COMPARISON OF SEVERAL OPTIMIZATION METHODS TO EXTRACT CANOPY BIOPHYSICAL PARAMETERS APPLICATION TO CAESAR DATA

291 COMPARISON OF SEVERAL OPTIMIZATION METHODS TO EXTRACT CANOPY BIOPHYSICAL PARAMETERS - APPLICATION TO CAESAR DATA S. JACQUEMOUD1*, S. FLASSE2, J. VERDEBOUT1, G. SCHMUCK1 Joint Research Centre Institute for Remote Sensing Applications (1) Advanced Techniques (2) Monitoring Tropical Vegetation 21020 Ispra (Va), Italy * Permanent affiliation: LAMP/OPGC, Université Blaise Pascal, 63177 Aubière, France ABSTRACT An improved version of the SAIL model which includes the hot spot effect and the spectral variation of vegetation reflectance is used to retrieve canopy biophysical parameters from visible and near infrared radiometric data. The leaf mesophyll structure, the chlorophyll a+b concentration, the leaf area index, the mean leaf inclination angle and the hot spot size parameter are determined by inversion of the coupled PROSPECT+SAIL model. Four different optimization methods (Quasi-Newton, Marquardt, Simplex, Genetic Algorithms+Quasi-Newton) are tested with several kinds of data (synthetic data and airborne data acquired with the CAESAR sensor) and compared in terms of accuracy and computation time. KEY WORDS: canopy reflectance, models, inversion INTRODUCTION The interpretation of optical remote sensing data for agricultural and ecological applications is still problematic. A classical approach involves vegetation indices built from reflectance values acquired in the red and near infrared by spaceborne sensors. The development of a new generation of instruments capable of measuring the spectral radiance at several viewing angles may be accompanied by new methods of interpretation.

• reflectance


• reflectance induced


• method based


• noise-disturbed inversions


• plant canopy


• qn method


• parameters can account


• reflectance spectrum