1. The Role of Models in Remotely Sensed Primary Production Estimates
Maosheng Zhao
NTSG, College of Forestry & Conservation
University of Montana
Global Vegetattion Workshop 2009
University of Montana, MT. Jun , 2009

2. Are Vegetation Indices (VIs) Everything?
NDVI is strongly related to NPP (Goward et al., 1985)
EVI is strongly related to GPP estimated at eddy fluxes towers (Huete et al, 2006; Rahman et al, 2005; Xiao et al. 2004; Others).
VIs are “observed” by satellite, which are more reliable if appropriate optical and atmospheric corrections employed. Models using remote sensing data will be less reliable?

3. VIs Cannot Reveal “Hidden” Variables
VIs “Observed” by Satellites
Green Biomass (LAI, FPAR)
Photosynthesis
Absorbed Light
Stomata Conductance
(light, temperature, water)

4. Light Use Efficiency Models
GPP = PAR * FPAR * LUEmax * Stomata_Cond_CTR(Tmin, Water)
NPP = GPP – Plant_Respiration

5. Higher EVI but lower NPP (based on the Collection4 MODIS data)
(Drought in Amazon, 2005)
The circled annual GPP are from Duck forest, and the problem is from the low maximum LUE the algorithm used for the site. The low correlation for Mixed Forest with annual GPP ranging from about 700 to 1500 is due to the saturation problem of MODIS FPAR.
Saleska et al., 2007 Science
(based on the Collection4 MODIS data)
Phillips et al., 2009 Science

6. Severe Drought in Amazon, 2005
FPAR
EVI
Collection 5
GPP
NPP
Collection 5.1

7. Global Scale Sensitivity Test
Correlations (inverted CO2 annual growth rate and NPP):
Control Run:
Fix FPAR/LAI (var. mete.):
Fix mete (var. FPAR/LAI): 0.34

8. Models Are Required
(Zhao & Running, 2008)