基于高分二号数据的面向对象城市土地利用分类研究

利用国产高分二号数据提取城市地物类别的方法研究具有重要的意义。以鸡西市城区作为研究区域,采用高分二号(GF-2)遥感影像为数据源,对影像进行多尺度分割,建立相应地物的分类规则,采用规则集的面向对象分类方法对地物进行分类,并与支持向量机(Support Vector Machine,SVM)监督分类结果进行比较。实验结果发现:利用面向对象方法对城市土地利用分类的总体精度92.52%,Kappa系数为0.91,与SVM方法相比较,有很大的提高,分类效果更加能体现城市地类形状特征。使用面向对象的分类方法对高分二号影像进行分类效果更好,精度更高,基于高分二号数据面向对象分类方法是提取城市土地利用分类的有效方法。

Object-oriented Urban Land Classfication with GF-2 Remote Sensing Image

It is of great significance to study the method of extracting urban features from GF-2 remote sensing data.Taking the urban area of Jixi City as the study area,and the GF-2 image is used as the data source.The image is divided into multiple scales,the classification rules of the corresponding objects are established,and the object-based classification method of the rule set is used to classify the objects.Compare with SVM supervised classification results .The results show that the overall accuracy of object-oriented classification is 92.52 %,and the Kappa coefficient is 0.91,which is significantly higher than the SVM supervised classification.Using the object-oriented classification method to classify the GF-2 image is better and the precision is higher.Object-oriented classification method based on GF-2 data is an effective method for extracting urban land use classification.