High-resolution remote sensing images using in water system classification
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Abstract:
Effective extraction of water system in the high-resolution remote sensing image is essential for the fast, high efficiency, wide range monitoring of the overall water system. In this paper, the study area is made the multi-scale segmentation of remote sensing image by eCognition software, it selects the most appropriate spectral factor , the best shape factor and ) for the segmentation; and then procees to the classification of object-oriented. It chooses Brightness in Layer Values of the object’s Spectral information and length/width in the object’s Geometry for the classification. The classification is made through the nearest neighbor classification method and the membership function classification method. Remote sensing image is classified into water system and other types of land. The classification result of object-oriented is better than the pixel-based classification relying solely on the spectral information. Classification result is more consistent with the way of human thinking. Through the comparison of the land-use classification result map and the best classification result computed in the software, it concludes that nearest neighbor classification is more accurate in the water system classification.
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