A growing body of research has demonstrated the complementary nature of remote sensing and ecosystem modeling in studies of terrestrial carbon
cycling. Whereas remote sensing instruments are designed to capture spatially continuous information on the reflectance properties of landscape
and vegetation, models focus on the underlying biogeochemical processes that regulate carbon transformation, often over longer temporal scales.
Remote sensing capabilities, developed over the past several decades, now provide regular, high-resolution (10-meter to 1-kilometer) mapping and
monitoring of land surface characteristics relevant to modeling, including vegetation type, biomass, stand age class, phenology, leaf area index, and
tree height. Integration of these data sets with ecosystem process models and distributed climate data provides a means for regional assessment of
carbon fluxes and analysis of the underlying processes affecting them. Applications include monitoring of carbon pools and flux in response to the
United Nations Framework Convention on Climate Change.