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• W2894325828 abstract "Google Earth is a source of high spatial resolution images. The freely available Google Earth (GE) images are utilized to generate Land use/Land cover thematic map of the highly heterogeneous landscape of typical urban scene. In this paper, we have presented Euclidean Distance and Average Pixel Intensity based K-NN classification to classify five different land objects. The classification accuracy of the proposed method is compared against generic K-NN. The overall classification accuracy and the kappa value of generic K-NN are found to be 75.04% and 0.74 respectively. Whereas, proposed method results with 76.38% and 0.78. Both the methods exhibits classification error because of poor spectral reflectance properties of google earth imagery." @default.
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• W2894325828 date "2017-12-01" @default.
• W2894325828 modified "2023-09-27" @default.
• W2894325828 title "Land Use/ Land Cover Classification of Google Earth Imagery" @default.
• W2894325828 doi "https://doi.org/10.1109/wiecon-ece.2017.8468898" @default.
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