基于分类变化检测方法的地表覆盖影像特征数据更新处理研究

Research on Updating Process of Land Cover Image Feature Data Based on Classification Change Detection Method

为了更好地采集我国地理地貌影像,提高地表影像的采集检测精度,选取海南省某地的卫星遥感影像作为分析数据,基于分类变化检测方法,对地表覆盖影像进行分类处理后,结合向后数据处理理论对其各类地表数据进行更新处理,实时更新当期采集的地表影像数据特征信息。研究结果表明,该方法能够较好地对地表特征信息进行分类,整体采集精度约为96.6%,计算过程自动进行,较传统的人工分类算法节省了大量的人力、物力、财力,能够为我国地表特征变化信息的检测提供良好的理论支撑。

In order to better collect topographic and geomorphological images of our country and improve the accuracy of land cover image acquisition and detection,satellite remote sensing images of a certain place in Hainan province are selected as analysis data.Based on the method of classification change detection,the land cover images are classified and processed.In combination with the theory of backward data processing,all kinds of land cover data are updated,and the land cover image data features are updated in real time.The research results showed that this method can classify the land cover feature information well.The accuracy of feature information classification was about 96.6%,and the calculation process was automatic.As compared with the traditional manual classification algorithm,it can save a lot of manpower,material,and financial resources,and provide a good theoretical support for the detection of land cover feature change information in China.