Data acquired during the Mac-Europe 91 campaign over the Black Forest ( Germany) are used to study the synergy of optical imaging spectrometer data ( AVIRIS) and polarimetric microwave data ( AIRSAR) for forest resource assessment. Original and new derived bands from AIRSAR and AVIRIS data are used to predict age and biomass. The best predictors ( bands) are selected through a multivariate stepwise regression analysis of each of the datasets separately. Then the joint AIRSAR-AVIRIS dataset is analysed. This study shows how the synergistic use of AIRSAR and AVIRIS data improves significantly the predictions obtained from the individual datasets for both age and biomass over the test site. In the analysis of AVIRIS data a new approach for processing large datasets as those provided by imaging spectrometers is presented, so that maximum likelihood classification of these datasets becomes feasible.