文章使用A STER遥感数据和土地利用分布图等地理辅助数据,用BP神经网络方法对土地覆盖进行了分类,并与最大似然法的分类结果进行精度比较分析提出神经网络方法在遥感图像分析与处理技术中的应用潜力。结果表明地理辅助数据参与的BP神经网络用于土地覆盖分类研究可以获得相对较好的分类结果。 This paper classified the land cover by using the BP neural network method and other geography aided data such as A STER remote sensing data and land use distribution map, compared with the classification results of the maximum likelihood method, and compared the accuracy of the neural network method in the remote sensing image analysis and Potential for processing technology. The results show that the BP neural network with geo-assistant data can be used to classify the land cover and get better classification result.