面向对象的 ALOS 影像土地覆盖信息提取

    Land cover information extraction based on ALOS image by object-oriented method

    • 摘要: 根据高分辨率遥感数据, 采用面向对象分类方法, 对南京市某地块的土地覆盖信息进行提取。 由于分类单元不再是单个像素, 而是综合了光谱信息、 纹理特征、 拓扑关系和专题信息的影像对象, 使得分类总体精度较传统方法提高 18.1%, 克服了传统基于像元分类法中的“椒盐现象” , 并且大幅降低了“异物同谱” 、 “同物异谱”对分类结果的负面影响。 该方法对于依托高分辨率遥感影像进行土地覆盖信息的提取与更新, 具有可行性和推广性。

       

      Abstract: According to the high resolution remote sensing image data, this paper used the object-oriented classification method to extract the land cover information of Nanjing city. Because the classification unit was not single pixel but image objects, which integrated the spectral information, texture feature, topological relationship and thematic information, the overall accuracy of classification enhanced by 18.1% compared to conventional method. The object- oriented method also overcame the pepper salt phenomenon which occurred in conventional method, and reduced the negative effects of foreign bodies with spectrum and different object with the same spectra characteristics. For the land cover information extraction and updating using high resolution remote sensing image, this method had practicable and generalization performance.