面向对象的土地利用/覆盖遥感分类方法与流程应用

为了进一步提高干旱/半干旱地区土地利用/覆盖分类精度，该文以新疆石河子垦区为研究区，利用NDVI时间序列分析的方法确定了土地利用/覆盖遥感分类最佳时相组合；采用最佳指数因子OIF对参与图像分割的谱段进行选择；选择不同分割参数建立4级分割层次，构建了不同尺度的分类对象；针对其不同特点，分别选择基于知识的模糊分类和基于样本的监督分类方法；建立了面向对象的土地利用/覆盖遥感分类流程。采用地面实测数据对分类效果进行评估，与基于像元的分类方法相比，该文方法能够获取更高的分类精度，可为同类的研究与应用提供借鉴。

Application of method and process of object-oriented land use-cover classification using remote sensing images

Taking Shihezi county as study area, the best temporal combination of land use-cover remote sensing classification was presented in the paper by NDVI time series analysis in order to further improve classification accuracy in arid and semi-arid areas. And the optimum segmental bands were selected with OIF index method. Four segmental levels were selected based on different segmentation parameters and different scales classification objects were constructed. According to the characteristic of different kinds of objects, the process of object-oriented land use-cover classification was worked out by means of fuzzy classification knowledge-based and unsupervised classification example-based respectively. Classification effects were evaluated through ground test data of the study area. Comparing with the method of pixel classification, the results show that the new method has higher accuracy, and can be a reference for later researches and applications.