Abstract
Very high spatial resolution remote sensing images have applications in many fields. However, research on the intelligent interpretation of such images is insufficient partly because of their the complexity and large size. In this study, a high spatial resolution remote sensing image intelligent interpretation system (HSR-RSIIIs) was designed with image segmentation, a geographical information system, and a data-mining algorithm. Some key methods such as image segmentation, feature extraction, feature selection, and classification algorithm for interpreting high spatial resolution remote sensing image have been studied. A land cover classification experiment was performed in the Zhuzhou area using a Quickbird multi-spectral image. The classification results were consistent with the visual interpretation results. In additional, the proposed interpretation method was compared with the traditional pixel-based method. The results indicate that the method proposed in the literature is more effective and intelligent than that used previously.