FOREST CANOPY CHEMISTRY WITH HIGH-SPECTRAL-RESOLUTION REMOTE-SENSING

Forest ecosystem modelling requires information about canopy chemistry . This is usually obtained through chemical analysis and laboratory sp ectrometric measurements. The potential of spectrometric remote sensin g was investigated with two airborne campaigns organized in 1991 with AVIRIS (Airborne Visible/Infrared Imaging spectrometer) and in 1993 wi th ISM (Infrared SpectroMeter) over the 'Landes' forest (south-west Fr ance): AVIRIS covers the 400-2500 nm spectral range with 210 bands, wh ereas the ISM instrument is an airborne profiling spectrometer that op erates in the 800-3200 nm spectral range with 128 bands. The study are a consists of homogeneous parcels of maritime pines with a wide variet y of ages from 2 to 48 years. Simultaneously with the airborne acquisi tion, foliar samples were collected in the field. These samples were c hemically analysed for determining nitrogen, lignin and cellulose cont ents. Reflectance spectra of dried pine needles were obtained with the help of two laboratory spectrometers: (1) the Technicon InfraAlyser-4 50 with 19 spectral bands centred on chemical absorption features; and (2) the NIR-6500 System with 10 nm wide 1050 bands from 400 nm to 250 0 nm. Predictive relationships of nitrogen, lignin and cellulose conce ntrations were established by using stepwise regression analysis on th e laboratory spectral measurements. These predictive relationships wer e quite different, depending on the laboratory spectrometers and the y ear of sampling. Consequently, different correlations (r(2)) were obta ined between predicted and actual chemical concentrations: 66-94 per c ent for nitrogen, 37-79 per cent for lignin and 45-85 per cent for cel lulose. The stability of predictive relationships from laboratory to r emote sensing level was especially analysed. The application of labora tory derived predictive equations to airborne data led to encouraging results: best correlations (r(2)) were obtained for nitrogen (AVIRIS: 55 per cent ISM: 66 per cent) and cellulose (AVIRIS: 63 per cent) but lignin could not be predicted. It was attempted to improve these resul ts while laking into account atmospheric effects: whereas AVIRIS-deriv ed correlations were not improved, ISM-derived correlations were impro ved for nitrogen from 66 per cent to 76 per cent and lignin from 9 per cent to 77 per cent. The better signal-to-noise ratio of ISM may be t he reasons for the better results obtained with this instrument.