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Large scale ecosystem modeling using parameters derived from imaging spectrometer data

The capability to predict the response of ecosystems to change relies on our ability to understand and model the effective functioning of biotic processes at large scales and the transport functions of the atmospheric/hydrospheric processes. To successfully evaluate changes in ecological processes at the required spatial and temporal scales remote sensing technology and ecosystem theory must be considered jointly. A review of developments in remote sensing analysis using high spectral resolution sensors has led to the selection of a potential set ofparameters to be used in ecosystem models. These parameters quantify the light interception properties that scale from leaf to landscape. Spectral mixture analysis forms a framework for the systematic separation of both vegetative and non-vegetative components at sub-pixel spatial resolution. The spectral concentrations of the vegetative components defined by the spectral mixture analysis are then used to drive canopy radiative transfer models from which the ecosystem parameters are inferred. 1.