基于ETM^+影像的森林资源信息提取——以黄土高原丘陵沟壑区水土保持林为例  

Information extraction of forest resources based on ETM^+ image:A case study of water and soil conservation forest in a hilly and gully area of Loess Plateau

作　　者：李巍岳[1,2] 胡志斌[1] 闫巧玲[1] 

机构地区：[1]中国科学院沈阳应用生态研究所,沈阳110016 [2]辽宁工程技术大学测绘与地理科学学院,辽宁阜新123000

出　　处：《生态学杂志》2009年第9期1737-1742,共6页Chinese Journal of Ecology

基　　金：中国科学院知识创新工程重大项目(KZCX1-YW-08-02);国家自然科学基金项目资助(40701185)

摘　　要：以森林资源遥感分类为切入点,以黄土高原丘陵沟壑区陕西黄龙县境内的水土保持林作为对象,针对ETM+遥感影像在森林信息提取中存在的大量混合像元的问题,引入一种基于针叶林-阔叶林-灌草(C-B-G)模型的混合像元分解方法,通过这种方法,分别得到研究区针叶林、阔叶林、灌草的覆盖图像,并提取出了针阔混交林的分布情况。采用ER-DAS 9.1对分类结果进行精度评价,结果表明针阔混交林的分类精度相对于通用分类方法——监督分类的精度提高了20%,说明该方法可以改善植被信息提取的效果。According to the remote sensing classification of forest resources, the water and soil conservation forests in Huanglong County of Shaanxi Province, a hilly and gully area of Loess Plateau, were chosen as research objects, and a mixed pixel decomposition method based on coniferous-broad leaved-grass （C-B-G） model was introduced for solving the mixed pixel problems in forest information extraction by ETM ^＋ remote sensing images. Using this method, the cover images of coniferous forest, broad-leaved forest, bush, and grass were obtained respectively, and the distribution of coniferous and broad-leaved mixed forest was extracted. Erdas 9. 1 was used to evaluate the classification accuracy. Comparing with the supervised classification, a general clas- sification method, our method had 20% higher classification accuracy on the coniferous and broad-leaved mixed forest, suggesting its improved effect in vegetation information extraction.

关 键 词：ETM^+影像 混合像元 针阔混交林 分类精度 

分 类 号：S712[农业科学—林学]