Abstract
Remote sensing images are increasingly important in providing information to monitor the earth's surface. To make the most of this data source, remote sensing image classification methods are becoming smarter and more efficient, converting information on images into valuable information. The object-based classification method has proven its accuracy compared to the pixel-by-pixel classification method. However, this method is often applied to high-resolution satellite images but has not been widely applied to medium-resolution satellite images, moreover, the combined use of both classification methods has not been proven. lots of testing. This study combines object-based classification and pixel-based classification methods to improve classification accuracy. The results show that combining both methods can improve the overall classification accuracy by 20% when using high-resolution images.