Tracking diurnal to seasonal variations of gross primary productivity using a geostationary satellite, GK-2A advanced meteorological imager
2022 · Remote Sensing of Environment
저자
Sungchan Jeong, 류영렬 (Youngryel Ryu), Benjamin Dechant, Xing Li, Juwon Kong, Wonseok Choi, Minseok Kang, Jong‐Min Yeom, Joongbin Lim, Keunchang Jang, Jung‐Hwa Chun
연구주제
Remote Sensing in Agriculture · Plant Water Relations and Carbon Dynamics · Remote Sensing and LiDAR Applications
NTIS 과학기술표준분류
에너지/자원만에너지·환경·원자력 확장
배정 근거: AI 키워드가 잡은 NTIS 과제의 분류(정책 연계 맵과 같은 방법).
AI 연구 키워드·방법
정지궤도 위성 관측 총일차생산량(GPP) 식생 근적외선 반사율(NIRv)
키워드 (OpenAlex)
gross primary productivity geostationary satellites diurnal variation seasonal variation canopy photosynthesis near-infrared reflectance photosynthetically active radiation atmospheric correction
초록
The diurnal sampling capability of geostationary satellites provides unprecedented opportunities for monitoring canopy photosynthesis at multiple temporal scales. At the diurnal scale, only geostationary satellites can currently provide sub-daily data at regular intervals, also it can help to minimize data gaps due to clouds at the seasonal scale. However, the potential of geostationary satellites for monitoring photosynthesis has not been explored in depth. In this study, we tracked diurnal to seasonal variations in gross primary production (GPP) using the product of near-infrared reflectance of vegetation and photosynthetically active radiation (PAR) (NIRvP) over deciduous forests, mixed forests and a rice paddy during the growing season. For this purpose, we generated three levels of reflectance and PAR from Geostationary Korea Multi-Purpose Satellite-2A (GK-2A). We examined how NIRvP…
이 논문을 지원한 국가R&D 과제 (NTIS 성과)
| 연도 | 과제 | 부처 | 사업 | 수행기관 | NTIS 분류(1순위) |
|---|---|---|---|---|---|
| 2023 | 서울대학교 스마트시티 글로벌 융합 혁신인재양성 교육연구단 | 교육부 | 4단계두뇌한국21사업 | 서울대학 | – |
인접 그래프
노드 hover = 이웃 강조 · 1회 클릭 = 고정 · 고정된 노드 다시 클릭 = 페이지 이동
이 문서와 연결된 페이지
교수 1
연구주제 1
정책분야 1
키워드 3
총일차생산량(GPP) · 식생 근적외선 반사율(NIRv) · 정지궤도 위성 관측