of Maryland, Geography Department, College Park, MD 20742 United States
AU: Blair, J B
EM: James.B.Blair
AF: NASA Goddard Spaceflight Center, Laser Remote Sensing Branch, Greenbelt, MD 20742 United States
AU: Sheldon, S
EM: sagels@umd.edu
AF: University of Maryland, Geography Department, College Park, MD 20742 United States
AB: The ICESAT mission has acquired lidar measurements of land surface vertical structure for several years. Although these have severely limited spatio-temporal resolutions and coverages, they nonetheless are the only consistent, global data of this kind. Our earlier work has linked airborne lidar measurements with a height-structured ecosystem model, the Ecosystem Demography (ED) model for modeling local (10's of kilometers) carbon stocks and fluxes at 1 hectare grid resolution. In this research we explore extending these modeling efforts to link space-based lidar observations of vegetation structure with ED to produce estimates of biomass at regional scales. Sparse ICESAT data are first combined with airborne lidar and MODIS-derived landcover information to provide contextual information for each observation, and to provide appropriate estimates of vegetation structure at 1° resolution. Next, to assess their relationship with known biophysical attributes, we perform exploratory analyses linking various ICESAT lidar waveform metrics with biomass, age and other vegetation data obtained from the U.S. Forest Inventory Analysis (FIA) for 1° grid cells. Lastly, we explore methods for initialization of the ED model using ICESAT data to produce regional estimates of biomass for the eastern half of the US, which are then compared with gridded FIA estimates of biomass.
DE: 0414 Biogeochemical cycles, processes, and modeling (0412, 0793, 1615, 4805, 4912)
DE: 0480 Remote sensing
SC: Biogeosciences [B]
MN: Fall Meeting 2005