AN ASSESSMENT OF CANOPY CHEMISTRY WITH AVIRIS - A CASE-STUDY IN THE LANDES FOREST, SOUTH-WEST FRANCE

Citation
Jp. Gastelluetchegorry et al., AN ASSESSMENT OF CANOPY CHEMISTRY WITH AVIRIS - A CASE-STUDY IN THE LANDES FOREST, SOUTH-WEST FRANCE, International journal of remote sensing, 16(3), 1995, pp. 487-501
Citations number
29
Categorie Soggetti
Photographic Tecnology","Remote Sensing
ISSN journal
01431161
Volume
16
Issue
3
Year of publication
1995
Pages
487 - 501
Database
ISI
SICI code
0143-1161(1995)16:3<487:AAOCCW>2.0.ZU;2-F
Abstract
The capability of airborne (AVIRIS) and laboratory spectrometry was in vestigated for assessing the chemical composition of foliar elements o f a pine forest (The Landes, SW France). Simultaneously with AVIRIS ac quisition, an atmospheric profile was carried out, and the forest vege tation was sampled for chemical analyses and laboratory spectral measu rements. Predictive relations between concentrations of nitrogen (r = 97 per cent), lignin (r = 89 per cent) and cellulose (r = 83 per cent) and reflectances of pre-treated pine needles were determined through stepwise regression analyses. A methodology was designed to assess the ir extrapolation to remotely acquired spectrometric data: (1) geometri c and atmospheric corrections, (2) registration within a biophysical d ata 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 correlati ons for nitrogen (74 per cent) and cellulose (79 per cent); poorer res ults were obtained for lignin (55 per cent). The use of atmosphericall y corrected reflectances led to slightly worse correlations: nitrogen (73 per cent), cellulose (78 per cent) and lignin (44 per cent). It wa s attempted to improve these results while taking into account the inf luence of the canopy structure and total quantity of chemical compound s. (1) Slightly poorer results were obtained when chemical concentrati ons were weighted with local biomass and LAI values. (2) Predictive eq uations based on laboratory measurements were applied to reflectances of pine needles that were computed through the inversion of two reflec tance 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 informa tion to GIS based ecosystem models chemical concentrations were tentat ively mapped.