利用高光谱遥感数据进行农作物分类方法研究  

Study on Classification of Agricultural Crop by Hyperspectral Remote Sensing Data

作　　者：刘亮[1] 姜小光[2] 李显彬[1] 唐伶俐[1] 

机构地区：[1]中国科学院中国遥感卫星地面站 [2]中国科学院光电研究院,北京100080

出　　处：《中国科学院研究生院学报》2006年第4期484-488,共5页Journal of the Graduate School of the Chinese Academy of Sciences

基　　金：国家自然科学基金项目(40271048)资助

摘　　要：以北京顺义区为研究区,研究、探讨利用高光谱遥感数据,通过逐级分层分类方法进行农作物信息提取与挖掘的基本思路和步骤.该方法面向应用目标,将复杂的信息提取过程分为相对简单的子过程,每个子过程根据拟提取的目标不同而选择不同特征参数和信息提取方法,从而实现有效地利用高光谱数据的丰富信息,提高信息提取精度的目的.In this paper,taking the Shunyi district hyperpectral imagery as an example,we probe into the keypoints and principal procedures for multi-level classification approach and apply this object-oriented method in extracting and mining crops information. Because multi-level classification approach can simplify the complicated information extraction procedure into several relatively easy sub-process, we can intentionally select different characteristic parameters and data mining methods for information extraction in each sub-process according to the feature of the crop we want to discriminate. Consequently, we can make the most of the abundant information in hyperspectral data, and improve the precision of the extracted information.

关 键 词：成像光谱遥感 农作物 信息提取 特征选择 

分 类 号：TP75[自动化与计算机技术—检测技术与自动化装置]