HR: 1340h
AN: B43B-0282    [Abstracts]
TI: Analysis of Prototype Collection 5 Products of Leaf Area Index from Terra and Aqua MODIS Sensors
AU: * Shabanov, N V
EM: shabanov@bu.edu
AF: Boston University, Geography Department, 675 Commonwealth Ave., #334G, Boston, MA 02215 United States
AU: Yang, W
EM: ywze@crsa.bu.edu
AF: Boston University, Geography Department, 675 Commonwealth Ave., #334G, Boston, MA 02215 United States
AU: Dong, H
EM: dh@crsa.bu.edu
AF: Boston University, Geography Department, 675 Commonwealth Ave., #334G, Boston, MA 02215 United States
AU: Knyazikhin, Y
EM: jknjazi@crsa.bu.edu
AF: Boston University, Geography Department, 675 Commonwealth Ave., #334G, Boston, MA 02215 United States
AU: Myneni, R
EM: rmyneni@crsa.bu.edu
AF: Boston University, Geography Department, 675 Commonwealth Ave., #334G, Boston, MA 02215 United States
AB: A prototype product suite, containing the Terra 8-day, Aqua 8-day, Terra and Aqua combined 8- and 4-day products, was generated as part of testing for the next version of MODIS LAI products - the Collection 5. These products were analyzed for consistency between Terra and Aqua retrievals. The potential for combining retrievals from the two sensors to derive improved products by reducing the impact of environmental conditions and temporal compositing period was also explored. The results suggest no significant discrepancies between large area averages of Terra and Aqua 8-day surface reflectances and LAI products. The differences over smaller regions, however, can be large due to the random nature of residual atmospheric effects. Best quality radiative transfer based retrievals can be expected in 90-95% of the pixels with mostly herbaceous cover and about 50-75% of the pixels with woody vegetation during the growing season. Rate of the best quality retrievals during the growing season is mostly restricted by aerosol contamination of the MODIS data. The combined 8-day product helps to minimize this effect and increases the amount of the best quality retrievals by 10-20% over woody vegetation. The combined 8-day product did not result in more main algorithm retrievals during the winter period because the extent of snow contamination of Terra and Aqua observations is similar. Likewise, the number of cloudy pixels in single-sensor and combined products is also similar. The combined 4-day product provides advantages for fine time step phenology monitoring, especially during transition periods of spring and fall. Implementation of the fine time step does not reduce accuracy of retrievals: the LAI magnitudes, seasonal profiles and the amount of best quality retrieval were found to be comparable between the combined 4-day and the single-sensor 8-day products. Finally, it was found that both Terra and Aqua surface reflectances over the northern high latitudes needle leaf forests demonstrate inverse seasonal trends compared to radiative transfer simulation of the MODIS LAI algorithm. This leads to anomalous LAI seasonality in the retrievals and needs to be investigated further referencing corresponding field measurements through seasonal cycle. Overall, the obtained results indicate that further improvement of the MODIS LAI products is mainly restricted not by the amount, but the precision of the MODIS observations.
DE: 0414 Biogeochemical cycles, processes, and modeling (0412, 0793, 1615, 4805, 4912)
DE: 0416 Biogeophysics
DE: 0430 Computational methods and data processing
DE: 0434 Data sets
DE: 0480 Remote sensing
SC: Biogeosciences [B]
MN: Fall Meeting 2005