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학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
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연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2022.12
- 수록면
- 55 - 61 (7page)
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This study was conducted to compare and analyze summer and winter land cover classifications using Sentinel-2 satellite images. Land cover classification is a method of classifying the physical condition of the ground surface. There are two types of classification methods: supervised classification and unsupervised classification. The unsupervised classification does not require any training data and errors may occur in classifying only by the characteristics of the image. Therefore, in this study, we performed the land cover classification with images of summer and winter by the unsupervised classification method to investigate their seasonal differences and what is the limitation of such classification. First, the satellite images were inserted into the ArcGIS software to be classified into 10 classes through isodata training of unsupervised classification. As a result of the classification, categories of similar features were recombined to have a total of 6 categories (land covers) such as water, built-up, grassland, forest, road, and bare soil. We compared the six land covers in this way between summer and winter.
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UCI(KEPA) : I410-ECN-0101-2023-539-000368074