http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
- 中文 을 입력하시려면 zhongwen을 입력하시고 space를누르시면됩니다.
- 北京 을 입력하시려면 beijing을 입력하시고 space를 누르시면 됩니다.
RISS 인기검색어
- 검색키워드
- 저자 : 윤성욱 ( Seong Uk Yoon ) (검색결과 3 건)
- 무료
- 기관 내 무료
- 유료
-
SENTINEL-2 위성영상을 이용한 조림 특성 조사: 세미양오름를 통한 사례 연구
정용석,윤성욱,허성,김윤석,안진현,한경덕,Chung, Yong Suk,Yoon, Seong Uk,Heo, Seong,Kim, Yoon Seok,Ahn, Jinhyun,Han, Gyung Deok 한국환경과학회 2022 한국환경과학회지 Vol.31 No.9
Global warming affects forests and their ecology. Diversity in the forest is a buffer that reduces the damage due to global warming. Mixed forests are ecologically more valuable as versatile habitats and are effective in preventing landslides. In Korea, most forests were created by simple afforestation with trees of evergreen species. Typically, evergreen trees are shallow-rooted, and deciduous trees are deep-rooted. Mixed forest tree roots grip the soil effectively, which reduces the occurrence of landslides. Therefore, improving the distribution of tree types is essential to reduce damage due to global warming. For this improvement, the investigation of tree types of the forest is needed. However, determining the tree type distribution of forests that are spread over wide areas is labor-intensive and time-consuming. This study suggests effective methods for determining the distribution of tree types in a forest that is spread across a relatively wide area. Using normalized difference vegetation index and RGB images from unmanned aerial vehicles, each evergreen and deciduous tree, and grassland area can be distinguished. The distinguished image determines the distribution of tree type. This method is effective compared to directly determining the tree type distribution in the forest by the use of manpower. The data from these methods could be applied to plan a mixed forest or to prepare for future damage due to global warming.
-
위성화상을 이용한 고도 1,600 m 이상의 한라산 적설 면적 변화 추적
한경덕,윤성욱,정용석,안진현,이승재,김윤석,민태선,Han, Gyung Deok,Yoon, Seong Uk,Chung, Yong Suk,Ahn, Jinhyun,Lee, Seung-Jae,Kim, Yoon Seok,Min, Taesun 한국환경과학회 2022 한국환경과학회지 Vol.31 No.10
It is necessary to understand the amount of snowfall and area of snow cover of Mt. Halla to ensure the safety of mountaineers and to protect the ecosystem of Mt. Halla against climate change. However, there are not enough related studies and observation posts for monitoring snow load. Therefore, to supplement the insufficient data, this study proposes an analysis of snow load and snow cover using normalized-difference snow index. Using the images obtained from the Sentinel2 satellite, the normalized-difference snow index image of Mt. Halla could be acquired. This was examined together with the meteorological data obtained from the existing observatory to analyze the change in snow cover for the years 2020 and 2021. The normalized-difference snow index images showed a smaller snow pixel number in 2021 than that in 2020. This study concluded that 2021 may have been warmer than 2020. In the future, it will be necessary to continuously monitor the amount of snow and the snow-covered area of Mt. Halla using the normalized-difference snow index image analysis method.
-
위성이미지 기반 시설하우스 판별 Mask-RCNN 모델 개발
김윤석 ( Yun Seok Kim ),허성 ( Seong Heo ),윤성욱 ( Seong Uk Yoon ),안진현 ( Jinhyun Ahn ),최인찬 ( Inchan Choi ),장성율 ( Sungyul Chang ),이승재 ( Seung-jae Lee ),정용석 ( Yong Suk Chung ) 한국농림기상학회 2021 한국농림기상학회지 Vol.23 No.3
본 인스턴스 분할 모델은 위성을 이용해 촬영된 원격탐지 영상 내의 객체 탐지에 높은 정확도를 갖는다는 것을 입증하였으며, 불법으로 가설된 시설 하우스를 발견하는데 활용될 수 있다. 즉, 특정 지역 및 일정시기를 기준으로 시설하우스를 인식시키고 그 이후에 신축된 하우스를 분별하는데 사용할 수 있을 것이다. 또한 본 기술을 응용하여, 토지피복도 조사와 같은 인력중심의 작업을 빠르게 해결할 수 있다. 앞으로 이 모델은 지리정보시스템(Geographic Information System)과 연계하여 중앙정부 차원의 단일화된 관리체계를 수립할 수 있을 것이며 또한 시설하우스 면적 통계 수치 계산에도 쉽게 응용될 수 있을 것으로 판단된다. The number of smart farms has increased to save labor in agricultural production as the subsidy become available from central and local governments. The number of illegal greenhouses has also increased, which causes serious issues for the local governments. In the present study, we developed Mask-RCNN model to detect greenhouses based on satellite images. Greenhouses in the satellite images were labeled for training and validation of the model. The Mask-RCNN model had the average precision (AP) of 7 5.6%. The average precision values for 50% and 75% of overlapping area were 91.1% and 81.8%, respectively. This results indicated that the Mask-RCNN model would be useful to detect the greenhouses recently built without proper permission using a periodical screening procedure based on satellite images. Furthermore, the model can be connected with GIS to establish unified management system for greenhouses. It can also be applied to the statistical analysis of the number and total area of greenhouses.
ScienceON
DBpia연관 검색어 추천
이 검색어로 많이 본 자료
활용도 높은 자료
