Estimating the stem carbon production of a coniferous forest using an ecosystem simulation model driven by the remotely sensed red edge

A general forest ecosystem model(FOREST-BGC) driven by remotely sensed and meteorological data was used to estimate stem carbon production (SCP) for a forest in mid-Wales. Key inputs to the model were spatial estimates of lea f area index (LAI) and leaf nitrogen concentration (LNC). The red edge posi tion (REP) was determined for data acquired by the Compact Airborne Spectro graphic Imager (CASI) sensor. There was a strong linear correlation (r=0.94 ) between LAI and the REP and the relationship was used to obtain spatial e stimates of LAI. There was no relationship between LNC and the REP and so s patial estimates of LNC were derived indirectly from LAI. Estimates of SCP generated from FOREST-BGC compared favourably with estimates derived from t ree cores (RMSE = +/- 0.34 Mg C ha(-1) yr(-1)).