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Automatic Extraction of Initial Training Data Using National Land Cover Map and Unsupervised Classification and Updating Land Cover Map
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 Title & Authors
Automatic Extraction of Initial Training Data Using National Land Cover Map and Unsupervised Classification and Updating Land Cover Map
Soungki, Lee; Seok Keun, Choi; Sintaek, Noh; Noyeol, Lim; Juweon, Choi;
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Those land cover maps have widely been used in various fields, such as environmental studies, military strategies as well as in decision-makings. This study proposes a method to extract training data, automatically and classify the cover using ingle satellite images and national land cover maps, provided by the Ministry of Environment. For this purpose, as the initial training data, those three were used; the unsupervised classification, the ISODATA, and the existing land cover maps. The class was classified and named automatically using the class information in the existing land cover maps to overcome the difficulty in selecting classification by each class and in naming class by the unsupervised classification; so as achieve difficulty in selecting the training data in supervised classification. The extracted initial training data were utilized as the training data of MLC for the land cover classification of target satellite images, which increase the accuracy of unsupervised classification. Finally, the land cover maps could be extracted from updated training data that has been applied by an iterative method. Also, in order to reduce salt and pepper occurring in the pixel classification method, the MRF was applied in each repeated phase to enhance the accuracy of classification. It was verified quantitatively and visually that the proposed method could effectively generate the land cover maps.
Land Cover Map;Training Data;MRF;Medium-resolution Satellite Image;
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Landsat 위성영상을 활용한 낙동강 삼각주 연안사주의 면적 시계열 분석,이슬기;양미희;이창욱;

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