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- W2381301960 abstract "In this paper we compare the performance of two image classification paradigms(object-and pixel-based) for creating a land cover map of suburb of Guangzhou city, China using High-resolution satellite image, the QuickBird images.The image was classified into residential area, water, road, and forest and agriculture land by using supervised and unsupervised combined classification for the pixelbased approach and nearest neighbor(NN) method for the object-oriented approach.The classification outputs were assessed using overall accuracy and Kappa indices.The pixel-and object-based classification methods result in an overall accuracy of 78.53% and 89.53%, respectively.The Kappa coefficient for pixel-and object-based approaches was 0.73 and 0.87, respectively.The object-oriented method greatly lighten the noise influence, has higher classification accuracy and efficiency than that achieved by pixel-based method.Meanwhile, the classification result of object-oriented method is much easier to understand and explain." @default.
- W2381301960 created "2016-06-24" @default.
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- W2381301960 date "2009-01-01" @default.
- W2381301960 modified "2023-09-24" @default.
- W2381301960 title "Classification of Urban Land Use Based on Object-oriented Method" @default.
- W2381301960 hasPublicationYear "2009" @default.
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