中文摘要：

为了更准确地对遥感数据进行分类，结合GeoEye高分辨率遥感影像和机载LiDAR数据，通过对分割参数、特征选择、分类规则等特征进行研究，提出采用面向对象的模糊分类方法——成员函数法选择实验区进行了分类研究。实验结果表明：该分类方法能够更有效地提取出建筑物、煤堆、灌木等矿区典型地物，总体分类精度达到93．92％，KIA为92．52％，分类精度相比单一遥感数据明显提高。

英文摘要：

With the development of high resolution remote sensing technology and the multi-source of data acquisition, the multi-source sensor data fusion method has become a hot spot in the field of remote sensing information extraction. This paper combined GeoEye high resolution aviation image with the LiDAR data, by the research on segmentation parameters, feature selection, and classification rules characteristics, puts forward the utilization of the fuzzy method for object-oriented classification--member function method to select a classification study of the experimental area. The result showed that this object-oriented classification method can be more effectively extracted the buildings, coal pile, shrubs, and other mining typical objects, and that the overall accuracy reached 93.92% , KIA is 92.52%. Compared to the single remote sensing data, the classification accuracy has been significantly improved.