HR: 11:50h
AN: B52B-07    [Abstracts]
TI: Spatial Estimates of GPP Using LiDAR- and Quickbird-Derived fPAR
AU: * Cook, B D
EM: brucecook@umn.edu
AF: University of Minnesota, Dept. of Forest Resources 1530 N Cleveland Ave, Saint Paul, MN 55108, United States
AU: Bolstad, P V
EM: pbolstad@umn.edu
AF: University of Minnesota, Dept. of Forest Resources 1530 N Cleveland Ave, Saint Paul, MN 55108, United States
AU: Naesset, E
EM: erik.naesset@umb.no
AF: Norwegian University of Life Sciences, INA, UMB P.O.Box 5003, Ås, NO-1432, Norway
AU: Heinsch, F A
EM: faithann@ntsg.umt.edu
AF: University of Montana, NTSG, Science Complex 437 University of Montana, Missoula, MT 59812, United States
AU: Anderson, R S
EM: ryan2.anderson@umontana.edu
AF: University of Montana, NTSG, Science Complex 437 University of Montana, Missoula, MT 59812, United States
AU: Garrigues, S
EM: Sebastien.Garrigues@gsfc.nasa.gov
AF: NASA Goddard Space Flight Center, Terrestrial Information Systems Branch Mail Code 614.5, Greenbelt, MD 20771, United States
AU: Morisette, J T
EM: jeff.morisette@nasa.gov
AF: NASA Goddard Space Flight Center, Terrestrial Information Systems Branch Mail Code 614.5, Greenbelt, MD 20771, United States
AU: Nickeson, J E
EM: Jaime.E.Nickeson@nasa.gov
AF: NASA Goddard Space Flight Center, Terrestrial Information Systems Branch Mail Code 614.5, Greenbelt, MD 20771, United States
AU: Hilton, T W
EM: hilton@meteo.psu.edu
AF: The Pennsylvania State University, Dept. of Meteorology 512 Walker Bldg, University Park, PA 16802, United States
AU: Davis, K J
EM: davis@meteo.psu.edu
AF: The Pennsylvania State University, Dept. of Meteorology 512 Walker Bldg, University Park, PA 16802, United States
AU: Roman, M O
EM: romanm@ieee.org
AF: Boston University, Dept of Geography/Center for Remote Sensing 675 Commonwealth Ave, Room:CAS 436, Boston, MA 02215, United States
AB: Regional- to global-scale gross primary production (GPP) is commonly estimated with light-use efficiency models, which are largely dependent on remotely sensed estimates of the fraction of photosynthetically active radiation absorbed by vegetation (fPAR). Methodologies to quantify spatial variability of fPAR and improve GPP estimates have not been established for mixed forests and heterogeneous landscapes in the Great Lakes Region, and are needed to estimate photosynthetic sinks for the Mid-Continent Regional Intensive Campaign. In this study, hemispheric photos were collected during the 2006 growing season to estimate fPAR, plant area index (PAI), leaf inclination angle, and clumping factors in >130 lowland and upland stands within the footprint of a 400 m eddy covariance flux tower near Park Falls, Wisconsin, USA. Airborne LiDAR and Quickbird imagery were acquired during leaf-on and leaf-off periods to make predictions of canopy structure, and resulting PAI/fPAR estimates were compared with litterfall measurements and products derived from the Moderate Resolution Spectroradiometer (MODIS). GPP was modeled with the MODIS MOD17A2 algorithm, using fine-resolution land cover and fPAR inputs that were spatially aggregated into units ranging from 30 m to 1 km square. Uncertainties and errors associated with fPAR methods and spatial resolutions are discussed based on agreement with flux tower observations.
DE: 0414 Biogeochemical cycles, processes, and modeling (0412, 0793, 1615, 4805, 4912)
DE: 0428 Carbon cycling (4806)
DE: 0439 Ecosystems, structure and dynamics (4815)
DE: 0480 Remote sensing
SC: Biogeosciences [B]
MN: 2007 Fall Meeting