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Landsat 위성을 활용한 지속적인 수자원 관리  

Jeong, Yun-Jae ((주)지오씨엔아이 GIS 연구소)
Lee, Eung-Jun ((주)지오씨엔아이 GIS 연구소)
Park, Hye-Ji ((주)지오씨엔아이 제2센터)
Jo, Myeong-Hui (경북대학교 융복합시스템공학부)
Publication Information
Water for future / v.52, no.3, 2019 , pp. 43-47 More about this Journal
Keywords
Citations & Related Records
연도 인용수 순위
  • Reference
1 한국항공우주연구원. 인공위성. Available online: https://www.kIlri.re.kr/kor/sub03_02.do (assessed on 18 March 2019).
2 Choung, Y.-J., Jo. M.-H. 2016. Shoreline change assessment for various types of coasts using multi-temporal Landsat imagery of the east coast of South Korea. Remote Sensing Letters, 7, 1, 91-100.   DOI
3 Cheung, Y.-J., Jo, M.-H. 2017. Comparison between a Machine-Learning-Based Method and a Water-Index-Based Method for Shoreline Mapping Using a High-Resolution Satellite Image Acquired in Hwado Island, South Korea. Journal of Sensors 2017, 1-13.
4 Satellite Imaging Corporation. Landsat 8 Satellite Sensor (15cm), Available online: https://www.satimagingcorp.com/satelllte-sensors/other-satellite-sensors/landsat-8/ (assessed on 18 March 2019)
5 USGS. Landsat Missions. Available online: https://www.usgs.gov/land-resources/nli/landsat (assessed on 18 March 2019)