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• W2030536700 abstract "With rapid land development, land category should be updated on a regular basis. However, manual field surveys have certain limitations. In this study, attempts were made to extract a feature vector considering spectral signature by parcel, PIMP (Percent Imperviousness), texture, and VIs (Vegetation Indices) based on RapidEye satellite image and cadastral map. A total of nine land categories in which feature vectors were significantly extracted from the images were selected and classified using SVM (Support Vector Machine). According to accuracy assessment, by comparing the cadastral map and classification result, the overall accuracy was 0.74. In the paddy-field category, in particular, PO acc. (producer's accuracy) and US acc. (user's accuracy) were highest at 0.85 and 0.86, respectively." @default.
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• W2030536700 date "2014-12-31" @default.
• W2030536700 modified "2023-09-25" @default.
• W2030536700 title "Extraction of Spatial Characteristics of Cadastral Land Category from RapidEye Satellite Images" @default.
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• W2030536700 doi "https://doi.org/10.7848/ksgpc.2014.32.6.581" @default.
• W2030536700 hasPublicationYear "2014" @default.
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