Coupling Remotely Sensed Data to an Ecosystem Simulation Model-an Example Involving a Coniferous Plantation in Upland Wales

A major goal for environmental scientists is to gain an improved understanding of the state and dynamics of the Earth's forested regions and their interactions with biogeochemical cycles at regional to global scales. Consequently, there is a need for the acquisition of accurate, quantitative estimates of biophysical and biochemical properties of forest ecosystems. Over regional to global scales remote sensing provides the only practical means of collecting such data. These data can be used to drive environmental ecosystem simulation models which attempt to predict ecosystem properties of interest (e.g. carbon storage, photosynthesis) that are not measurable directly by remote sensing techniques. Estimates of forest biophysical and biochemical properties within the Tywi forest plantation, central Wales, are derived from polarimetric synthetic aperture radar data and fine spectral resolution optical/infrared remotely sensed data. These are used to drive the Forest BGC (BioGeochemical Cycles) environmental simulation model. The preliminary results from a three-stage analysis are presented. These include (i) the comparison of stem carbon production estimates from model simulations with data acquired in the field, and (ii) the relationships between stem biomass and leaf area index, and remotely sensed data.