A Classification Study Of High Resolution Data Of Remote Sensing Based On The Object-oriented Analysis

With the application of the high-resolution image more and more popular, it is urgently require people to carry on research to classification of the high-resolution remote sensing in order to meet the increasing application and study requirement of the information of high-resolution images. However, when used the traditional pixel-oriented method to classify the high-resolution remote sensing image, it can't fully utilize image information, should reduce the precision of classification and has slow speed. According to the characteristic of the high-resolution remote sensing image, the paper proposes to use the object-oriented method to classify high- resolution remotely sensed data.Taken SPOT5 image of Xiamen Island as an example, choosing the typical urban building area and landuse abundant area as study areas, and regarding Ecognition software as the platform, the paper carry on the classification experiment to the study areas. The paper dose the research by the follow steps: 1) according to the characteristic of different surface features types, choosing the optimum scale to segment the area to extract the objects; 2) constructing the classification system; 3) extracting the characteristics or characteristic associations of the surface feature types; 4) adopting fuzzy classification to classify to surface feature types, then getting the classification result of study areas. At the end, the paper compares and appraises the classification result between the method of object-oriented and pixel-oriented (such as the maximum likelihood classification, the minimum distance classification, the mahalanobis distance classification, and the Isodata cluster classification) The result indicates that: 1) The extracted surface features have higher shape and attribute consistency with true surface features when used object-oriented method; 2) It has higher precision when used object-oriented method to classify the high-resolution image; 3) The object-oriented method is so effective to reduce the "Pepper and Salt Phenomenon"; 4) The classification result of object-oriented analysis is more easy to understand and explain.