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- W2888745308 abstract "This study detected the required parameters to segment the Landsat 8 satellite imageries at different levels for mapping Land Use/Land Cover (LULC). Firstly, Mutiresolution segmentation was used to segment the images into different levels. Two important parameters used to segment are Scale and Shape; of which different levels – 20, 30 and 40 for Scale; and 0.1, 0.2, 0.3 and 0.4 for Shape – were tested. Secondly, Nearest Neighbor classifier was applied on the segmented images to classify the whole area into 7 different types of LULC using training sites from field and available data. Finally, the classification results were validated using independent data based on the two criteria of Overall Accuracy and Kappa coefficient. The results show that the best result was found in case of using the Scale=40 and the Shape parameter=0,3 which gained the highest accuracy with Overall Accuracy was 81,9% and Kappa coefficient was 0,788." @default.
- W2888745308 created "2018-08-31" @default.
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- W2888745308 date "2018-01-01" @default.
- W2888745308 modified "2023-09-25" @default.
- W2888745308 title "Lựa chọn tham số phân đoạn phù hợp để phân loại ảnh vệ tinh đa phổ Landsat 8 OLI" @default.
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- W2888745308 doi "https://doi.org/10.22144/ctu.jvn.2018.065" @default.
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