GF-2影像城市地物分类方法探讨

GF-2影像具有较高的分辨率和丰富的光谱、几何及纹理信息。为了深入探索GF-2影像城市地物分类方法，本文以四川省隆昌县城为研究区，提出了一种基于最优尺度和规则的面向对象分类法。在影像分割的基础上，通过构建评价函数，并结合最大面积法选取最优尺度，进而构建分层体系，提取影像的光谱、几何及纹理特征建立规则并分类，且将其与单尺度下的面向对象和基于像素分类法进行对比分析。结果表明，本文方法的总体精度和Kappa系数分别为93.33%和0.92。

Discussion on classification methods of urban features based on GF-2 images

The GF-2 image has higher resolution as well as more detailed characteristics of spectral, features, geometric and texture. In order to explore the classification method of the GF-2 image in urban features, an object oriented classification method based on optimal scale and rules is proposed in the study area of Longchang County, Sichuan Province. Based on segmentations, the evaluation function is constructed, combining with the maximum area method, optimal segmentation scales are selected to construct multiple layers. The spectral, geometric and texture features of the image are extracted to establish rules for classification and compared with the classification methods of object-oriented with the single scale and pixel based. The results show that the overall accuracy and Kappa coefficient of the proposed method are 93.33% and 0.92, respectively.