Abstract: Land cover classification is processed by Mahalanobis Distance method, maximum likelihood method, and support vector machine method with confusion matrix assessing the classification accuracy. The results show that the maximum likelihood method and support vector machine method are effective. Maximum likelihood method is taken as an example for land cover classification performance analysis by introducing the Normalized Difference Vegetation Index（NDVI） and GLCM texture features. Results reveal that the classification accuracy is improved to varying degrees when NDVI, CONTRAST, MEAN are incorporated in classification process. Further combination of the three features with the original band represents the highest classification accuracy. The general landscape pattern characteristics are quantified based on  classification results and landscape metrics. The results show that cropland and human settlements are dominating the landscape with an area ratio of 82%, which implies high human pressure and ecological risk in the landscape. It is, therefore, necessary to strengthen land use planning and management in the desert-oasis transitional area in the middle reaches of the Heihe River. Specifically, concrete measures are urgently needed to slow down and regulate cropland and residential area expansion with improved land use efficiency. At the same time, ecological conservation and rehabilitation need to be enhanced to increase landscape resilience to disturbances.

Key words: ALOS, land cover, classification, landscape pattern

摘要： 通过马氏距离法、最大似然法、支持向量机三种途径对土地覆盖进行分类，以混淆矩阵对分类结果做精度评价，结果显示，最大似然法和支持向量机分类有较好的效果。以最大似然法为例，通过引入归一化植被指数（NDVI）、基于灰度共生矩阵的纹理特征等进行不同特征组合的分类，探讨其对分类的影响。研究表明，NDVI、对比度、均值参与分类后，对分类精度都有不同程度的提高，而三者与原始波段的结合分类精度最高。基于分类结果做景观格局定量分析。结果表明，研究区景观类型较为丰富，以耕地为主导，再加上城镇和农村聚落用地，约占到整个研究区的82%，表明景观所受的人类活动干扰和压力很大、生态风险高。因此，必须强化黑河中游绿洲荒漠区的土地利用规划和管理，适当约束耕地和聚落用地的扩张，提高土地利用效率；要加强生态保护和建设，提高景观的抗干扰能力。

关键词: ALOS, 土地覆盖, 分类, 景观格局