The capability of airborne (AVIRIS) and laboratory spectrometry was investigated for assessing the chemical composition of foliar elements of a pine forest (The Landes, SW France). Simultaneously with AVIRIS acquisition, an atmospheric profile was carried out, and the forest vegetation was sampled for chemical analyses and laboratory spectral measurements. Predictive relations between concentrations of nitrogen (r=97 per cent), lignin (r = 89 per cent) and cellulose ( = 83 per cent) and reflectances of pre-treated pine needles were determined through stepwise regression analyses. A methodology was designed to assess their extrapolation to remotely acquired spectrometric data: (1) geometric and atmospheric corrections, (2) registration within a biophysical data base (e.g. LAI, biomass), and (3) comparative statistical analysis of laboratory and airborne spectrometric information. The application of laboratory derived relationships led to relatively large correlations for nitrogen (74 per cent) and cellulose (79 per cent); poorer results were obtained for lignin (55 per cent). The use of atmospherically corrected reflectances led to slightly worse correlations: nitrogen ( 73 per cent), cellulose (78 per cent) and lignin (44 per cent). It was attempted to improve these results while taking into account the influence of the canopy structure and total quantity of chemical compounds. (1) Slightly poorer results were obtained when chemical concentrations were weighted with local biomass and LAI values. (2) Predictive equations based on laboratory measurements were applied to reflectances of pine needles that were computed through the inversion of two reflectance models. This last approach improved correlations for lignin ( 74 per cent). No improvement was observed for nitrogen ( 70 per cent) and cellulose ( 69 per cent). Finally, in order to provide suitable information to GIS based ecosystem models chemical concentrations were tentatively mapped.