基于归一化高光谱位置变量的干叶片生化组分分析  

Analysis of Dry-Leaf Biochemistry Based on the Normalized Hyperspectral Position Variables

作　　者：沈艳[1] 牛铮[2] 缪启龙[1] 徐永明[3] 

机构地区：[1]南京信息工程大学大气科学系,江苏南京210044 [2]中国科学院遥感应用研究所遥感科学国家重点实验室,北京100101 [3]南京信息工程大学中美合作遥感中心,江苏南京210044

出　　处：《南京气象学院学报》2006年第6期833-838,共6页Journal of Nanjing Institute of Meteorology

基　　金：中国科学院知识创新工程重要方向项目(KZCX3-SW-338);国家自然科学基金资助项目(40571117);中国气象局气象新技术推广项目(CMATG2006Z03)

摘　　要：利用实测干叶片生化组分和高光谱反射率数据,提出了基于面积归一化的高光谱位置变量一阶导数极值法提取生化组分的新思路。结果表明:该方法能较好地提取叶片全氮、纤维素、木质素和淀粉含量,尤其是对纤维素、木质素和淀粉含量的反演精度有了提高。研究还表明:该方法在提取全氮、纤维素、木质素含量时,能有效剔除土壤影响,但是在提取淀粉含量时,效果不够理想。Using the measured dry-leaf biochemistry and hyperspectral reflectance data, a new thinking clue of leaf biochemical retrieval is developed based on the 1 st derivative extremum of area-nomalized hyperspectral position variables. Research results indicate that this method can be employed to effectively extract the concentration of foliar total nitrogen, cellulose, lignin and starch. Especially the retrieval precision of cellulose, lignin and starch contents is better than the research available. Moreover, the ultimate application direction of vegetation remote sensing is the its canopy level. The investigation suggests that this technique can effectively remove soil influence on the extraction of total nitrogen,cellulose and lignin content,but the retrival result of starch is still not satisfactory.

关 键 词：高光谱 位置变量 生化组分 面积归一化 

分 类 号：TP79[自动化与计算机技术—检测技术与自动化装置] Q945[自动化与计算机技术—控制科学与工程]