Ecosystem process models have become important tools for
scaling NPP and NEP over landscape to regional domains.
Their power is largely derived from their ability to distill a wide
array of diverse data into useful information and to force consistency
among numerous discrete observational data sets.
Satellite remote sensing is providing an increasing variety of
spatial data layers that are potentially usable as model input
or for validation of model output. The integration of process
models and remote sensing is particularly effective for monitoring
at landscape to regional scales, because at fine spatial
and temporal resolutions it can resolve the major near-term
controls on carbon fluxes, including land use, foliar biophysical
characteristics, topography, and climatic gradients.
Research challenges in this field include optimizing spatial and
temporal resolution for specific applications, differentiating
the relative influences of structural and chemical variables on
ecosystem carbon fluxes, and systematically validating modelbased
flux estimates.