This paper presents the results of forest discrimination

classification

and volume estimation in two test sitesof China using multiparameters airborne and spaceborne imaging radar data. The SAR data were acquired duringSIR-GX-SAR and GlobeSAR missions. To improve the understanding of radar backscatter to canopy geometric feature

we extracted backscatter coefficient and intensity to analyze the effect of forest type discrimination

and the relationshipbetween forest parameters and radar backscatter. This study shows that it is very efficient for multifrequency andmultipolarization SAR data to discriminate different types of forest. The intensity of radar backscatter is also quitesensitive to the forest parameters

especially diameter at breast height (dbh) and tree mean height. Based on thissensitivity

the forest volume of the test site was estimated. Finally

the potential of multiparameters SAR data for forestapplications was analyzed.