利用多参数机载全球雷达(GIobeSAR)数据和航天飞机成像雷达(SIR-C/X-SAR)数据,分别在我国南、北方两个试验区进行森林识别与分类,以及蓄积量估测的试验。为了更好地了解雷达后向散射与森林结构特征的关系,分别从雷达图像上提取了后向散射系数和强度,进行森林类型识别效果的分析,以及森林结构参数与雷达后向散射强度的相关分析。结果显示多波段、多极化SAR数据能有效地识别不同类型的森林。雷达的后向散射强度对森林的结构参数,尤其是森林的平均胸径和高度较为敏感,据此对试验区的森林蓄积量进行了估测,并分析了多参数SAR在森林应用中的潜力。

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.