利用面向对象的信息提取技术进行城市用地分类

Classification of Urban Land Using Object-oriented Information Extraction Technology

针对城市用地分类问题,利用面向对象的高分辨率影像信息提取技术,对高分辨率影像进行影像分割,寻找影响对象提取精度的最优分割尺度,在得到最优分割尺度的基础上针对研究区城市用地的特点,有针对性地建立不同对象的提取规则,实现对目标对象的信息提取,从而形成最终的城市用地分类图,并将其与基于像元的光谱信息分类的方法进行对比,结果表明:视觉方面,面向对象信息提取技术克服了监督分类最大似然方法仅利用光谱信息分类的缺陷,充分考虑了像元间的空间关系特点,有效消除了"椒盐"噪声的影响;精度方面,面向对象信息提取技术的总体精度高达86.1166%,比最大似然法的总体精度提高了9.8851%,KAPPA系数也高达0.8131。

Object-oriented extraction technology is applied to urban land classification for the purpose of finding the optimal segmentation scale,which affects the accuracy of the classification,and combining with the characteristics of the study area. Different extraction rules should be established to extract the object information.Compared with the pixel-based classification method,the results shows that：1object-oriented extraction technology takes full account of the spatial relationships between features,and eliminates the＂pepper and salt＂noises;2In accuracy,the overallaccuracy of the object-oriented extraction technology is up to 86.1166%,9.8851 percentage points higher than the maximum likelihood method,Also a KAPPA coefficient of 0.8131 is acquired.