HR: 0800h
AN: B31B-0212    [Abstracts]
TI: MODIS LAI and FPAR: Product Analysis
AU: * Huang, D
EM: dh@crsa.bu.edu
AF: Boston University, Geography Department, 675 Commenwealth Ave, Boston, MA 02215 United States
AU: Shabanov, N
EM: shabanov@crsa.bu.edu
AF: Boston University, Geography Department, 675 Commenwealth Ave, Boston, MA 02215 United States
AU: Yang, W
EM: ywze@crsa.bu.edu
AF: Boston University, Geography Department, 675 Commenwealth Ave, Boston, MA 02215 United States
AU: Tan, B
EM: tanbin@crsa.bu.edu
AF: Boston University, Geography Department, 675 Commenwealth Ave, Boston, MA 02215 United States
AU: Knyazikhin, Y
EM: jknjazi@crsa.bu.edu
AF: Boston University, Geography Department, 675 Commenwealth Ave, Boston, MA 02215 United States
AU: Myneni, R
EM: rmyneni@crsa.bu.edu
AF: Boston University, Geography Department, 675 Commenwealth Ave, Boston, MA 02215 United States
AB: Leaf Area Index (LAI) and Fraction of Photosynthetically Active Radiation [400-700 nm] absorbed by vegetation (FPAR) are key environmental variables used in climate research to characterize exchange of fluxes of energy, mass and momentum in Earth system. MODerate resolution Imaging Spectroradiometer (MODIS) provide set of global remote sensing measurements to generate 16 land geophysical products including LAI and FPAR. Current MODIS LAI and FPAR research integrates three major components: LAI and FPAR algorithm development, product analysis and product validation. Product analysis is the central activity, which is closely interconnected with algorithm development and validation. The objective of this presentation is to illustrate this interconnection, targeted for continuous product refinement from Collection 3 through current Collection 4 and into future Collection 5 of the LAI and FPAR products. Product analysis is presented at global scale, regional scale (MODIS tile) and local scale (validation). At global scale we routinely analyzed spatial coverage of the main algorithm, studied seasonality of LAI and FPAR products, and analyzed impact of snow and cloud conditions on product retrievals. MODIS tile scale is convenient for detailed study of product retrievals as function of the algorithm and its input uncertainties and provide direct feedback to algorithm refinement. Finally we summarized reported in peer-reviewed literature results of the validation activities, performed by LAI/FPAR team as well as external validators.
DE: 1640 Remote sensing
SC: Biogeosciences [B]
MN: 2004 AGU Fall Meeting