本文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丰富的信息，提高了信息提取的精度目的。

In this paper, taking 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 to 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 extracted information.